What is a reasonable code coverage % for unit tests (and why)? [closed]

If you were to mandate a minimum percentage code-coverage for unit tests, perhaps even as a requirement for committing to a repository, what would it be?

Please explain how you arrived at your answer (since if all you did was pick a number, then I could have done that all by myself ;)

This prose by Alberto Savoia answers precisely that question (in a nicely entertaining manner at that!):

http://www.artima.com/forums/flat.jsp?forum=106&thread=204677

Testivus On Test Coverage

Early one morning, a programmer asked the great master:

“I am ready to write some unit tests. What code coverage should I aim for?”

The great master replied:

“Don’t worry about coverage, just write some good tests.”

The programmer smiled, bowed, and left.

...

Later that day, a second programmer asked the same question.

The great master pointed at a pot of boiling water and said:

“How many grains of rice should I put in that pot?”

The programmer, looking puzzled, replied:

“How can I possibly tell you? It depends on how many people you need to feed, how hungry they are, what other food you are serving, how much rice you have available, and so on.”

“Exactly,” said the great master.

The second programmer smiled, bowed, and left.

...

Toward the end of the day, a third programmer came and asked the same question about code coverage.

“Eighty percent and no less!” Replied the master in a stern voice, pounding his fist on the table.

The third programmer smiled, bowed, and left.

...

After this last reply, a young apprentice approached the great master:

“Great master, today I overheard you answer the same question about code coverage with three different answers. Why?”

The great master stood up from his chair:

“Come get some fresh tea with me and let’s talk about it.”

After they filled their cups with smoking hot green tea, the great master began to answer:

“The first programmer is new and just getting started with testing. Right now he has a lot of code and no tests. He has a long way to go; focusing on code coverage at this time would be depressing and quite useless. He’s better off just getting used to writing and running some tests. He can worry about coverage later.”

“The second programmer, on the other hand, is quite experience both at programming and testing. When I replied by asking her how many grains of rice I should put in a pot, I helped her realize that the amount of testing necessary depends on a number of factors, and she knows those factors better than I do – it’s her code after all. There is no single, simple, answer, and she’s smart enough to handle the truth and work with that.”

“I see,” said the young apprentice, “but if there is no single simple answer, then why did you answer the third programmer ‘Eighty percent and no less’?”

The great master laughed so hard and loud that his belly, evidence that he drank more than just green tea, flopped up and down.

“The third programmer wants only simple answers – even when there are no simple answers … and then does not follow them anyway.”

The young apprentice and the grizzled great master finished drinking their tea in contemplative silence.

Code Coverage is a misleading metric if 100% coverage is your goal (instead of 100% testing of all features).

You could get a 100% by hitting all the lines once. However you could still miss out testing a particular sequence (logical path) in which those lines are hit.
You could not get a 100% but still have tested all your 80%/freq used code-paths. Having tests that test every 'throw ExceptionTypeX' or similar defensive programming guard you've put in is a 'nice to have' not a 'must have'

So trust yourself or your developers to be thorough and cover every path through their code. Be pragmatic and don't chase the magical 100% coverage. If you TDD your code you should get a 90%+ coverage as a bonus. Use code-coverage to highlight chunks of code you have missed (shouldn't happen if you TDD though.. since you write code only to make a test pass. No code can exist without its partner test. )

Jon Limjap makes a good point - there is not a single number that is going to make sense as a standard for every project. There are projects that just don't need such a standard. Where the accepted answer falls short, in my opinion, is in describing how one might make that decision for a given project.

I will take a shot at doing so. I am not an expert in test engineering and would be happy to see a more informed answer.

When to set code coverage requirements

First, why would you want to impose such a standard in the first place? In general, when you want to introduce empirical confidence in your process. What do I mean by "empirical confidence"? Well, the real goal correctness. For most software, we can't possibly know this across all inputs, so we settle for saying that code is well-tested. This is more knowable, but is still a subjective standard: It will always be open to debate whether or not you have met it. Those debates are useful and should occur, but they also expose uncertainty.

Code coverage is an objective measurement: Once you see your coverage report, there is no ambiguity about whether standards have been met are useful. Does it prove correctness? Not at all, but it has a clear relationship to how well-tested the code is, which in turn is our best way to increase confidence in its correctness. Code coverage is a measurable approximation of immeasurable qualities we care about.

