Software Testing Categorization
July 14th, 2009 | Published in Google Testing
by Miško Hevery
You hear people talking about small/medium/large/unit/integration/functional/scenario tests but do most of us really know what is meant by that? Here is how I think about tests.
Unit/Small
Lets start with unit test. The best definition I can find is that it is a test which runs super-fast (under 1 ms) and when it fails you don't need debugger to figure out what is wrong. Now this has some implications. Under 1 ms means that your test cannot do any I/O. The reason this is important is that you want to run ALL (thousands) of your unit-tests every time you modify anything, preferably on each save. My patience is two seconds max. In two seconds I want to make sure that all of my unit tests ran and nothing broke. This is a great world to be in, since if tests go red you just hit Ctrl-Z few times to undo what you have done and try again. The immediate feedback is addictive. Not needing a debugger implies that the test is localized (hence the word unit, as in single class).
The purpose of the unit-test is to check the conditional logic in your code, your 'ifs' and 'loops'. This is where the majority of your bugs come from (see theory of bugs). Which is why if you do no other testing, unit tests are the best bang for your buck! Unit tests, also make sure that you have testable code. If you have unit-testable code than all other testing levels will be testable as well.
A KeyedMultiStackTest.java is what I would consider great unit test example from Testability Explorer. Notice how each test tells a story. It is not testMethodA, testMethodB, etc, rather each test is a scenario. Notice how at the beginning the test are normal operations you would expect but as you get to the bottom of the file the test become little stranger. It is because those are weird corner cases which I have discovered later. Now the funny thing about KeyedMultiStack.java is that I had to rewrite this class three times. Since I could not get it to work under all of the test cases. One of the test was always failing, until I realized that my algorithm was fundamentally flawed. By this time I had most of the project working and this is a key class for byte-code analysis process. How would you feel about ripping out something so fundamental out of your system and rewriting it from scratch? It took me two days to rewrite it until all of my test passed again. After the rewrite the overall application still worked. This is where you have an AHa! moment, when you realize just how amazing unit-tests are.
Does each class need a unit test? A qualified no. Many classes get tested indirectly when testing something else. Usually simple value objects do not have tests of their own. But don't confuse not having tests and not having test coverage. All classes/methods should have test coverage. If you TDD, than this is automatic.
Medium/Functional
So you proved that each class works individually, but how do you know that they work together? For this we need to wire related classes together just as they would be in production and exercise some basic execution paths through it. The question here we are trying to answer is not if the 'ifs' and 'loops' work, (we have already answered that,) but whether the interfaces between classes abide by their contracts. Great example of functional test is MetricComputerTest.java. Notice how the input of each test is an inner class in the test file and the output is ClassCost.java. To get the output several classes have to collaborate together to: parse byte-codes, analyze code paths, and compute costs until the final cost numbers are asserted.
Many of the classes are tested twice. Once directly throughout unit-test as described above, and once indirectly through the functional-tests. If you would remove the unit tests I would still have high confidence that the functional tests would catch most changes which would break things, but I would have no idea where to go to look for a fix, since the mistake can be in any class involved in the execution path. The no debugger needed rule is broken here. When a functional test fails, (and there are no unit tests failing) I am forced to take out my debugger. When I find the problem, I add a unit test retroactively to my unit test to 1) prove to myself that I understand the bug and 2) prevent this bug from happening again. The retroactive unit test is the reason why the unit tests at the end of KeyedMultiStackTest.java file are "strange" for a lack of a better world. They are things which I did not think of when i wrote the unit-test, but discovered when I wrote functional tests, and through lot of hours behind debugger track down to KeyedMultiStack.java class as the culprit.
Now computing metrics is just a small part of what testability explorer does, (it also does reports, and suggestions) but those are not tested in this functional test (there are other functional tests for that). You can think of functional-tests as a set of related classes which form a cohesive functional unit for the overall application. Here are some of the functional areas in testability explorer: java byte-code parsing, java source parsing, c++ parsing, cost analysis, 3 different kinds of reports, and suggestion engine. All of these have unique set of related classes which work together and need to be tested together, but for the most part are independent.
Large/End-to-End/Scenario
We have proved that: 'ifs' and 'loops' work; and that the contracts are compatible, what else can we test? There is still one class of mistake we can make. You can wire the whole thing wrong. For example, passing in null instead of report, not configuring the location of the jar file for parsing, and so on. These are not logical bugs, but wiring bugs. Luckily, wiring bugs have this nice property that they fail consistently and usually spectacularly with an exception. Here is an example of end-to-end test: TestabilityRunnerTest.java. Notice how these tests exercises the whole application, and do not assert much. What is there to assert? We have already proven that everything works, we just want to make sure that it is wired properly.
