The trouble with TDD is that quite often we don't really know how our programs are going to work when we start writing them, and often make design choices iteratively as we start to realize how our software should behave.
This ultimately means, what most programmers intuitively know, that it's impossible to write adequate test coverage up front (since we don't even really know how we want the program to behave) or worse, test coverage gets in the way of the iterative design process. In theory TDD should work as part of that iterative design, but in practice it means a growing collection of broken tests and tests for parts of the program that end up being completely irrelevant.
The obvious exception to this, where I still use TDD, is when implementing a well defined spec. Anytime you need to build a library to match an existing protocol, well documented api, or even an non-trivial mathematical function, TDD is a tremendous boon. But this is only because the program behavior is well defined.
The times where I've used TDD and it makes sense it's be a tremendous productivity increase. If you're implementing some standard you can basically write the tests to confirm you understand how the protocol/api/function works.
Unfortunately most software is just not well defined up front.
>Unfortunately most software is just not well defined up front.
This is exactly how I feel about TDD, but it always feels like you're not supposed to say it. Even in environments where features are described, planned, designed, refined, written as ACs, and then developed, there are still almost always pivots made or holes filled in mid-implementation. I feel like TDD is not for the vast majority of software in practice - it seems more like something useful for highly specialist contexts with extremely well defined objective requirements that are made by, for, and under engineers, not business partners or consumers.
I forget which famous Unix personality the quote / story comes from, but it amounts to "The perfect program is the one you write after you finish the first version, throw it in the garbage, and then handle in the rewrite all the things you didn't know that you didn't know."
That rings true to my experience, and TDD doesn't add much to that process.
Screenwriters encourage a "vomit draft" -- A draft that is not supposed to be good but just needs to exist to get all the necessary parts on the page. Then a writer can choose to either fix or rewrite, but having a complete presentation of the story is an important first step.
I've advocated the same for early projects or new features. Dump something bad and flawed and inefficient, but which still accomplishes what you want to accomplish. Do it as fast as possible. This is your vomit draft.
I strongly believe that the amount a team could learn from this would be invaluable and would speed up the development process, even if every single line of code had to be scrapped and rebuilt from scratch.
The idea of the vomit draft works for narrative text because it's aimed at human consumers and humans are very adaptable when it comes to accepting input. We can absorb a whole bunch of incoherent, inconsistent content and still find the parts in it which make sense, do useful and interesting things.
An executing program is a lot less forgiving, for obvious and unavoidable reasons.
What TDD brings to the table when you are building a throwaway version is that it helps to identify and deal with the things which are pure implementation errors (failure to handle missing inputs, format problems, regression failures and incompatibilities between different functional requirements). In some cases it can speed up the delivery of a working prototype, or at least reduce the chance that the first action that the first non-developer user of your system does causes the whole application to crash.
Genuine usability failures, performance issues and failure to actually do what the user wanted will not get caught by TDD, but putting automated tests in early means that the use of the prototype as a way of revealing unavoidable bugs is not downgraded by the existence of perfectly avoidable ones. It may also make it easier to iterate on the functionality in the prototype by catching regressions during the changes cycle, although I'll admit that the existence of lots of tests here may well be a double-edged sword. It very much depends on how much the prototype changes during the iterative phase, before the whole thing gets thrown away and rebuilt.
And, when you come to building your non-throw away version, the suite of tests you wrote for your prototype give you a check list of things you want to be testing in the next iteration, even if you can't use the code directly. And it seems likely enough that at least some of your old test code can be repurposed more easily than writing it all from scratch.
This is how I write documents - start with the table of contents and fill in the blanks until the document is done.
Isn't there some law as well that states that successful software projects start with a working prototype, and software designed from the ground up is destined to fail?
Reminds me of the chapter "Plan to Throw One Away" from The Mythical Man Month.
> In most projects, the first system built is barely usable. It may be too slow, too big, awkward to use, or all three. There is no alternative but to start again, smarting but smarter, and build a redesigned version in which these problems are solved. The discard and redesign may be done in one lump, or it may be done piece-by-piece. But all large-system experience shows that it will be done. Where a new system concept or new technology is used, one has to build a system to throw away, for even the best planning is not so omniscient as to get it right the first time.
Exactly. I write my programs/systems a few times. Each time I discard the previous version and start from scratch. I end up writing code that's easy to test and easy to swap parts if needed. I also know what TDD brings to the table. On top of that I have over 15 years of professional experience... so I usually know how to write software that complies with what we usually call "good code", so TDD offers me zero help.
For more junior engineers, I think TDD can help, but once you "master" TDD, you can throw it out of the window: "clean code" will come out naturally without having to write tests first.
I was taken by TDD for about six months, years ago. I always felt that I was never good at it because edge cases I hadn’t thought of came up or the interface wasn’t actually the best/cleanest/most maintainable way to write that code.
But it got me thinking about testing while writing the class instead of shoehorning a class into a test just before the PR went up. That’s what I think my takeaway was. To this day I think about not just how clean/maintainable the code is, but also how testable the code is while I am writing it. It really helps keep monkeypatching and mocking down.
Whoever said that specific quote, it is a paraphrase of a point that Alan Kay has been making since the late 1970s. His speeches, in which he argued in favor of SmallTalk and dynamic program, make the point over and over again. I believe he said almost exactly the words you are quoting.
Doesn't matter how good you are the v1 of a program in an unknown area is always complete crap but lets you write an amazing v2 if you paid attention making v1.
Yes its not well defined, neither before nor after implementing. I've made peace with accepting it never will be.
An implementation without definition, and a whole host of assumptions gets delivered as v1.
Product expectations get lowered, bugs and defects raised, implementation is monkey patched as v2.
devs quit, managers get promoted, new managers hire new devs, they ask for the definition and they're asked to follow some flavor of the year process (TDD, Agile, whatever).... rinse and repeat v3.
it doesn't matter how well your app is designed, your UX designer is not going to tell you you need a function that does X. you just build something that looks like the thing they want, and then write some tests to make sure someone doesn't break that thing, and if you have to write a dozen functions to create it and they're testable then you test them but you don't say oh no i can't write a 13th function now because that wasn't part of the preordained plan
I think part of what you are getting at here also points to differences in what people mean by “unit test”.
It’s always possible to write a test case that covers a new high-level functional requirement as you understand it; part of the skill of test-first (disclaimer - I use this approach sometimes but not religiously and don’t consider myself a master at this) is identifying the best next test to write.
But a lot of people cast “unit test” as “test for each method on a class” which is too low-level and coupled to the implementation; if you are writing those sort of UTs then in some sense you are doing gradient descent with a too-small step size. There is no appreciable gradient to move down; adding a new test for a small method doesn’t always get you closer to adding the next meaningful bit of functionality.
When I have done best with TDD is when I start with what most would call “functional tests” and test the behaviors, which is isomorphic to the design process of working with stakeholders to think through all the ways the product should react to inputs.
I think the early TDD guys like Kent Beck probably assumed you are sitting next to a stakeholder so that you can rapidly iterate on those business/product/domain questions as you proceed. There is no “upfront spec” in agile, the process of growing an implementation leads you to the next product question to ask.
> But a lot of people cast “unit test” as “test for each method on a class” which is too low-level and coupled to the implementation; if you are writing those sort of UTs then in some sense you are doing gradient descent with a too-small step size. There is no appreciable gradient to move down; adding a new test for a small method doesn’t always get you closer to adding the next meaningful bit of functionality.
In my experience, the best time to do "test for each method on a class" or "test for each function in a module" is when the component in question is a low level component in the system that must be relied upon for correctness by higher level parts of the system.
Similarly, in my experience, it is often a waste of effort and time to do such thorough low level unit testing on higher level components composed of multiple lower level components. In those cases, I find it's much better to write unit tests at the highest level possible (i.e. checking `module.top_level_super_function()` inputs produce expected outputs or side effects)
> is when the component in question is a low level component in the system that must be relied upon for correctness by higher level parts of the system.
And then, property tests are more likely to be possible, and IMO should be preferred!
> a lot of people cast “unit test” as “test for each method on a class” which is too low-level
Definitely agree with you here - I've seen people dogmatically write unit tests for getter and setter methods at which point I have a hard time believing they're not just fucking with me. However, there's a "sweet spot" in between writing unit tests on every single function and writing "unit tests" that don't run without a live database and a few configuration files in specific locations, which (in my experience) is more common when you ask a mediocre programmer to try to write some tests.
I'm having flashbacks to a previous workplace. I was literally asked to write unit tests for getters and setters. I complained they were used elsewhere in the code, and therefore tested indirectly anyway. Nope, my PR would not be "approved" until I tested every getter and setter. I think I lasted there about 6 months.
> But a lot of people cast “unit test” as “test for each method on a class” which is too low-level and coupled to the implementation;
Those tests suit a project that applies the open-closed principle strictly, such as libraries / packages that will rarely be modified directly and will mostly be used by "clients" as their building blocks.
They don't suit a spaghetti monolith with dozens of leaky APIs that change on every sprint.
The harsh truth is that in the industry you are more likely to work with spaghetti code than with stable packages. "TDD done right" is a pipe dream for the average engineer.
I always suspect that many people who have a hard time relating to TDD already have experience writing these class & method oriented tests. So they understandably struggle with trying to figure out how to write them before writing the code.
Thinking about tests in terms of product features is how it clicked for me.
That being said, as another poster above mentioned, using TDD for unstable or exploratory features is often unproductive. But that’s because tests for uncertain features are often unproductive, regardless if you wrote them before or after.
