Static Methods
Static methods are procedural in nature and they have no place in OO world. I can already hear the screams, so let me explain why, but first we need to agree that global variables and state is evil. If you agree with previous statement than for a static method to do something interesting it needs to have some arguments, otherwise it will always return a constant. Call to a staticMethod() must always return the same thing, if there is no global state. (Time and random, has global state, so that does not count and object instantiation may have different instance but the object graph will be wired the same way.)
This means that for a static method to do something interesting it needs to have arguments. But in that case I will argue that the method simply belongs on one of its arguments. Example: Math.abs(-3) should really be -3.abs(). Now that does not imply that -3 needs to be object, only that the compiler needs to do the magic on my behalf, which BTW, Ruby got right. If you have multiple arguments you should choose the argument with which method interacts the most.
But most justifications for static methods argue that they are "utility methods". Let's say that you want to have toCamelCase() method to convert string "my_workspace" to "myWorkspace". Most developers will solve this as StringUtil.toCamelCase("my_workspace"). But, again, I am going to argue that the method simply belongs to the String class and should be "my_workspace".toCamelCase(). But we can't extend the String class in Java, so we are stuck, but in many other OO languages you can add methods to existing classes.
In the end I am sometimes (handful of times per year) forced to write static methods due to limitation of the language. But that is a rare event since static methods are death to testability. What I do find, is that in most projects static methods are rampant.
Instance Methods
So you got rid of all of your static methods but your codes still is procedural. OO says that code and data live together. So when one looks at code one can judge how OO it is without understanding what the code does, simply by looking at the relationship of data and code.
Static methods are procedural in nature and they have no place in OO world. I can already hear the screams, so let me explain why, but first we need to agree that global variables and state is evil. If you agree with previous statement than for a static method to do something interesting it needs to have some arguments, otherwise it will always return a constant. Call to a staticMethod() must always return the same thing, if there is no global state. (Time and random, has global state, so that does not count and object instantiation may have different instance but the object graph will be wired the same way.)
This means that for a static method to do something interesting it needs to have arguments. But in that case I will argue that the method simply belongs on one of its arguments. Example: Math.abs(-3) should really be -3.abs(). Now that does not imply that -3 needs to be object, only that the compiler needs to do the magic on my behalf, which BTW, Ruby got right. If you have multiple arguments you should choose the argument with which method interacts the most.
But most justifications for static methods argue that they are "utility methods". Let's say that you want to have toCamelCase() method to convert string "my_workspace" to "myWorkspace". Most developers will solve this as StringUtil.toCamelCase("my_workspace"). But, again, I am going to argue that the method simply belongs to the String class and should be "my_workspace".toCamelCase(). But we can't extend the String class in Java, so we are stuck, but in many other OO languages you can add methods to existing classes.
In the end I am sometimes (handful of times per year) forced to write static methods due to limitation of the language. But that is a rare event since static methods are death to testability. What I do find, is that in most projects static methods are rampant.
Instance Methods
So you got rid of all of your static methods but your codes still is procedural. OO says that code and data live together. So when one looks at code one can judge how OO it is without understanding what the code does, simply by looking at the relationship of data and code.
class Database {
// some fields declared here
boolean isDirty(Cache cache, Object obj) {
for (Object cachedObj : cache.getObjects) {
if (cachedObj.equals(obj))
return false;
}
return true;
}
}
The problem here is the method may as well be static! It is in the wrong place, and you can tell this because it does not interact with any of the data in the Database, instead it interacts with the data in cache which it fetches by calling the getObjects() method. My guess is that this method belongs to one of its arguments most likely Cache. If you move it to Cache you well notice that the Cache will no longer need the getObjects() method since the for loop can access the internal state of the Cache directly. Hey, we simplified the code (moved one method, deleted one method) and we have made Demeter happy.