Some specific cases where having an empirical standard could add value:

To satisfy stakeholders. For many projects, there are various actors who have an interest in software quality who may not be involved in the day-to-day development of the software (managers, technical leads, etc.) Saying "we're going to write all the tests we really need" is not convincing: They either need to trust entirely, or verify with ongoing close oversight (assuming they even have the technical understanding to do so.) Providing measurable standards and explaining how they reasonably approximate actual goals is better.
To normalize team behavior. Stakeholders aside, if you are working on a team where multiple people are writing code and tests, there is room for ambiguity for what qualifies as "well-tested." Do all of your colleagues have the same idea of what level of testing is good enough? Probably not. How do you reconcile this? Find a metric you can all agree on and accept it as a reasonable approximation. This is especially (but not exclusively) useful in large teams, where leads may not have direct oversight over junior developers, for instance. Networks of trust matter as well, but without objective measurements, it is easy for group behavior to become inconsistent, even if everyone is acting in good faith.
To keep yourself honest. Even if you're the only developer and only stakeholder for your project, you might have certain qualities in mind for the software. Instead of making ongoing subjective assessments about how well-tested the software is (which takes work), you can use code coverage as a reasonable approximation, and let machines measure it for you.

Which metrics to use

Code coverage is not a single metric; there are several different ways of measuring coverage. Which one you might set a standard upon depends on what you're using that standard to satisfy.

I'll use two common metrics as examples of when you might use them to set standards:

Statement coverage: What percentage of statements have been executed during testing? Useful to get a sense of the physical coverage of your code: How much of the code that I have written have I actually tested?
- This kind of coverage supports a weaker correctness argument, but is also easier to achieve. If you're just using code coverage to ensure that things get tested (and not as an indicator of test quality beyond that) then statement coverage is probably sufficient.
Branch coverage: When there is branching logic (e.g. an if), have both branches been evaluated? This gives a better sense of the logical coverage of your code: How many of the possible paths my code may take have I tested?
- This kind of coverage is a much better indicator that a program has been tested across a comprehensive set of inputs. If you're using code coverage as your best empirical approximation for confidence in correctness, you should set standards based on branch coverage or similar.

There are many other metrics (line coverage is similar to statement coverage, but yields different numeric results for multi-line statements, for instance; conditional coverage and path coverage is similar to branch coverage, but reflect a more detailed view of the possible permutations of program execution you might encounter.)

What percentage to require

Finally, back to the original question: If you set code coverage standards, what should that number be?

Hopefully it's clear at this point that we're talking about an approximation to begin with, so any number we pick is going to be inherently approximate.

Some numbers that one might choose:

100%. You might choose this because you want to be sure everything is tested. This doesn't give you any insight into test quality, but does tell you that some test of some quality has touched every statement (or branch, etc.) Again, this comes back to degree of confidence: If your coverage is below 100%, you know some subset of your code is untested.
- Some might argue that this is silly, and you should only test the parts of your code that are really important. I would argue that you should also only maintain the parts of your code that are really important. Code coverage can be improved by removing untested code, too.
99% (or 95%, other numbers in the high nineties.) Appropriate in cases where you want to convey a level of confidence similar to 100%, but leave yourself some margin to not worry about the occasional hard-to-test corner of code.
80%. I've seen this number in use a few times, and don't entirely know where it originates. I think it might be a weird misappropriation of the 80-20 rule; generally, the intent here is to show that most of your code is tested. (Yes, 51% would also be "most", but 80% is more reflective of what most people mean by most.) This is appropriate for middle-ground cases where "well-tested" is not a high priority (you don't want to waste effort on low-value tests), but is enough of a priority that you'd still like to have some standard in place.

I haven't seen numbers below 80% in practice, and have a hard time imagining a case where one would set them. The role of these standards is to increase confidence in correctness, and numbers below 80% aren't particularly confidence-inspiring. (Yes, this is subjective, but again, the idea is to make the subjective choice once when you set the standard, and then use an objective measurement going forward.)

Other notes

The above assumes that correctness is the goal. Code coverage is just information; it may be relevant to other goals. For instance, if you're concerned about maintainability, you probably care about loose coupling, which can be demonstrated by testability, which in turn can be measured (in certain fashions) by code coverage. So your code coverage standard provides an empirical basis for approximating the quality of "maintainability" as well.

Code coverage is great, but functionality coverage is even better. I don't believe in covering every single line I write. But I do believe in writing 100% test coverage of all the functionality I want to provide (even for the extra cool features I came with myself and which were not discussed during the meetings).

I don't care if I would have code which is not covered in tests, but I would care if I would refactor my code and end up having a different behaviour. Therefore, 100% functionality coverage is my only target.

My favorite code coverage is 100% with an asterisk. The asterisk comes because I prefer to use tools that allow me to mark certain lines as lines that "don't count". If I have covered 100% of the lines which "count", I am done.

The underlying process is:

I write my tests to exercise all the functionality and edge cases I can think of (usually working from the documentation).
I run the code coverage tools
I examine any lines or paths not covered and any that I consider not important or unreachable (due to defensive programming) I mark as not counting
I write new tests to cover the missing lines and improve the documentation if those edge cases are not mentioned.

This way if I and my collaborators add new code or change the tests in the future, there is a bright line to tell us if we missed something important - the coverage dropped below 100%. However, it also provides the flexibility to deal with different testing priorities.