I once spent months trying to invent a new product using TDD. I was constantly deleting tests because I was constantly changing features. Even worse, I found myself resisting changing features that needed changing because I was attached to the work I had done to test them. I eventually gave up.
I still use TDD all the time, but not when I’m exploring new ideas.
I do the same. But almost always wish I had done TDD. The times I can bring myself to git reset —-hard after I have finished exploring and then TDD it in, the code benefits. Often though I can’t bring myself to do it and I retro fit in a few tests and reorder the commit history :)
The above poster used 'TDD', not 'unit test', they are not the same thing.
You can (and often should!) have a suite of unit tests, but you can choose to write them after the fact, and after the fact means after most of the exploration is done.
I think if most people stopped thinking of unit tests as a correctness mechanism and instead thought of them as a regression mechanism unit tests as a whole would be a lot better off.
Also as an dependency canary: when your low level object tests start demanding access to databases and config files and networking, it's time for a think.
Also a passing unit test always provides up-to-date implicit documentation on how to use the tested code.
None of this either/or reasoning is correct, in my experience. In practice, I write tests both before and after implementation, for different reasons. In practice, my tests both test correctness, and of course they also work as regression tests.
Writing before the fact allows you to test your mental model of the interface, unspoiled by having the implementation fresh in your mind. (Not entirely, since you probably have some implementation ideas very early on.)
Writing tests after the fact is what you must do to explore 1) weak points that occur to you as you implement, and 2) bugs. After-the-fact testing also allows you to hone in on vagueness in the spec, which may show up as (1) or (2).
+1 on "well defined spec" -- a lot of Healthcare integrations are specified as "here's the requests, ensure your system responds like this" and being able to put those in a test suite and know where you're at is invaluable!
But TDD is fantastic for growing software as well! I managed to save an otherwise doomed project by rigorously sticking to TDD (and its close cousin Behavior Driven Development.)
It sounds like you're expecting that the entire test suite ought to be written up front? The way I've had success is to write a single test, watch it fail, fix the failure as quickly as possible, repeat, and then once the test passes fix up whatever junk I wrote so I don't hate it in a month. Red, Green, Refactor.
If you combine that with frequent stakeholder review, you're golden. This way you're never sitting on a huge pile of unimplemented tests; nor are you writing tests for parts of the software you don't need. For example from that project: week one was the core business logic setup. Normally I'd have dove into users/permissions, soft deletes, auditing, all that as part of basic setup. But this way, I started with basic tests: "If I go to this page I should see these details;" "If I click this button the status should update to Complete." Nowhere do those tests ask about users, so we don't have them. Focus remains on what we told people we'd have done.
I know not everyone works that way, but damn if the results didn't make me a firm believer.
The problem I’ve run into is that when you’re iterating fast, writing code takes double the time when you also have to write the tests.
Unit tests are still easy to write but most complex software have many parts that combine combinatorially and writing integration tests requires lots of mocking. This investment pays off when the design is stable but when business requirements are not that stable this becomes very expensive.
Some tests are actually very hard to write — I once led a project that where the code had both cloud and on-prem API calls (and called Twilio). Some of those environments were outside our control but we still had to make sure they we handled their failure modes. The testing code was very difficult to write and I wished we’d waited until we stabilized the code before attempting to test. There were too many rabbit holes that we naturally got rid of as we iterated and testing was like a ball and chain that made everything super laborious.
TDD also represents a kind of first order thinking that assumes that if the individual parts are correct, the whole will likely be correct. It’s not wrong but it’s also very expensive to achieve. Software does have higher order effects.
It’s like the old car analogy. American car makers used to believe that if you QC every part and make unit tolerances tight, you’ll get a good car on final assembly (unit tests). This is true if you can get it right all the time but it made US car manufacturing very expensive because it required perfection at every step.
Ironically Japanese carmakers eschewed this and allowed loose unit tolerances, but made sure the final build tolerance worked even when the individual unit tolerances had variation. They found this made manufacturing less expensive and still produced very high quality (arguably higher quality since the assembly was rigid where it had to be, and flexible where it had to be). This is craftsman thinking vs strict precision thinking.
This method is called “functional build” and Ford was the first US carmaker to adopt it. It eventually came to be adopted by all car makers.
> Some tests are actually very hard to write — I once led a project that where the code had both cloud and on-prem API calls
I believe that this is a fundamental problem of testing in all distributed systems: you are trying to test and validate for emergent behaviour. The other term we have for such systems is: chaotic. Good luck with that.
In fact, I have begun to suspect that the way we even think about software testing is backwards. Instead of test scenarios we should be thinking in failure scenarios - and try to subject our software to as much of those as possible. Define the bounding box of the failure universe, and allow computer to generate the testing scenarios within. EXPECT that all software within will eventually fail, but as long as it survives beyond set thresholds, it gets a green light.
In a way... we'd need something like a bastard hybrid of fuzzing, chaos testing, soak testing, SRE principles and probabilistic outcomes.
>I believe that this is a fundamental problem of testing in all distributed systems: you are trying to test and validate for emergent behaviour. The other term we have for such systems is: chaotic. Good luck with that
Emergent behaviour is complex, not chaotic. Chaos comes from sensitive dependence on initial conditions. Complexity is associated with non-ergodic statistics (i.e. sampling across time gives different results to sampling across space).
I work in Erlang virtual machine (elixir) and I am regularly writing tests against common distributed systems failures? You don't need property tests (or jeppsen maelstrom - style fuzzing) for your 95% scenarios. Distributed systems are not magically failure prone.
> TDD also represents a kind of first order thinking that assumes that if the individual parts are correct, the whole will likely be correct. It’s not wrong
In fact it is not just wrong, but very wrong, as your auto example shows. Unfortunately engineers are not trained/socialised to think as holistically as perhaps they should be.
The non-strawman interpretation of TDD is the converse: if the individual parts are not right, then the whole will probably be garbage.
It's worth it to apply TDD to the pieces to which TDD is applicable. If not strict TDD than at least "test first" weak TDD.
The best candidates for TDD are libraries that implement pure data transformations with minimal integration with anything else.
(I suspect that the rabid TDD advocates mostly work in areas where the majority of the code is like that. CRUD work with predictable control and data flows.)
Yes. Agree about TDD being more suited to low dependency software like CRUD apps or self contained libraries.
Also sometimes even if the individual parts aren’t right, the whole can still work.
Consider a function that handles all cases except for one that is rare, and testing for that case is expensive.
The overall system however can be written to provide mitigations upon composing — eg each individual function does a sanity check on its inputs. The individual function itself might be wrong (incomplete) but in the larger system, it is inconsequential.
Test effort is not a 1:1. Sometimes the test can be many times as complicated to write and maintain as the function being tested because it has to generate all the corner cases (and has to regenerate them if anything changes upstream). If you’re testing a function in the middle of a very complex data pipeline, you have regenerate all the artifacts upstream.
Whereas sometimes an untested function can be written in such a way where it is inherently correct from first principles. An extreme analogy would be the Collatz conjecture. If you start by first writing the test, you’d be writing an almost infinite corpus of tests — on the flip side, writing the Collatz function is extremely simple and correct up to large finite number.
Computer code is an inherently brittle thing, and the smallest errors tend to cascade into system crashes. Showstopper bugs are generated from off-by-one errors, incorrect operation around minimum and maximum values, a missing semicolon or comma, etc.
And doing sanity check on function inputs addresses only a small proportion of bugs.
I don't know what kind of programming you do, but the idea that a wrong function becomes inconsequential in a larger system... I feel like that just never happens unless the function was redundant and unnecessary in the first place. A wrong function brings down the larger system feels like the only kind of programming I've ever seen.
Physical unit tolerances don't seem like a useful analogy in programming at all. At best, maybe in sysops regarding provisioning, caches, API limits, etc. But not for code.
> I don't know what kind of programming you do, but the idea that a wrong function becomes inconsequential in a larger system... I feel like that just never happens unless the function was redundant and unnecessary in the first place. A wrong function brings down the larger system feels like the only kind of programming I've ever seen.
I think we’re talking extremes here. An egregiously wrong function can bring down a system if it’s wrong in just the right ways and it’s a critical dependency.
But if you look at most code bases, many have untested corner cases (which they’re likely not handling) but the code base keeps chugging along.
Many codebases are probably doing something wrong today (hence GitHub issues). But to catastrophize that seems hyperbolic to me. Most software with mistakes still work. Many GitHub issues aren’t resolved but the program still runs. Good designs have redundancy and resilience.
A counter to that could be all the little issues found by fuzz testing legacy systems and static analysis. Often in widely used software where those issues did not indeed manifest. Unit tests also don't prove correctness, they're as good as the writer of the unit test's ability to predict failure.
I can tell you that most (customer) issues in the software I work on are systemic issues, the database fails (widely used OSS) can corrupt under certain scenarios. They can be races, behaviour under failure modes, lack of correctness on some higher order (e.g. having half failed operations), the system not implementing the intent of the user. I would say very rarely those are issues that would have been caught by unit testing. Now integration testing and stress testing will uncover a lot of those. This is a large scale distributed system.
Now sometimes after the fact a unit test can somehow be created to reproduce the specific failure, possibly at great effort. That's not really something that useful at this point. You wouldn't write that in advance for every possible failure scenario (infinite).
All that said, sometimes there's attacks on systems that relate to some corner cases errors, which is a problem. Static analysis and fuzzers are IMO more useful tools in this realm as well. Also I think I'm hearing "dynamic/interepreted" language there (missing semicolons???). Those might need more unit testing to make up for the lack of compiler checks/warnings/type safety for sure.