The funny thing about the getter methods is that it usually means that the code where the data is processed is outside of the class which has the data. In other words the code and data are not together.
class Authenticator {
Ldap ldap;
Cookie login(User user) {
if (user.isSuperUser()) {
if ( ldap.auth(user.getUser(),
user.getPassword()) )
return new Cookie(user.getActingAsUser());
} else (user.isAgent) {
return new Cookie(user.getActingAsUser());
} else {
if ( ldap.auth(user.getUser(),
user.getPassword()) )
return new Cookie(user.getUser());
}
return null;
}
}
Now I don't know if this code is well written or not, but I do know that the login() method has a very high affinity to user. It interacts with the user a lot more than it interacts with its own state. Except it does not interact with user, it uses it as a dumb storage for data. Again, code lives with data is being violated. I believe that the method should be on the object with which it interacts the most, in this case on User. So lets have a look:
class User {
String user;
String password;
boolean isAgent;
boolean isSuperUser;
String actingAsUser;
Cookie login(Ldap ldap) {
if (isSuperUser) {
if ( ldap.auth(user, password) )
return new Cookie(actingAsUser);
} else (user.isAgent) {
return new Cookie(actingAsUser);
} else {
if ( ldap.auth(user, password) )
return new Cookie(user);
}
return null;
}
}
Ok we are making progress, notice how the need for all of the getters has disappeared, (and in this simplified example the need for the Authenticator class disappears) but there is still something wrong. The ifs branch on internal state of the object. My guess is that this code-base is riddled with if (user.isSuperUser()). The issue is that if you add a new flag you have to remember to change all of the ifs which are dispersed all over the code-base. Whenever I see If or switch on a flag I can almost always know that polymorphism is in order.
class User {
String user;
String password;
Cookie login(Ldap ldap) {
if ( ldap.auth(user, password) )
return new Cookie(user);
return null;
}
}
class SuperUser extends User {
String actingAsUser;
Cookie login(Ldap ldap) {
if ( ldap.auth(user, password) )
return new Cookie(actingAsUser);
return null;
}
}
class AgentUser extends User {
String actingAsUser;
Cookie login(Ldap ldap) {
return new Cookie(actingAsUser);
}
}
Now that we took advantage of polymorphism, each different kind of user knows how to log in and we can easily add new kind of user type to the system. Also notice how the user no longer has all of the flag fields which were controlling the ifs to give the user different behavior. The ifs and flags have disappeared.
Now this begs the question: should the User know about the Ldap? There are actually two questions in there. 1) should User have a field reference to Ldap? and 2) should User have compile time dependency on Ldap?
Should User have a field reference to Ldap? The answer is no, because you may want to serialize the user to database but you don't want to serialize the Ldap. See here.
Should User have compile time dependency on Ldap? This is more complicated, but in general the answer depends on weather or not you are planning on reusing the User on a different project, since compile time dependencies are transitive in strongly typed languages. My experience is that everyone always writes code that one day they will reuse it, but that day never comes, and when it does, usually the code is entangled in other ways anyway, so code reuse after the fact just does not happen. (developing a library is different since code reuse is an explicit goal.) My point is that a lot of people pay the price of "what if" but never get any benefit out of it. Therefore don't worry abut it and make the User depend on Ldap. Permalink | Links to this post |
The Advantages of Unit Testing Early
Wednesday, July 15, 2009 8:33 PM
by Shyam Seshadri
Nowadays, when I talk with (read: rant at) anyone about why they should do test driven development or write unit tests, my spiel has gotten extremely similar and redundant to the point that I don't have to think about it anymore. But even when I do pairing with skeptics, even as I cajole and coax testable code or some specific refactorings out of them, I wonder, why is it that I have to convince you of the worth of testing ? Shouldn't it be obvious ?
And sadly, it isn't. Not to many people. To many people, I come advocating the rise of the devil itself. To others, it is this redundant, totally useless thing that is covered by the manual testers anyway. The general opinion seems to be, "I'm a software engineer. It is my job to write software. Nowhere in the job description does it say that I have to write these unit tests." Well, to be fair, I haven't heard that too many times, but they might as well be thinking it, given their investment in writing unit tests. And last time I checked, an engineer's role is to deliver a working software. How do you even prove that your software works without having some unit tests to back you up ? Do you pull it up and go through it step by step, and start cursing when it breaks ? Because without unit tests, the odds are that it will.