You hear people talking about small/medium/large/unit/integration/functional/scenario tests but do most of us really know what is meant by that? Here is how I think about tests.
Unit/Small
Lets start with unit test. The best definition I can find is that it is a test which runs super-fast (under 1 ms) and when it fails you don't need debugger to figure out what is wrong. Now this has some implications. Under 1 ms means that your test cannot do any I/O. The reason this is important is that you want to run ALL (thousands) of your unit-tests every time you modify anything, preferably on each save. My patience is two seconds max. In two seconds I want to make sure that all of my unit tests ran and nothing broke. This is a great world to be in, since if tests go red you just hit Ctrl-Z few times to undo what you have done and try again. The immediate feedback is addictive. Not needing a debugger implies that the test is localized (hence the word unit, as in single class).
The purpose of the unit-test is to check the conditional logic in your code, your 'ifs' and 'loops'. This is where the majority of your bugs come from (see theory of bugs). Which is why if you do no other testing, unit tests are the best bang for your buck! Unit tests, also make sure that you have testable code. If you have unit-testable code than all other testing levels will be testable as well.
A KeyedMultiStackTest.java is what I would consider great unit test example from Testability Explorer. Notice how each test tells a story. It is not testMethodA, testMethodB, etc, rather each test is a scenario. Notice how at the beginning the test are normal operations you would expect but as you get to the bottom of the file the test become little stranger. It is because those are weird corner cases which I have discovered later. Now the funny thing about KeyedMultiStack.java is that I had to rewrite this class three times. Since I could not get it to work under all of the test cases. One of the test was always failing, until I realized that my algorithm was fundamentally flawed. By this time I had most of the project working and this is a key class for byte-code analysis process. How would you feel about ripping out something so fundamental out of your system and rewriting it from scratch? It took me two days to rewrite it until all of my test passed again. After the rewrite the overall application still worked. This is where you have an AHa! moment, when you realize just how amazing unit-tests are.
Does each class need a unit test? A qualified no. Many classes get tested indirectly when testing something else. Usually simple value objects do not have tests of their own. But don't confuse not having tests and not having test coverage. All classes/methods should have test coverage. If you TDD, than this is automatic.
Medium/Functional
So you proved that each class works individually, but how do you know that they work together? For this we need to wire related classes together just as they would be in production and exercise some basic execution paths through it. The question here we are trying to answer is not if the 'ifs' and 'loops' work, (we have already answered that,) but whether the interfaces between classes abide by their contracts. Great example of functional test is MetricComputerTest.java. Notice how the input of each test is an inner class in the test file and the output is ClassCost.java. To get the output several classes have to collaborate together to: parse byte-codes, analyze code paths, and compute costs until the final cost numbers are asserted.
Many of the classes are tested twice. Once directly throughout unit-test as described above, and once indirectly through the functional-tests. If you would remove the unit tests I would still have high confidence that the functional tests would catch most changes which would break things, but I would have no idea where to go to look for a fix, since the mistake can be in any class involved in the execution path. The no debugger needed rule is broken here. When a functional test fails, (and there are no unit tests failing) I am forced to take out my debugger. When I find the problem, I add a unit test retroactively to my unit test to 1) prove to myself that I understand the bug and 2) prevent this bug from happening again. The retroactive unit test is the reason why the unit tests at the end of KeyedMultiStackTest.java file are "strange" for a lack of a better world. They are things which I did not think of when i wrote the unit-test, but discovered when I wrote functional tests, and through lot of hours behind debugger track down to KeyedMultiStack.java class as the culprit.
Now computing metrics is just a small part of what testability explorer does, (it also does reports, and suggestions) but those are not tested in this functional test (there are other functional tests for that). You can think of functional-tests as a set of related classes which form a cohesive functional unit for the overall application. Here are some of the functional areas in testability explorer: java byte-code parsing, java source parsing, c++ parsing, cost analysis, 3 different kinds of reports, and suggestion engine. All of these have unique set of related classes which work together and need to be tested together, but for the most part are independent.
Large/End-to-End/Scenario
We have proved that: 'ifs' and 'loops' work; and that the contracts are compatible, what else can we test? There is still one class of mistake we can make. You can wire the whole thing wrong. For example, passing in null instead of report, not configuring the location of the jar file for parsing, and so on. These are not logical bugs, but wiring bugs. Luckily, wiring bugs have this nice property that they fail consistently and usually spectacularly with an exception. Here is an example of end-to-end test: TestabilityRunnerTest.java. Notice how these tests exercises the whole application, and do not assert much. What is there to assert? We have already proven that everything works, we just want to make sure that it is wired properly.