The other point that's often missed is the drag that "bad" tests add to a project. Since it's so hard to write good tests when you mandate testing you end up with a pile of garbage that makes it harder to make progress. Other factors are the additional hit you take maintaining your tests.
Basically choosing the right kind of tests, at the right level, is judgement. You use the right tool for the right job. I rarely use TDD but I have used it in cases where the problem can relatively easily be stated in terms of tests and it helps me get quick feedback on my code.
EDIT: Also as another extreme thought ;) some software out there could be working because some function isn't behaving as expected. There's lots of C code out there that uses things that are technically UB but do actually have some guarantee under some precise circumstances (but idea but what can you do). In this case the unit test would pass despite the code being incorrect.
I work in software testing, and I've seen this many times actually. Small bugs that I notice because I'm actually reading the code, which became inconsequential because that code path is never used anymore or the result is now discarded, or any of a number of things that change the execution environment of that piece of code.
If anything I'm wondering the same question about you. If you find it so inconceivable that a bug is hiding in working code that is held up because the calling environment around it, than you must not have worked with big or even moderately sized codebases at all.
> sometimes even if the individual parts aren’t right, the whole can still work.
And in fact, fault tolerance with the assumption that all of it's parts are unreliable and will fail quickly makes for more fault tolerant systems.
The _processes and attitude_ that cause many individual parts to be incorrect will also cause the overall system to be crap. There's a definite correlation, but that correlation isn't about any specific part.
Yes. Though my point is not that we should aim for a shaky foundation, but that if one is a craftsman one ought to know where to make trade offs to allow some parts of the code to be shaky with no consequences. This ability to understand how to trade off perfection for time — when appropriate — is what distinguishes senior from junior developers. The idea of ~100% correct code base is an ideal — it’s achieved only rarely on very mature code bases (eg TeX, SQLite).
Code is ultimately organic, and experienced developers know where the code needs be 100% and where the code can flex if needed. People have this idea that code is like mathematics where if one part fails, every part fails. To me if that is so, the design too tight and brittle and will not ship on time. But well designed code is more like an organism that has resilience to variation.
If individual parts being correct meant the whole thing will be correct, that means if you have a good sturdy propeller and you put it on top of your working car, then you have a working helicopter.
> writing code takes double the time when you also have to write the tests
this time is more than made up for by the usual subsequent loss of debugging, refactoring and maintenance time, in my experience, at least for anything actively being used and updated
Yes, if you were right about the requirements, even if they weren't well specified. But if it turns out you implemented the wrong thing (either because the requirements simply changed for external reasons, or because you missed some fundamental aspect), then you wouldn't have had to debug, refractor or maintain that initial code, and the initial tests will probably be completely useless even if you end up salvaging some of the initial implementation.
form a belief about a requirement
write a test
test fails
write code
test fails
add debug info to code
test fails no debug showing
call code directly and see debug code
change assert
test fails
rewrite test
test succeed
output test class data.. false
positive checking null equals null
rewrite test
test passes
forget original purpose and stare at green passing tests with pride.
On a more serious note: just learn to use a debugger, and add asserts, if need be. To me TDD only helps having something that would run your code - but that's pretty much it. If you have other test harness options, I fail to see the benefits outside conference talks and books authoring.
Yes, so much this. I don’t really understand how people could object to TDD. It’s just about putting together what one manually does otherwise. As a bonus, it’s not subject to biases because of after-the-fact testing.
>at least for anything actively being used and updated
This implies that the strength of the tests appears when it's modified?
Like the article says, TDD doesn't own the concept of testing. You can write good tests without submitting yourself to a dogma of red/green, minimum-passing (local-maximum-seeking) code. Debating TDD is tough because it gets bogged down with having to explain how you're not a troglodyte who writes buggy untested code.
And - on a snarkier note - this is a better argument against dynamic typing than for TDD.
I can't remember the last time the speed at which I could physically produce code was the bottleneck in a project. It's all about design and thinking through and documenting the edge cases, and coming up with new edge cases and going back to the design. By the time we know what we're going to write, writing the code isn't the bottleneck, and even if it takes twice as long, that's fine, especially since I generally end up designing a more usable interface as a result of using it (in my tests) as it's being built.
> The problem I’ve run into is that when you’re iterating fast, writing code takes double the time when you also have to write the tests.
The times I have believed this myself, often turned out to be wrong when the full cost of development was taken into account. And I came back to the code later wishing I had tests around it. So you end up TDDing only the bug fix and exercising that part of the code with the failing test and then the code correction.
> The problem I’ve run into is that when you’re iterating fast, writing code takes double the time when you also have to write the tests.
That was the time it took to actually write working code for that feature.
The version of "working code" that took 50% as long was just a con to fool people into thinking you'd finished until they move onto other things and a "perfectly acceptable" regression is discovered.
The reason someone is iterating fast is usually because they are trying to discover the best solution to a problem by building things. Once they have found this then they can write "working code". But they don't want to have to write tests for all the approaches that didn't work and will be thrown away after the prototyping phase.
There are two problems I've seen with this approach. One is that sometimes the feature you implemented and tested turns out to be wrong.
Say, initially you were told "if I click this button the status should update to complete", you write the test, you implement the code, rinse and repeat until a demo. During the demo, you discover that actually they'd rather the button become a slider, and it shouldn't say Complete when it's pressed, it should show a percent as you pull it more and more. Now, all the extra care you did to make sure the initial implementation was correct turns out to be useless. It would have been better to have spent half the time on a buggy version of the initial feature, and found out sooner that you need to fundamentally change the code by showing your clients what it looks like.
Of course, if the feature doesn't turn out to be wrong, then TDD was great - not only is your code working, you probably even finished faster than if you had started with a first pass + bug fixing later.
But I agree with the GP: unclear and changing requirements + TDD is a recipe for wasted time polishing throw-away code.
Edit: the second problem is well addressed by a sibling comment, related to complex interactions.
> Say, initially you were told "if I click this button the status should
> update to complete", you write the test, you implement the code, rinse and
> repeat until a demo. During the demo, you discover that actually they'd
> rather the button become a slider, and it shouldn't say Complete when it's
> pressed, it should show a percent as you pull it more and more. Now, all the
> extra care you did to make sure the initial implementation was correct turns
> out to be useless.
Sure, this happens. You work on a thing, put it in front of the folks who asked for it, and they realize they wanted something slightly different. Or they just plain don't want the thing at all.
This is an issue that's solved by something like Agile (frequent and regular stakeholder review, short cycle time) and has little to do with whether or not you've written tests first and let them guide your implementation; wrote the tests after the implementation was finished; or just simply chucked automated testing in the trash.
Either way, you've gotta make some unexpected changes. For me, I've really liked having the tests guide my implementation. Using your example, I may need to have a "percent complete" concept, which I'll only implement when a test fails because I don't have it, and I'll implement it by doing the simplest thing to get it to pass. If I approach it directly and hack something together I run the risk of overcomplicating the implementation based on what I imagine I'll need.
I don't have an opinion on how anyone else approaches writing complex systems, but I know what's worked for me and what hasn't.
Respectfully, I think the distinction they're making it that "writing ONE failing test then the code to pass it" is very different than "write a whole test suite, and then write the code to pass it".
The former is more likely to adapt to the learning inherent in the writing of code, which someone above mentioned was easy to lose in TDD :)
One of the above comments mentions BDD as a close cousin to TDD, but that is wrong as TDD is actually BDD as you should only be testing behaviours, which allow you to "fearlessly refactor"
I don't think TDD gets to own the concept of having a test for what you're refactoring. That's just good practice & doesn't require that you make it fail first.
This falls under the category of problems where verifying, hell describing, the result is harder than the code to produce it.
Here’s how I would do it. The challenge is that the result can’t be precisely defined because it’s essentially art. But with TDD the assertions don’t actually have to actually live in code. All we have to do is make incremental verifiable progress that lets us fearlessly make changes.
So I would set up my viewport as a grid where in each square there will eventually live a rendered image or animation. The first one blank, the second one a dot, the third a square, the fourth with color, the fifth a rhombus, the sixth with two disjoint rhombuses …
When you’re satisfied with each box you copy/paste the code into the next one and work on the next test always rendering the previous frames. So you can always reference all the previous working states and just start over if needed.
So the TDD flow becomes
1. Write down what you want the result of the next box to look like.
2. Start with the previous iteration and make changes until it looks like what you wanted.
Using wetware test oracles is underappreciated. You can't do it in a dumb way, of course, but with a basic grasp of statistics and hypothesis testing you can get very far with sprinkles of manual verification of test results.
(Note: manual verification is not the same as manual execution!)
And that’s happening. The next test is “the 8th box should contain a rhombus slowly rotating clockwise” and it’s failing because the box is currently empty. So now you write code.
No, this is nonsense. You don't write the test coverage up front!
You think of a small chunk of functionality you are comfident about, write the tests for that (some people say just one test, i am happy with up to three or so), then write the implementation that makes those tests pass. Then you refactor. Then you pick off another chunk and 20 GOTO 10.
If at some point it turns out your belief about the functionality was wrong, fine. Delete the tests for that bit, delete the code for it, make sure no other tests are broken, refactor, and 20 GOTO 10 again.
The process of TDD is precisely about writing code when you don't know how the program is going to work upfront!
On the other hand, implementing a well-defined spec is when TDD is much less useful, because you have a rigid structure to work to in both implementation and testing.
I think the biggest problem with TDD is that completely mistaken ideas about it are so widespread that comments like this get upvoted to the top even on HN.