But writing unit tests as you develop isn't just to prove that your code works (though that is a great portion of it). There are so many more benefits to writing unit tests. Lets talk in depth about a few of these below.
Instantaneous Gratification
The biggest and most obvious reason for writing unit tests (either as you go along, or before you even write code) is instantaneous gratification. When I write code (write, not spike. That is a whole different ball game that I won't get into now), I love to know that it works and does what it should do. If you are writing a smaller component of a bigger app (especially one that isn't complete yet), how are you even supposed to know if what you just painstakingly wrote even works or not ? Even the best engineers make mistakes.
Whereas with unit tests, I can write my code. Then just hit my shortcut keys to run my tests, and voila, within a second or two, I have the results, telling me that everything passed (in the ideal case) or what failed and at which line, so I know exactly what I need to work on. It just gives you a safety net to fall back on, so you don't have to remember all the ways it is supposed to work in. Something tells you if it is or not.
Also, doing Test Driven Development when developing is one of the best ways to keep track of what you are working on. I have times when I am churning out code and tests, one after the other, before I need to take a break. The concept of TDD is that I write a failing test, and then I write just enough code to pass that test. So when I take a break, I make it a point to leave at a failing test, so that when I come back, I can jump right back into writing the code to get it to pass. I don't have to spend 15 - 20 minutes reading through the code to figure out where I left off. My asserts usually tell me exactly what I need to do.
Imposing Modularity / Reusability
The very first rule of reusable code is that you have to be able to instantiate an instance of the class before you can use it. And guess what ? With unit tests, you almost always have to instantiate an instance of the class under test. Therefore, writing a unit test is always a first great step in making code reusable. And the minute you start writing unit tests, most likely, you will start running into the common pain points of not having injectable dependencies (Unless of course, you are one of the converts, in which case, good for you!).
Which brings me to the next point. Once you start having to jump through fiery hoops to set up your class just right to test it, you will start to realize when a class is getting bloated, or when a certain component belongs in its own class. For instance, why test the House when what you really want to test is the Kitchen it contains. So if the Kitchen class was initially part of the House, when you start writing unit tests, it becomes obvious enough that it belongs separately. Before long, you have modular classes which are small and self contained and can be tested independently without effort. And it definitely helps keep the code base cleaner and more comprehensible.
Refactoring Safety Net
Any project, no matter what you do, usually ends up at a juncture where the requirements change on you. And you are left with the option of refactoring your codebase to add / change it, or rewrite from scratch. One, never rewrite from scratch, always refactor. Its always faster when you refactor, no matter what you may think. Two, what do you do when you have to refactor and you don't have unit tests ? How do you know you haven't horribly broken something in that refactor ? Granted, IDE's such as Eclipse and IntelliJ have made refactoring much more convenient, but adding new functionality or editing existing features is never simple.
More often than not, we end up changing some undocumented way the existing code behaved, and blow up 10 different things (it takes skill to blow up more, believe me, I have tried). And its often something as simple as changing the way a variable is set or unset. In those cases, having unittests (remember those things you were supposed to have written?) to confirm that your refactoring broke nothing is godsend. I can't tell you the amount of times I have had to refactor a legacy code base without this safety net. The only way to ensure I did it correct was to write these large integration tests (because again, no unit tests usually tends to increase the coupling and reduce modularity, even in the most well designed code bases) which verified things at a higher level and pray fervently that I broke nothing. Then I would spend a few minutes bringing up the app everytime, and clicking on random things to make sure nothing blew up. A complete waste of my time when I could have known the same thing by just running my unit tests.
Documentation
Finally, one of my favorite advantages to doing TDD or writing unit tests as I code. I have a short memory for code I have written. I could look back at the code I wrote two days ago, and have no clue what I was thinking. In those cases, all I have to do is go look at the test for a particular method, and that almost always will tell me what that method takes in as parameters, and what all it should be doing. A well constructed set of tests tell you about valid and invalid inputs, state that it should modify and output that it may return.