I feel like I'm in crazy town in this thread. Most of the replies seem to be misunderstanding the intent of TDD, and yours is one of the few that gets it right.
Is general understanding of TDD really that far off the mark? I had no idea, and I've been doing this for essentially 2 decades now.
No we really understand that the whole religion of only writing code after a failing test only applies to niche cases of libraries for headless applications in monoliths.
Lets say my designer came to me and now wants bump mapped textures on engine, well I cannot touch that compute shader without writing a test first, so suggestions for a TDD framework for GPU shaders.
Ive done a form of TDD where I have a test scenario set up that generates a picture and I tweak the code until the picture looks right and then "freeze" it.
Once frozen the test compares the picture (or other artefact) against the generated picture (or artefact).
Im not sure if it'd be useful in your situation though.
The code changes that changed the UI - even changing some CSS - would cause a screenshot comparison failure on certain steps in the test. If it is what was expected then we overwrote the old screenshot with a new one.
It isnt exactly the same as the TDD process coz sometimes you write the code first (e.g. CSS), eyeball it and then rebuild the screenshot if it looks correct.
I'd say it's close enough though.
I wont pretend it worked perfectly. The screenshot comparison algorithms were sometimes flaky and UIs can be surprisingly non-determinstic and you need to have a process to pull the database and update screenshots accordingly. However, it's the approach I'd prefer to take in the future (I havent done UIs for about 3 years now).
I also wasnt religious about covering every single scenario with tests but I could have been. The company moved fast and sometimes they just wanted quick and not reliable.
That is the whole deal, it was Web, so kind of easier than native, given its source based form, and even then, you had to bend the rules from TDD religion.
I think you're being a little uncharitable to the TDD folks here. Sure the early writing was very dogmatic, but real world TDD doesn't seem to be to be as rigid as you describe.
Or perhaps you've worked with some real TDD zealots, that doesn't sound like fun.
The folks I've worked with use these as guiding recommendations, not binding dictates.
For some of the UI stuff you mentioned elsewhere, I've seen a stronger focus on testing not just business logic, but view logic as well (where possible), but generally not to the degree of testing the rendered output of the UI. Maybe that's a thing somewhere, but I haven't personally seen it.
The same sort of thing should be possible for various kinds of native too. You'll need a selenium-esque library that can interact with UIs and take screenshots in your environment.
But yeah, if you dont have one of those tools or its super unreliable or it's only available in a language you cant use then you cant do this.
I dont really consider this to be bending the rules of TDD. It's more like next gen TDD IMO.
The big issue I see when people have trouble with TDD is really a cultural one and one around the definition of tests, especially unit tests.
If you're thinking of unit tests as the thing that catches bugs before going to production and proves your code is correct, and want to write a suite of tests before writing code, that is far beyond the capabilities of most software engineers in most orgs, including my own. Some folks can do it, good for them.
But if you think of unit tests as a way to make sure individual little bits of your code work as you're writing them (that is, you're testing "the screws" and "the legs" of the tables, not the whole table), then it's quite simple and really does save time, and you certainly do not need full specs or even know what you're doing.
Write 2-3 simple tests, write a function, write a few more tests, write another function, realize the first function was wrong, replace the tests, write the next function.
You need to test your code anyway and type systems only catch so much, so even if you're the most agile place ever and have no idea how the code will work, that approach will work fine.
If you do it right, the tests are trivial to write and are very short and disposable (so you don't feel bad when you have to delete them in the next refactor).
Do you have a useful test suite to do regression testing at the end? Absolutely not! In the analogy, if you have tests for a screw attaching the leg of a table, and you change the type of legs and the screws to hook them up, of course the tests won't work anymore. What you have is a set of disposable but useful specs for every piece of the code though.
You'll still need to write tests to handle regressions and integration, but that's okay.
And I think most people who don't write tests in code work that way anyway, just manually -- they F5 the page, or run the code some other way.
But the end result of writing tests is often that you create a lot of testing tied to what should be implementation details of the code.
E.g. to write "more testable" code, some people advocate making very small functions. But the public API doesn't change. So if you test only the internal functions, you're just making it harder to refractor.
> But the end result of writing tests is often that you create a lot of testing tied to what should be implementation details of the code.
This is the major issue I have with blind obedience to TDD.
It often feels like the question of "What SHOULD this be doing" isn't asked and instead what you end up with is a test suite that answers the question "What is this currently doing?"
If refactoring code causes you to refactor tests, then your tests are too tightly coupled to implementation.
Perhaps the missing step to TDD is deleting or refactoring the test at the end of the process so you better capture intent rather than the flow of consciousness.
Example: I've seen code that had different code paths to send in a test "logger" to ensure the logger was called at the right locations and said the right messages. That made it difficult add new information to the logger or add new logger messages. And for what?
If your goal is to avoid coupling tests to implementation then TDD seems like the most obvious strategy. You write the test before the implementation, so it is much harder to end up with the coupling than other strategies.
I often TDD little chunks of code, end up deciding they make more sense inside larger methods, and delete the tests. But that's ok, the test was still useful to help me develop the chunk of code.
Many people have a wrong perception of TDD. The main idea is to break a large, complicated thing into many small ones until there is nothing left, like you said.
You're not supposed to write every single test upfront, you write a tiny test first. Then you add more and refactor your code, repeat until there is nothing left of that large complicated thing you were working on.
There are also people who test stupid things and 3rd party code in their tests and either they get a fatigue from it and/or think their tests are well written.
>If you do it right, the tests are trivial to write and are very short and disposable (so you don't feel bad when you have to delete them in the next refactor).
The raison d'etre of TDD is that developers can't be trusted to write tests that pass for the right reason - that they can't be trusted to write code that isn't buggy. Yet it depends on them being able to write tests with enough velocity that they're cheap enough to dispose?
Yep, TDD for little chunks of code is really nice, I think of it like just a more structured way to trying things out in a repl as you go (and it works for languages without repls). Even if you decide to never check the test in because the chunk of code ended up being too simple for a regression test to be useful, if it was helpful in testing assumptions while developing the code, that's great.
But yeah, trying to write all the tests for a whole big component up front, unless it's for something with a stable spec (eg. I once implemented some portions of the websockets spec in servo, and it was awesome to have an executable spec as the tests), is usually an exercise in frustration.
I think we should try and separate exploration from implementation. Some of the ugliest untestable code bases I have worked with have been the result of some one using exploratory research code for production. It's OK to use code to figure out what you need to build, but you should discard it and create the testable implementation that you need. If you do this, you won't be writing tests up front when exploring the solution space, but you will be when doing the final implementation.
Have you ever had to convince a non-technical boss or client that the exploratory MVP you wrote and showed to them working must be completely rewritten before going into production? I tried that once when I attempted to take us down the TDD route and let me tell you, that did not go over well.
People blame engineers for not writing tests or doing TDD when, if they did, they would likely be replaced with someone who can churn out code faster. It is rare, IME, to have culture where the measured and slow progress of TDD is an acceptable trade off.
Places where software is carrying a great deal of value tend to be more like that. That is, if mistakes can cost $20,000 / hour or so, then even the business will back down on the push now vs. be sure it works debate.
As always, the job of a paid software person is to merge what the product people want with what good software quality requires (and what power a future version will unleash). Implement valuable things in software in a way that makes the future of that software better and more powerful.
I've always favored exploration before implementation [1]. For me TDD has immense benefit when adding something well defined, or when fixing bugs. When it comes to building something from scratch i found it to get in the way of the iterative design process.
I would however be more amenable to e.g. Prototyping first, and then using that as a guide for TDD. Not sure if there is a name for that approach though. "spike" maybe?
I find that past a certain size, even exploratory code base benefits from having tests. Otherwise, as I'm hacking, I end up breaking existing functionality. Then I spend more time debugging trying to figure out what changed.. what's your experience when it comes to more than a few hundred lines of code?
Indeed, but once you start getting to that point I'd argue you are starting to get beyond a prototype. But you raise a good point, id say if the intention is to throw the code away (which you probably should) then if add as few tests as will allow you to make progress.
I think this is the reasonable approach I take. It's ok to explore and figure out the what. Once you know (or the business knows) then it's time to write a final spec and test coverage. In the end, the mantra should be "it's just code".
This makes sense, but I think many (most?) pipelines don't allow for much playtime because they are too rigid and top-down. At best you will convince somebody that a "research task" is needed, but even that is just another thing you have to get done in the same given time frame. Of course this is the fault of management, not of TDD.
> The trouble with TDD is that quite often we don't really know how our programs are going to work
Interesting - for me, that's the only time I truly practice TDD, when I don't know how the code is going to work. It allows me to start with describing the ideal use case - call the API / function I would like to have, describe the response I would expect. Then work on making those expectations a reality. Add more examples. When I run into a non-trivial function deeper down, repeat - write the ideal interface to call, describe the expected response, make it happen.
For me, TDD is the software definition process itself. And if you start with the ideal interface, chances are you will end up with something above average, instead of whatever happened to fall in place while arranging code blocks.
Agile, as the name hints, was developed precisely to deal with ever changing requirements. In opposition to various versions of "first define the problem precisely, then implement that in code, and then you're done forever".
So the TDD OP describes here is not an Agile TDD.
The normal TDD process is:
1. add one test
2. make it (and all others) pass
3. maybe refactor so code is sane
4. back to 1, unless you're done.
When requirements change, you go to 1 and start adding or changing tests, iterate until you're done.
Exactly. Nobody's on board with paying at least twice as much for software though. But that's what you get when things change and you have to refactor BOTH your code AND your tests.
But what is your process for determining code is correct, and is it really faster and more reliably than writing tests? Sheer force of will? Running it through your brain a few times? Getting peer review? I often find tests that all things being equal tests are just the fastest way to review my own work, even if I hate writing them sometimes.
To have automated tests does not mean you have well-defined requirements.
I 100% agree with capturing requirements in tests. However, I argue that TDD does not cause that to happen.
I'd even make a stronger statement. Automated tests that don't capture a requirement should be deleted. Those sorts of tests only serve to hinder future refactoring.
A good test for a sort method is one that verifies data is sorted at the end of it. A bad test for a sort method is one that checks to see what order elements are visited in the sorting process. I have seen a lot of the "element order visit" style tests but not a whole lot of "did this method sort the data" style tests.
Imagine that in the process of implementing the sort method, you decide "I'm going to use a heap sort".
So, you say "Ok, I'll need a `heapify` method and a `siftDown` methods, so I'm going to write the tests to make sure both of those are working properly". But remember, we started this discussion saying "we need a sort method". So now, if you decide "You know what, heapsort is garbage, let's do tim sort instead!" Now, all the sudden you've got a bunch of useless tests. In the best case, you can simply delete those tests, but often devs often get intimidated deleting such tests "What if something else needs the `heapify` method"?
And that's exactly the problem I was pointing out with the example. We started the convo saying "tests couple implementation" and that's what's happened here. Our tests are making it seem like heap sort is the implementation we should use when we started this convo, we just needed a sorting method.
But now imagine we are talking about something way more complicated and/or less well known than a sorting algorithm. Now, it becomes a lot harder to sift out which tests are for implementation things and which are for requirements things. Without deleting the "these tests make sure I did a good implementation" future maintainers of the code are left to guess on what's a requirement and what's an implementation detail.
You don't write unit tests for heap sort, you write them for sort. Then you get them to pass using heap sort. Later, you replace heap sort with tim sort, and you can write it quickly and with confidence, because the test suite shows you when you've succeeded.
Public interfaces should change only under extreme circumstances, so needing to refactor legacy tests should be a rare event. Those legacy tests will help ensure that your public interface hasn't changed as it is extended to support changing requirements. You should not be testing private functions, leaving you free to refactor endlessly behind the public interface. What goes on behind the public interface is to be considered a black box. The code will ultimately be tested by virtue of the public interface being tested.
Assuming any piece of code won't or shouldn't be changed feels wrong. If you're a library developer you have to put processes in place to account for possible change. If not those public interfaces are just as refactorable as any other code imo. Nothing would be worse than not being able to implement a solution in the best manner because someone decided on an interface a year ago and enshrined it in unit tests.
Much, much worse is users having to deal with things randomly breaking after an update because someone decided they could make it better.
That's not to say you can't seek improvement. The public interface can be expanded without impacting existing uses. If, for example, an existing function doesn't reflect your current view of the world add a new one rather than try to jerry-rig the old one. If the new solutions are radically different such that you are essentially rewriting your code from scratch, a clean break is probably the better route to go.
If you are confident that existing users are no longer touching your legacy code, remove it rather than refactor it.
Things change. You change the code in response. What broke? Without the tests, you don't know.
"Things change" include "you fixed a bug". Bug fixes can create new bugs (the only study I am familiar with says 20-50% probability). Did your bug fix break anything else? How do you know? With good test coverage, you just run the tests. (Yes, the tests are never complete enough. They can be complete enough that they give fairly high confidence, and they can be complete enough to point out a surprising number of bugs.)
Does that make you pay "at least twice"? No. It makes you pay, yes, but you get a large amount of value back in terms of actually working code.
That can be an acceptable risk actually and it does quite often. There are two conceptually different phases in SDLC: verification that proves implementation is working according to spec and validation that proves that spec matches business expectations. Automated tests work on first phase, minimizing the risk that when reaching the next phase we will be validating the code that wasn’t implemented according to spec. If that risk is big enough, accepting the refactoring costs after validation may make a lot of sense.
Is it twice as much? I think unsound architectural practices in software is the root cause of this issue, not red green refactor.
You aren't doing "double the work" even though it seems that way on paper, unless the problem was solved with brittle architectural foundations and tightly coupled tests.
At the heart of this problem is most developers don't quite grasp boundary separation intuitively I think.
> The trouble with TDD is that quite often we don't really know how our programs are going to work when we start writing them
Even if you know exactly how the software is going to work, how would you know if your test cases are written correctly without having the software to run them against? For that reason alone, the whole idea of TDD doesn't even make sense to me.
One reason why TDD can be a good idea is the cycle involves actually testing the test cases: if you write the test, run it and see that it fails, then write the code, then run the test again and see that it succeeds, you can have some confidence the test is actually testing something (not necessarily the right thing, but at least something). Wheras if you're writing the test after writing the code and expect that it will succeed the first time you run it, it's quite possible to write a test which doesn't actually test anything and will always succeed. (There are other techniques like mutation testing which may get you a more robust indication that your tests actually depend on the state of your software, but I've rarely seem them used in practice).
Good point. Sometimes I cheat and implement before I test, but often when I do that I'll comment & uncomment the code that actually does the thing so I can see the tests go from red to green.
Have been meaning to try mutation testing as a way of sussing out tests that cover lines but don't actually test behavior.
Snap, me too, amazing how many times it catches a simple mistake too like a < instead of > that you were certain you got the right way round as you wrote it.
Most tests shouldn't be hard to read and reason about so it shouldn't be a problem. In case of more complex tests, you can do it like you would do it during iterative development - debug tests and code to figure out what's wrong - nothing changes here.
It’s funny that in your paragraph there I thought you were about to write… “for that reason alone, TDD is the only way that makes sense to me.”
The reason is, the tests and the code are symbiotic, your tests prove the code works and your code proves the tests are correct. TDD guarantees you always have both of those parts. But granted it is not the only way to get those 2 parts.
You can still throw into the mix times when a bug is present, and it is this symbiotic relationship that helps you find the bug fast, change the test to exercise the newly discovered desired behaviour, see the test go red for the correct reason and then make the code tweak to pass the test (and see all the other tests still pass).
This is exactly my problem with TDD. Note this problem is not only in SW. For any development you do, you could start with designing tests. You can do for some HW for sure. If you want to apply TDD to any other development, you see pretty fast, what the problem is: you are going to design lots of tests, that a at the end will not be used. A total waste.
Also with TDD often it will be centered in quantity of tests and not so much quality.
What I find is much much better approach is what I call "detached test development" (DTD). The idea is: 2 separate teams get the requirements; one team writes code, the other write tests. They do not talk to each other! Fist when a test is not passed, they have to discuss: is the requirement not clear enough? What is the part that A thought about, but not B?
Assignment of tests and code can be mixed, so a team makes code for requirements 1 through 100, and tests for 101 to 200, or something like that. I had very very good results with such approach.
Who starts with designing just the tests? I have no idea how this is an association with TDD.
TDD is a feedback cycle, you write small increments of tests before writing a small bit of a code. You don't write a bunch of tests upfront, that'd be silly. The whole point is to integrate small amounts of learning as you go, which help guide the follow-on tests, as well as the actual implementation, not to mention questions to need to ask the broader business.
Your DTD idea has been tried a lot in prior decades. In fact, as a student I was on one of those testing teams. It's a terrible idea, throwing code over a wall like that is a great way to radically increase the latency of communication, and to have a raft of things get missed.
I have no idea why there's such common misconceptions of what TDD is. Maybe folks are being taught some really bad ideas here?
> Also with TDD often it will be centered in quantity of tests and not so much quality.
100%. Metrics of quality are really really hard to define in a way that are both productive and not gamified by engineers.
> What I find is much much better approach is what I call "detached test development" (DTD)
I'm a test engineer and some companies do 'embed' an SDET like the way you mention within a team - it's not quite that clear cut, they can discuss, but it's still one person implementing and another testing.
I'm always happy to see people with thoughts on testing as a core part of good engineering rather than an afterthought/annoyance :)
What you described is a quite common role of QA automation team, but it does not really replace TDD. Separate team working on a test can do it only relying on a remote contract (e.g. API, UI or database schema), they cannot test local contracts like a public interface of a class, because that would require the that code already to be written. In TDD you often write the code AND the test at the same time, integrating the test and the code in compile time.
>2 separate teams get the requirements; one team writes code, the other write tests.
This feels a bit like when you write a layer of encapsulation to try to make a problem easier only to discover that all of the complexity is now in the interface. Isn't converting the PO's requirements into good, testable requirements the hard technical bit?
thats kind of TDDs core point. you don't really know upfront, so you write tests to validate what you can define up front, and through that, you should find you discover other things that were not accounted for, and the cycle continues, until you have a working system that satisfies the requirements. Then all those tests serve as a basic form of documentation & reasonable validation of the software so when further modifications are desired, you don't break what you already know to be reasonably valid.
Therefore, TDD's secret sauce is in concretely forcing developers to think through requirements, mental models etc. and quantify them in some way. When you hit a block, you need to ask yourself whats missing, then figure out, and continue onward, making adjustments along the way.
This is quite malleable to unknown unknowns etc.
I think the problem is most people just aren't chunking down the steps of creating a solution enough. I'd argue that the core way of approaching TDD fights most human behavioral traits. It forces a sort of abstract level of reasoning about something that lets you break things down into reasonable chunks.
What's inherent about this problem that wouldn't benefit from chunking things into digestible, iterative parts that lend themselves nicely to the TDD approach as I described?