Now this is useful for people like me with short memory spans. But it is also useful, say, when you have a new person joining the team. We had this cushion the last time someone joined our team for a short period of time, and when we asked him to add a particular check to a method, we just pointed him to the tests for that method, which basically told him what the method does. He was able to understand the requirements, and go ahead and add the check with minimal handholding. And the tests give a safety net so he doesn't break anything else while he was at it.
Also useful is the fact that later, when someone comes marching through your door, demanding you fix this bug, you can always make sure whether it was a a bug (in which case, you are obviously missing a test case) or if it was a feature that they have now changed the requirements on (in which case you already have a test which proves it was your intent to do it, and thus not a bug).
Permalink | Links to this post |
Nowadays, when I talk with (read: rant at) anyone about why they should do test driven development or write unit tests, my spiel has gotten extremely similar and redundant to the point that I don't have to think about it anymore. But even when I do pairing with skeptics, even as I cajole and coax testable code or some specific refactorings out of them, I wonder, why is it that I have to convince you of the worth of testing ? Shouldn't it be obvious ?
And sadly, it isn't. Not to many people. To many people, I come advocating the rise of the devil itself. To others, it is this redundant, totally useless thing that is covered by the manual testers anyway. The general opinion seems to be, "I'm a software engineer. It is my job to write software. Nowhere in the job description does it say that I have to write these unit tests." Well, to be fair, I haven't heard that too many times, but they might as well be thinking it, given their investment in writing unit tests. And last time I checked, an engineer's role is to deliver a working software. How do you even prove that your software works without having some unit tests to back you up ? Do you pull it up and go through it step by step, and start cursing when it breaks ? Because without unit tests, the odds are that it will.
But writing unit tests as you develop isn't just to prove that your code works (though that is a great portion of it). There are so many more benefits to writing unit tests. Lets talk in depth about a few of these below.
Instantaneous Gratification
The biggest and most obvious reason for writing unit tests (either as you go along, or before you even write code) is instantaneous gratification. When I write code (write, not spike. That is a whole different ball game that I won't get into now), I love to know that it works and does what it should do. If you are writing a smaller component of a bigger app (especially one that isn't complete yet), how are you even supposed to know if what you just painstakingly wrote even works or not ? Even the best engineers make mistakes.
Whereas with unit tests, I can write my code. Then just hit my shortcut keys to run my tests, and voila, within a second or two, I have the results, telling me that everything passed (in the ideal case) or what failed and at which line, so I know exactly what I need to work on. It just gives you a safety net to fall back on, so you don't have to remember all the ways it is supposed to work in. Something tells you if it is or not.
Also, doing Test Driven Development when developing is one of the best ways to keep track of what you are working on. I have times when I am churning out code and tests, one after the other, before I need to take a break. The concept of TDD is that I write a failing test, and then I write just enough code to pass that test. So when I take a break, I make it a point to leave at a failing test, so that when I come back, I can jump right back into writing the code to get it to pass. I don't have to spend 15 - 20 minutes reading through the code to figure out where I left off. My asserts usually tell me exactly what I need to do.
Imposing Modularity / Reusability
The very first rule of reusable code is that you have to be able to instantiate an instance of the class before you can use it. And guess what ? With unit tests, you almost always have to instantiate an instance of the class under test. Therefore, writing a unit test is always a first great step in making code reusable. And the minute you start writing unit tests, most likely, you will start running into the common pain points of not having injectable dependencies (Unless of course, you are one of the converts, in which case, good for you!).
Which brings me to the next point. Once you start having to jump through fiery hoops to set up your class just right to test it, you will start to realize when a class is getting bloated, or when a certain component belongs in its own class. For instance, why test the House when what you really want to test is the Kitchen it contains. So if the Kitchen class was initially part of the House, when you start writing unit tests, it becomes obvious enough that it belongs separately. Before long, you have modular classes which are small and self contained and can be tested independently without effort. And it definitely helps keep the code base cleaner and more comprehensible.