What about behaviors and expectations? At the end of the day you’re verifying behaviors and expectations of software. I mean when designing a solution you need to think these things through. TDD compliments this just the same
> test coverage gets in the way of the iterative design process. In theory TDD should work as part of that iterative design, but in practice it means a growing collection of broken tests and tests for parts of the program that end up being completely irrelevant.
So much of this is because TDD has become synonymous with unit testing, and specifically solitary unit testing of minimally sized units, even though that was often not the original intent of the ideators of unit testing. These tests are tightly coupled to your unit decomposition. Not the unit implementation (unless they're just bad UTs), but the decomposition of the software into which units/interfaces. Then the decomposition becomes very hard to change because the tests are exactly coupled to them.
If you take a higher view of unit testing, such as what is suggested by Martin Fowler, a lot of these problems go away. Tests can be medium level and that's fine. You don't waste a bunch of time building mocks for abstractions you ultimately don't need. Decompositions are easier to change. Tests may be more flaky, but you can always improve that later once you've understood your requirements better. Tests are quicker to write, and they're more easily aligned with actual user requirements rather than made up unit boundaries. When those requirements change, it's obvious which tests are now useless. Since tests are decoupled from the lowest level implementation details, it's cheap to evolve those details to optimize implementation details when your performance needs change.
> The trouble with TDD is that quite often we don't really know how our programs are going to work when we start writing them, and often make design choices iteratively as we start to realize how our software should behave.
This is a trouble I often see expressed about static types. And it’s an intuition I shared before embracing both. Thing is, embracing both helped me overcome the trouble in most cases.
- If I have a type interface, there I have the shape of the definition up front. It’s already beginning to help verify the approach that’ll form within that shape.
- Each time I write a failing test, there I have begun to define the expected behavior. Combined with types, this also helps verify that the interface is appropriate, as the article discusses, though not in terms of types. My point is that it’s also verifying the initial definition.
Combined, types and tests are (at least a substantial part of) the definition. Writing them up front is an act of defining the software up front.
I’m not saying this works for everyone or for every use case. I find it works well for me in the majority of cases, and that the exception tends to be when integrating with systems I don’t fully understand and which subset of their APIs are appropriate for my solution. Even so writing tests (and even sometimes types for those systems, though this is mostly a thing in gradually typed languages) often helps lead me to that clarity. Again, it helps me define up front.
All of this, for what it’s worth, is why I also find the semantics of BDD helpful: they’re explicit about tests being a spec.
> Unfortunately most software is just not well defined up front.
This is true, and I think that's why TDD is a valuable exercise to disambiguate requirements.
You don't need to take an all/nothing approach. Even if you clarify 15-20% of the requirements enough to write tests before code, that's a great place to begin iterating on the murky 80%.
>Unfortunately most software is just not well defined up front.
Because for years people have practice with defining software iteratively, whether by choice or being forced by deadlines and agile.
That doesn't inherently make one or the other harder, it's just another familiarity problem.
TDD goes nicely with top-down design using something like Haskell's undefined to stub out functionality that typechecks and it's where clauses.
myFunction = haveAParty . worldPeace . fixPoverty $ world
where worldPeace = undefined
haveAParty = undefined
fixPoverty = undefined
Iterative designs usually suck to maintain and use because they reflect the organizational structure of your company. That'll happen anyway to an extent, but better abstractions to make future you and future co-workers lives easier are totally worth it.
I often come up with test cases (just the cases, not the actual logic) while writing the feature. However I am never in the mood to context switch to write the test, so I'll do the bare minimum. I'll flip over to the test file and write the `it()` boilerplate with the one-line test title and flip back to writing the feature.
By the time I've reached a point where the feature can actually be tested, I end up with a pretty good skeleton of what tests should be written.
There's a hidden benefit to doing this, actually. It frees up your brain from keeping that running tally of "the feature should do X" and "the feature should guard against Y", etc. (the very items that go poof when you get distracted, mind you)
I seem to remember this being mentioned in the original TDD book. To brain dump that next test scenario title you think of so as to get it out of your head and get back to the current scenario you are trying to make pass. So by the same idea as above, to not context switch between the part of the feature you are trying to get to work.
jeez, well defined spec? what a weird concept. Instead, we took a complete 180 and all we get are weekly sprints. just start coding, don't spend time understanding your problem. what a terrible concept.
Even for something which is well defined up-front this can of dubious value.
Converting an positive integer less than 3000 is well-defined task.
Now if you try to write such a program using TDD what do you think will end up with?
Try it. Write a test for 1, and an implementation which passes that test then for 2, and so on.
Bellow is something written without any TDD (in Java)
private static String convert(int digit, String one, String half, String ten) {
switch(digit) {
case 0: return "";
case 1: return one;
case 2: return one + one;
case 3: return one + one + one;
case 4: return one + half;
case 5: return half;
case 6: return half + one;
case 7: return half + one + one;
case 8: return half + one + one + one;
case 9: return one + ten;
default:
throw new IllegalArgumentException("Digit out of range 0-9: " + digit);
}
}
public static String convert(int n) {
if (n > 3000) {
throw new IllegalArgumentException("Number out of range 0-3000: " + n);
}
return convert(n / 1000, "M", "", "") +
convert((n / 100) % 10, "C", "D", "M") +
convert((n / 10) % 10, "X", "L", "C") +
convert(n % 10, "I", "V", "X");
}
> In theory TDD should work as part of that iterative design, but in practice it means a growing collection of broken tests and tests for parts of the program that end up being completely irrelevant.
If you have "a growing collection of broken tests", that's not TDD. That's "they told us we have to have tests, so we wrote some, but we don't actually want them enough to maintain them, so instead we ignore them".
Tests help massively with iterating a design on a partly-implemented code base. I start with the existing tests running. I iterate by changing some parts. Did that break anything else? How do I know? Well, I run the tests. Oh, those four tests broke. That one is no longer relevant; I delete it. That other one is testing behavior that changed; I fix it for the new reality. Those other two... why are they breaking? Those are showing me unintended consequences of my change. I think very carefully about what they're showing me, and decide if I want the code to do that. If yes, I fix the test; if not, I fix the code. At the end, I've got working tests again, and I've got a solid basis for believing that the code does what I think it does.
> The trouble with TDD is that quite often we don't really know how our programs are going to work
> The obvious exception to this, where I still use TDD, is when implementing a well defined spec.
From my understanding (and experience), TDD is quite the opposite. It's most useful when you don't have the spec, don't have clue how software will work in the end. TDD creates the spec, iteratively.
When I've been serious about testing I'll usually:
1. Hack in what I want in some exploratory way
2. Write good tests
3. Delete my hacks from step 1, and ensure all my new tests now fail
4. Re-implement what I hacked together in step 1
5. Ensure all tests pass
This allows you to explore while still retaining the benefits of TDD.
There's a name for it, it's called a "spike". You write a bunch of exploratory stuff, get the idea right, throw it all away (without even writing tests) and then come back doing TDD.
Also not sure why you are getting downvoted. We call it "breakthrough", as in piercing though all the layers to connect one simple usecase from front to end.
Once we established that that works properly, we think of a way to do it clean and tested for all other usecases.
(In the book "the pragmatic programmer" it's called "tracer bullets / code".)
Not sure why you got downvotes for this. It is a very effective technique.
Since typing speed was never the bottleneck in software development. Throwing away the little bit of code you wrote, it not expensive. And writing it back in with TDD is incredibly efficient.
For the software you're thinking about, do you have specific use cases or users in mind? Or are you building, say, an app for the first time, perhaps for a very early stage startup that is nowhere close to market fit yet?
We typically write acceptance tests, and they have been helpful either early on or later in our product development lifecycle.
Even if software isn't defined upfront, the end goal is likely defined upfront, isn't it? "User X should be able to get data about a car," or "User Y should be able to add a star ratings to this review," etc.
If you're building a product where you're regularly throwing out large parts of the UI / functionality, though, I suppose it could be bad. But as a small startup, we have almost never been in that situation over the many years we've been in business.
It's funny, because I feel like TDD -- not just unit-testing, but TDD -- is most helpful when things aren't well-defined. I think back to "what's the simplest test that could fail?" and it helps me focus on getting some small piece done. From there, it snowballs and the code emerges. Obviously it's not always perfect, and something learned along the way spurs refactoring/redesign. That always strikes me as a natural process.
In many ways I guess I lean maximalist in my practices, and find it helpful, but I'd readily concede that the maximalist advocates are annoying and off-putting. I once had the opportunity to program with Ward Cunningham for a weekend, and it was a completely easygoing and pragmatic experience.
And this is why you use spike solutions, to explore the problem space without the constraints of TDD.
But spikes are written to be thrown away. You never put them into production. Production code is always written against some preexisting test, otherwise it is by definition broken.
> it's impossible to write adequate test coverage up front
I'm not sure what you mean by this. Why are the tests you're writing not "adequate" for the code you're testing?
If I read into this that you're using code coverage as a metric -- and perhaps even striving for as close to 100% as possible -- I'd argue that's not useful. Code coverage, as a goal, is perhaps even harmful. You can have 100% code coverage and still miss important scenarios -- this means the software can still be wrong, despite the huge effort put into getting 100% coverage and having all tests both correct and passing.
I wish I could remember who wrote the essay with the idea of tests as investment in protecting functionality. When after a bit of experimentation or iteration you think you have figured out more or less one part of how your software should behave, then you want to protect that result. It is worth investing in writing and maintaining a test to make sure you don't accidentally break this functionality.
Functionality based on a set of initial specs and a hazy understanding of the actual problem you are trying to solve might on the other hand might not be worth investing in protecting.