Refactoring Safety Net
Any project, no matter what you do, usually ends up at a juncture where the requirements change on you. And you are left with the option of refactoring your codebase to add / change it, or rewrite from scratch. One, never rewrite from scratch, always refactor. Its always faster when you refactor, no matter what you may think. Two, what do you do when you have to refactor and you don't have unit tests ? How do you know you haven't horribly broken something in that refactor ? Granted, IDE's such as Eclipse and IntelliJ have made refactoring much more convenient, but adding new functionality or editing existing features is never simple.
More often than not, we end up changing some undocumented way the existing code behaved, and blow up 10 different things (it takes skill to blow up more, believe me, I have tried). And its often something as simple as changing the way a variable is set or unset. In those cases, having unittests (remember those things you were supposed to have written?) to confirm that your refactoring broke nothing is godsend. I can't tell you the amount of times I have had to refactor a legacy code base without this safety net. The only way to ensure I did it correct was to write these large integration tests (because again, no unit tests usually tends to increase the coupling and reduce modularity, even in the most well designed code bases) which verified things at a higher level and pray fervently that I broke nothing. Then I would spend a few minutes bringing up the app everytime, and clicking on random things to make sure nothing blew up. A complete waste of my time when I could have known the same thing by just running my unit tests.
Documentation
Finally, one of my favorite advantages to doing TDD or writing unit tests as I code. I have a short memory for code I have written. I could look back at the code I wrote two days ago, and have no clue what I was thinking. In those cases, all I have to do is go look at the test for a particular method, and that almost always will tell me what that method takes in as parameters, and what all it should be doing. A well constructed set of tests tell you about valid and invalid inputs, state that it should modify and output that it may return.
Now this is useful for people like me with short memory spans. But it is also useful, say, when you have a new person joining the team. We had this cushion the last time someone joined our team for a short period of time, and when we asked him to add a particular check to a method, we just pointed him to the tests for that method, which basically told him what the method does. He was able to understand the requirements, and go ahead and add the check with minimal handholding. And the tests give a safety net so he doesn't break anything else while he was at it.
Also useful is the fact that later, when someone comes marching through your door, demanding you fix this bug, you can always make sure whether it was a a bug (in which case, you are obviously missing a test case) or if it was a feature that they have now changed the requirements on (in which case you already have a test which proves it was your intent to do it, and thus not a bug).
Permalink | Links to this post |
Software Testing Categorization
Tuesday, July 14, 2009 12:29 PM
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.
Permalink | Links to this post |
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.
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Why are we embarrassed to admit that we don't know how to write tests?
Wednesday, July 08, 2009 9:49 AM
Take
your average developer and ask "do you know language/technology X?"
None of us will feel any shame in admitting that we do not know X. After
all there are so many languages, frameworks and technologies, how could
you know them all? But what if X is writing testable code? Somehow we
have trouble answering the question "do you know how to write tests?"
Everyone says yes, whether or not we actually know it. It is as if there
is some shame in admitting that you don't know how to write tests.
Now I am not suggesting that people knowingly lie here, it is just that they think there is nothing to it. We think: I know how to write code, I think my code is pretty good, therefore my code is testable!
I personally think that we would do a lot better if we would recognize testability as a skill in its own right. And as such skills are not innate and take years of practice to develop. We could than treat it as any other skill and freely admit that we don't know it. We could than do something about it. We could offer classes, or other materials to grow our developers, but instead we treat it like breathing. We think that any developer can write testable code.
It took me two years of writing tests first, where I had as much tests as production code, before I started to understand what is the difference between testable and hard to test code. Ask yourself, how long have you been writing tests? What percentage of the code you write is tests?
Here is a question which you can ask to prove my point: "How do you write hard to test code?" I like to ask this question in interviews and most of the time I get silence. Sometimes I get people to say, make things private. Well if visibility is your only problem, I have a RegExp for you which will solve all of your problems. The truth is a lot more complicated, the code is hard to test doe to its structure, not doe to its naming conventions or visibility. Do you know the answer?