It sounds a little like you are trying to write all the tests to the spec up front? With TDD you are still allowed to change design choices as you go and as you realise how you want it to behave. That’s why the tests are one by one. In my experience, TDD carries the most value when you really don’t know where you are going, you write the first test and you start rolling, and somehow you end up at your destination and people think you were good at writing code but actually the code was writing itself in a way as it evolved its was to completeness.
Since you don’t know how to solve it, you first write a test that goes vaguely in the direction.
If you can’t do that yet, you spike, mess around with it, get your bearings and some insight into where you want to go, try a few things out. Then, trash that and then write the first test as above.
It almost always works, and excels somewhat in legacy code vs just changing things.
It isn’t about ‘might work’. The TDD paradigm isn’t about finding shiny places where you can use. It is just a nice way of writing clean maintainable software in almost all areas.
Places where TDD won’t work are usually by exception rather than the norm.
Often those exceptions are where something already exists and wasn’t put in by TDD because by the definition of TDD you wouldn’t have been able to write that in the first place.
And that is, write code, chuck it away, start again.
Prototype your feature without TDD. Then chuck it away and build it again with TDD.
My guess is by doing so code quality and reduced technical debt pay more than what is lost in time.
Very few companies work like this I imagine: None that I have worked for.
Since keyboard typing is a short part of software development it is probably a great use of time and could catch more bugs and design quirks early on when they cost $200/h instead of $2000/h.
That's one issue with TDD. I agree 100% in that respect.
Another partly orthogonal issue is that design is important for some problems, and you don't usually reach a good design by chipping away at a problem in tiny pieces.
TDD fanatics insist that it works for everything. Do I believe them that it improved the quality of their code? Absolutely; I've seen tons of crap code that would have benefited from any improvement to the design, and forcing it to be testable is one way to coerce better design decisions.
But it really only forces the first-order design at the lowest level to be decent. It doesn't help at all, or at least not much, with the data architecture or the overall data flow through the application.
And sometimes the only sane way to achieve a solid result is to sit down and design a clean architecture for the problem you're trying to solve.
I'm thinking of one solution I came up with for a problem that really wasn't amenable to the "write one test and get a positive result" approach of TDD. I built up a full tree data structure that was linked horizontally to "past" trees in the same hierarchy (each node was linked to its historical equivalent node). This data structure was really, really needed to handle the complex data constraints the client was requesting. As yes, we pushed the client to try to simplify those constraints, but they insisted.
The absolute spaghetti mess that would have resulted from TDD wouldn't have been possible to refactor into what I came up with. There's just no evolutionary path between points A and B. And after it was implemented and it functioned correctly--they changed the constraints. About a hundred times. I'm not even exaggerating.
Each new constraint required about 15 minutes of tweaking to the structure I'd created. And yes, I piled on tests to ensure it was working correctly--but the tests were all after the fact, and they weren't micro-unit tests but more of a broad system test that covered far more functionality than you'd normally put in a unit test. Some of the tests even needed to be serialized so that earlier tests could set up complex data and states for the later tests to exercise, which I understand is also a huge No No in TDD, but short of creating 10x as much testing code, much of it being completely redundant, I didn't really have a choice.
So your point about the design changing as you go is important, but sometimes even the initial design is complex enough that you don't want to just sit down and start coding without thinking about how the whole design should work. And no methodology will magically grant good design sense; that's just something that needs to be learned. There Is No Silver Bullet, after all.
> Another partly orthogonal issue is that design is important for some problems, and you don't usually reach a good design by chipping away at a problem in tiny pieces.
True, but… you can still design the architecture, outlining the solution for the entire problem, and then apply TDD. In this case your architectural solution will be an input for low level design created in TDD.
I described a situation where TDD really, really, really wouldn't have worked. The whole structure needed to be developed, or at least 80% of it, before it would have made sense to write any tests--and the actual TDD philosophy would be to write "one small test" and only write exactly as much code as required to satisfy the test.
The sane approach was to create the entire structure based on the design, and then test it after it was complete as an entire system. Some of the micro-functionality that TDD would have had you test would have become technical debt as a change-detector later when the client changed their specific requirements.
As I said above, there is no evolutionary path from tiny pieces to the full structure, and TDD requires that you follow such an evolutionary path. If you're writing a bunch of tests and then creating a nontrivial amount of code, then you're following test-first, but not really following TDD. And I question even how valuable that is when you don't necessarily understand what would need to be tested before you've finished implementing the system.
I disagree with you here. TDD does require evolutionary path for the entire system, but the minimum unit is a feature that is expected to be fully specified and implemented to pass the first test. You cannot evolve a data structure or an algorithm with TDD, because TDD by original definition allows only refactoring, not re-engineering (I.e. if your feature is addition, writing „return 4“ to pass test2plus2 isn’t meaningful TDD). So in your case properly applied TDD would require fully implemented structure or at least an atomic part of it within the known design to pass the first test (e.g. testing Feistel round function in an encryption algorithm is ok, but you will know the design of the entire algorithm from the start).
I remember early uml courses (based on pre Java / OO languages). They were all about modules and coupling dependencies. Trying to keep them low, and the modules not too defined. It seems that the spirit behind this (at least the only one that make sense to me) is you don't know, so you just want to avoid coupling hard early, leave the room for low cost adaptation while you discover how things will be.
Whenever I start a greenfield frontend for someone they think I’m horrible in the first iteration. I tend to use style attributes and just shove CSS in there, and once I have enough things of a certain type I extract a class. They all love the result but distrust the first step.
At this point I doubt the existence of well defined specs.
Regulations are always ambiguous, standards are never followed, and widely implemented standards are never implemented the way the document tells.
You will probably still gain productivity by following TDD for those, but your process must not penalize too much changes in spec, because it doesn't matter if it's written in Law, what you read is not exactly what you will create.
This is precisely my experience also. I loved TDD when developing a parser for XLSX files to be used in a PowerShell pipeline.
I created dozens of “edge case” sample spreadsheets with horrible things in them like Bad Strings in every property and field. Think control characters in the tab names, RTL Unicode in the file description, etc…
TDD isn't concerned with how your program works. In fact, implementation details leaking into your tests can become quite problematic, including introducing the problems you speak of. TDD is concerned with describing what your program should accomplish. If you don't know what you want to accomplish, what are you writing code for?
The issue is what you want to accomplish is often tightly coupled with how it is accomplished. In order to have a test for what it needs to contain the context of how.
As a made up example. The "what" of the program is to take in a bunch of transactions and emit daily summaries. That's a straight forward "what". It however leaves tons of questions unanswered. Where does the data come from and in what format? Is it ASCII or Unicode? Do we control the source or is it from a third party? How do we want to emit the summaries? Printed to a text console? Saved to an Excel spreadsheet? What version of Excel? Serialized to XML or JSON? Do we have a spec for that serialized form? What precision do we need to calculate vs what we emit?
So the real "what" is: take in transaction data encoded as UTF-8 from a third party provider which lives in log files on the file system without inline metadata then translate the weird date format with only minute precision and lacking an explicit time zone and summarize daily stats to four decimal places but round to two decimal places for reporting and emit the summaries as JSON with dates as ISO ordinal dates and values at two decimal places saved to an FTP server we don't control.
While waiting for all that necessarily but often elided detail you can either start writing some code with unit test or wait and do no work until you get a fully fleshed out spec that can serve as the basis for writing tests. Most organizations want to start work even while the final specs of the work are being worked on.
> Most organizations want to start work even while the final specs of the work are being worked on.
Is that significant? Your tests can start to answer these unanswered questions before you ever get around to writing implementation. Suppose you thought you wanted to write data in ASCII format. But then you write some test cases and realize that you actually need Unicode symbols. Now you know what your implementation needs to do.
Testing is the spec. The exact purpose of testing, which in fairness doesn't have the greatest name, is to provide documentation around what the program does. That it is self-verifying is merely a nice side effect. There is no need for all the questions to be answered while writing the spec (a.k.a. tests). You learn about the answers as you write the documentation. The implementation then naturally follows.
> But then you write some test cases and realize that you actually need Unicode symbols. Now you know what your implementation needs to do.
If your customer decides they want/need ASCII your test is immaterial. The same is true for writing any tests before you've got a meaningful specification. You're just writing code to write code. At that stage it makes more sense to write a scaffold in the general shape of the task than a bunch of tests defining precise but made up requirements.
Aspirational tests are great if you know exactly what you need to do. They tell you when you get there. If you don't know exactly what you need to do they're just wasted effort that get thrown away with nothing having been gained.
> If your customer decides they want/need ASCII your test is immaterial.
Not at all. First, if your customer doesn't know upfront that ASCII is necessary, showing the customer how the program will work will help them realize that. The lesson gained from your test was useful in getting to get to that point.
Second, your failed attempt at an interface that provides UTF-8 (or whatever) during exploration is convertible to a negative case that will fail if ASCII isn't used, documenting the customer's requirement for future developers.
If the customer originally required UTF-8 and years later a changing landscape forced them to require ASCII instead, again your spec can be negated to help you ensure that you made the correct modifications to meet the new requirements.
> Aspirational tests are great if you know exactly what you need to do.
Whereas I would argue that TDD isn't all that useful if you know exactly what you need to do. In that case you can simple write the code along with unit/integration/acceptance tests that validate behaviour.
TDD is about exploring the unknowns and answering questions – showing the customer how the program will function on the outside – before you waste time implementing all the internal details of a full program around UTF-8 only to be told when you demo it that the customer actually requires ASCII, potentially requiring massive rework. The latter is where you waste effort.
> If you don't know what you want to accomplish, what are you writing code for?