We all start at the same place. When I first heard about testing I immediately thought about writing a framework which will pretend to be a user so that I can put the app through its paces. It is only natural to thing this way. This kind of tests are called end-to-end-tests (or scenario or large tests), and they should be the last kind of tests which you write not the first thing you think of. End-to-end-tests are great for locating wiring bugs but are pretty bad at locating logical bugs. And most of your mistakes are in logical bugs, those are the hard ones to find. I find it a bit amusing that to fight buggy code we write even more complex framework which will pretends to be the user, so now we have even more code to test.
Everyone is in search of some magic test framework, technology, the know-how, which will solve the testing woes. Well I have news for you: there is no such thing. The secret in tests is in writing testable code, not in knowing some magic on testing side. And it certainly is not in some company which will sell you some test automation framework. Let me make this super clear: The secret in testing is in writing testable-code! You need to go after your developers not your test-organization.
Now lets think about this. Most organizations have developers which write code and than a test organization to test it. So let me make sure I understand. There is a group of people which write untestable code and a group which desperately tries to put tests around the untestable code. (Oh and test-group is not allowed to change the production code.) The developers are where the mistakes are made, and testers are the ones who feel the pain. Do you think that the developers have any incentive to change their behavior if they don't feel the pain of their mistakes? Can the test-organization be effective if they can't change the production code?
It is so easy to hide behind a "framework" which needs to be built/bought and things will be better. But the root cause is the untestable code, and until we learn to admit that we don't know how to write testable code, nothing is going to change...
Now I am not suggesting that people knowingly lie here, it is just that they think there is nothing to it. We think: I know how to write code, I think my code is pretty good, therefore my code is testable!
I personally think that we would do a lot better if we would recognize testability as a skill in its own right. And as such skills are not innate and take years of practice to develop. We could than treat it as any other skill and freely admit that we don't know it. We could than do something about it. We could offer classes, or other materials to grow our developers, but instead we treat it like breathing. We think that any developer can write testable code.
It took me two years of writing tests first, where I had as much tests as production code, before I started to understand what is the difference between testable and hard to test code. Ask yourself, how long have you been writing tests? What percentage of the code you write is tests?
Here is a question which you can ask to prove my point: "How do you write hard to test code?" I like to ask this question in interviews and most of the time I get silence. Sometimes I get people to say, make things private. Well if visibility is your only problem, I have a RegExp for you which will solve all of your problems. The truth is a lot more complicated, the code is hard to test doe to its structure, not doe to its naming conventions or visibility. Do you know the answer?
We all start at the same place. When I first heard about testing I immediately thought about writing a framework which will pretend to be a user so that I can put the app through its paces. It is only natural to thing this way. This kind of tests are called end-to-end-tests (or scenario or large tests), and they should be the last kind of tests which you write not the first thing you think of. End-to-end-tests are great for locating wiring bugs but are pretty bad at locating logical bugs. And most of your mistakes are in logical bugs, those are the hard ones to find. I find it a bit amusing that to fight buggy code we write even more complex framework which will pretends to be the user, so now we have even more code to test.
Everyone is in search of some magic test framework, technology, the know-how, which will solve the testing woes. Well I have news for you: there is no such thing. The secret in tests is in writing testable code, not in knowing some magic on testing side. And it certainly is not in some company which will sell you some test automation framework. Let me make this super clear: The secret in testing is in writing testable-code! You need to go after your developers not your test-organization.
Now lets think about this. Most organizations have developers which write code and than a test organization to test it. So let me make sure I understand. There is a group of people which write untestable code and a group which desperately tries to put tests around the untestable code. (Oh and test-group is not allowed to change the production code.) The developers are where the mistakes are made, and testers are the ones who feel the pain. Do you think that the developers have any incentive to change their behavior if they don't feel the pain of their mistakes? Can the test-organization be effective if they can't change the production code?
It is so easy to hide behind a "framework" which needs to be built/bought and things will be better. But the root cause is the untestable code, and until we learn to admit that we don't know how to write testable code, nothing is going to change...
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