Often times you write to find what you want to accomplish. It sounds backwards, perhaps it is backwards, but it's also very human. Without something to show the user, they often have no idea what they want. In fact, people are far better at telling you what's wrong with what's presented to them then enumerating everything they want ahead of time.
TDD is great but also completely useless for sussing requirements out of users.
It does not sound backwards at all. That is what TDD is for: To start writing the visible portions of your program to see how it works and adjust accordingly as user needs dictate. Once your program does what the user wants, all you have to do is backfill the "black box" implementation, using test cases created during the discovery phase to ensure that the "black box" provides what the user came to expect. The scenario you present is exactly what TDD was envisioned for.
If you know the exact requirements upfront, you don't really need TDD. You can simply write the code to those requirements and, perhaps, add in some automated acceptance testing to help catch mistakes. TDD shines when you are unsure and exploring options.
Isn't the issue because we are reluctant to remove stuff?
In the same vein as other said we should throw away one or two version of a program before shipping it.
Maybe we need to learn how to delete stuff that doesn't make sense.
Get rid of broken test. Get rid of incorrect documentation.
Don't be afraid to delete stuff to improve the overall program.
I still remember a project (I was the eng director and one of my team leads did this) where my team lead for a new dev project was given a group of near-shore SWEs + offshore SQA who were new to both the language & RDBMS of choice, and also didn't have any business domain experience. He decided that was exactly the time to implement TDD, and he took it upon himself to write 100% test coverage based on the approved specs, and literally just instructed the team to write code to pass the tests. They used daily stand-ups to answer questions, and weekly reviews to assess themes & progress. It was slow going, but it was a luxurious experience for the developers, many of whom were using pair programming at the time and now found themselves on a project where they had a committed & dedicated senior staffer to actively review their work and coach them through the project (and new tools learnings). I had never allowed a project to be run like that before, but it was one where we had a fairly flexible timeline as long as periodic deliverables were achieved, so I used it as a kind of science project to see how something that extreme would fare.
The result was that 1) the devs were exceptionally happy, 2) the TL was mostly happy, except with some of the extra forced work he created for himself as the bottleneck, 3) the project took longer than expected, and 4) the code was SOOOOO readable but also very inefficient. We realized during the project that forcing unit tests for literally everything was also forcing a breaking up of methods & functions into much smaller discrete pieces than would have been optimal from both performance & extensibility perspectives.
It wasn't the last TDD project we ran, but we were far more flexible after that.
I had one other "science project" while managing that team, too. It was one where we decided to create an architect role (it was the hotness at that time), and let them design everything from the beginning, after which the dev team would run with it using their typical agile/sprint methodology. We ended up with the most spaghetti code of abstraction upon abstraction, factories for all sorts of things, and a codebase that became almost unsupportable from the time it was launched, necessitating v2.0 be a near complete rewrite of the business logic and a lot of the data interfaces.
The lessons I learned from those projects was that it's important to have experienced folks on every dev team, and that creating a general standard that allows for flexibility in specific architectural/technical decisions will result in higher quality software, faster, than if one is too prescriptive (either in process or in architecture/design patterns). I also learned that there's no such thing as too much SQA, but that's for a different story.
Since I've moved to full time rust I'm finding it much harder to precede the code with tests (ignoring for a moment the maximalist/minimalist discussion). I think it's the because the abstractions can be so powerful that the development process is iterating over high level abstractions. The bit I worry about testing is the business logic, but that in my experience is not something you can test with a trivial unit test, and that test tends to iterate with the design to some extent. Essentially I end up with a series of behavioural tests and an implementation that as far as possible can't take inputs that can be mishandled (through e.g. the newtype pattern, static constraints etc).
I'm not quite sure what is right or wrong about my approach, but I do find the code tends to work and work reliably once it compiles and the tests pass.
I write tdd when doing advent of code. And it’s not that I set out to do it or to practice it or anything. It just comes very natural to small, well defined problems.
> This ultimately means, what most programmers intuitively know, that it's impossible to write adequate test coverage up front
Nobody out there is writing all their tests up front.
TDD is an iterative process, RED GREEN REFACTOR.
- You write one test.
- Write JUST enough code to make it pass.
- Refactor while maintaining green.
- Write a new test.
- Repeat.
I don't want this to come off the wrong way but what you're describing shows you are severely misinformed about what TDD actually is or you're just making assumptions about something based on its name and nothing else.
Writing N or 1 tests N times, depending on how many times I have to rewrite the "unit" for some soft idea of completeness. After the red/green 1 case, it necessarily has to expand to N cases as the unit is rewritten to handle the additional cases imagined (boundary, incorrect inputs, exceptions, etc). Now I see that I could have created optimizations in the method and rewrite it again and leverage the existing red/green.
Everyone understands the idea, it's just a massive time sink for no more benefit than a test-after methodology provides.
See my other comment below. I don't recommend doing it all the time specifically because with experience you can often skip a lot of the rgr loop.
> Everyone understands the idea, it's just a massive time sink for no more benefit than a test-after methodology provides.
This is not something I agree with. In my experience, when TDD is used you come up with solutions to problems that are better than what you'd come up with otherwise and it generally takes much less time overall.
Writing tests after ensures your code is testable. Writing your tests first ensures you only have to write your code once to get it under test.
Again, you don't always need TDD and applying it when you don't need it will likely be a net time sink with little benefit.
Those two steps aren't really trivial. Even just writing the single test might require making a lot of design decisions that you can't really make up-front without the code.
This acts as a forcing function for the software design. That TDD requires you to think about properly separating concerns via decomposition is a feature, not a bug. In my experience the architectural consequences are of greater value than the test coverage.
Sadly TDD is right up there with REST in being almost universally misunderstood.
Then you need to keep the test and signature in lock step. Your method signature is likely to change as the code evolves. I'm not arguing against tests but requiring them too early generates a lot of extra work.
The first test is never the problem. The problem as OP pointed out is after iterating a few times you realize you went down the wrong track or the requirements have changed / been clarified. Now a lot of the tests you iterated through aren't relevant anymore.
Is it possible that it was those tests and code in the TDD cycle that helped you realise you’d gone down the wrong path?
And if not, perhaps there was a preconceived idea of the code block and what it was going to do, rather than specifying the behaviour wanted via the RGR cycle. With a preconceived idea, with or without the tests, if that idea is wrong, you’ll hit the dead end and have to back track. Fortunately I find that even though I do sometimes find myself in this situation, quite often those tests can be repurposed fairly quickly rather than being chucked away, after all the tests are still software, and not hardware.
In my admittedly not-vast experience, a pattern going bad because the implementer doesn't understand it is actually only the implementer's fault a minority of the time, and is the fault of the pattern the majority of the time. This is because a pattern making sense to an implementer requires work from both sides, and which side is slacking can vary. Sometimes the people who get it and like it tend to purposefully overlook this pragmatic issue because "you're doing it wrong" seems like a golden bullet to critiques.
Reiterating the same argument in screaming case doesn't bolster your argument. It feels like the internet equivalent of a real life debate where a debater thinks saying the same thing LOUDER makes a better argument.
> - You write one test
Easier said than done. Say your task is to create a low level audio mixer which is something you've never done before. Where do you even begin? That's the hard part.
Some other commenters here have pointed out that exploratory code is different from TDD code, which is a much better argument then what you made here imo.
> I don't want this to come off the wrong way but what you're describing shows you are severely misinformed about what TDD actually is or you're just making assumptions about something based on its name and nothing else.
Instead of questioning the OP's qualifications, perhaps you should hold a slightly less dogmatic opinion. Perhaps OP is familiar with this style of development, and they've run into problem firsthand when they've tried to write tests for an unknown problem domain.
> Some other commenters here have pointed out that exploratory code is different from TDD code, which is a much better argument then what you made here imo.
I find that iterating on tests in exploratory code makes for an excellent driver to exercise the exploration. I don’t see the conflict between the two, except I am not writing test cases to show correctness, I am writing them to learn. To play with the inputs and outputs quickly.
I don't think GP was questioning their qualifications. Its exceedingly clear from OPs remarks they don't know what TDD is and haven't even read the article because it covers all this. In detail.
In my experience the write a new test bit is where it all falls down. It's too easy to skimp out on that when there are deadlines to hit or you are short staffed.
I've seen loads of examples where the tests haven't been updated in years to take account of new functionality. When that happens you aren't really doing TDD anymore.
TDD is not a testing process. It is a design process. The tests are a secondary and beneficial artifact of the well designed software that comes from writing a test first.
> TDD is not a testing process. It is a design process.
The article actually discusses whether this is accurate or not. TDD started out as a testing process but got adopted for its design consequences which is why there is a lot of confusion.
Naming it test driven design would have gone a long way to help things and also resulted in less cargo culting. "Have to TDD all day or you don't do TDD"
This ultimately means, what most programmers intuitively know, that it's impossible to write adequate test coverage up front (since we don't even really know how we want the program to behave) or worse, test coverage gets in the way of the iterative design process. In theory TDD should work as part of that iterative design, but in practice it means a growing collection of broken tests and tests for parts of the program that end up being completely irrelevant.
The obvious exception to this, where I still use TDD, is when implementing a well defined spec. Anytime you need to build a library to match an existing protocol, well documented api, or even an non-trivial mathematical function, TDD is a tremendous boon. But this is only because the program behavior is well defined.
The times where I've used TDD and it makes sense it's be a tremendous productivity increase. If you're implementing some standard you can basically write the tests to confirm you understand how the protocol/api/function works.
Unfortunately most software is just not well defined up front.