I have finally moved to my own domain.

Find my latest blog post about the ROI of unit testing at


July 15, 2009 at 2:19 pm Leave a comment

Separation anxiety ?

We all have separation anxiety. Its a human tendency. We love inertia, and we don’t like change. But why should your code have separation anxiety ? Its not human (even though it might try and grow a brain of its own at times)!

I bring this up because I got the chance to work with someone who had some questions on how to test UI code. Fairly innocuous question, and in most cases, my response would have been, keep the UI code simple and free of any logic, and don’t worry too much about it. Or you could write some nice end to end / integration tests / browser based tests. So with that response set in mind, I set off into the unknown. Little was I to know was that was the least of my concerns. As I sat down to look at the code, I saw that there were already tests for the code. I was optimistic now, I mean, how bad could things be if there are already tests for it ?

Well, I should remember next time to actually look at the tests first. But anyways, there were tests, so I was curious what kinds of tests they wanted to write and what kind of help I could provide, if any. So it turns out, the class was some sort of GUI Component, which basically had some fields, and depending on whether they were set of not, displayed them as widgets inside of it. So there were, say, 5 fields, and differing combinations of what was set would produce different output. The nice thing was that the rendered data was returned as a nice Java object, so you could easily assert on what was set, and get a handle on the widgets inside of it, etc. So the method was something along the following lines :

public RenderedWidgetGroup render() {
    RenderedWidgetGroup group =
    if ( = null) {
        return group;
    group.addWidget(new TextWidget(;
        new DateWidget(
            this.updatedTimestamp == null ?
                 this.createdTimestamp : this.updatedTimestamp));
    return group;

So far, so good, right ? Nice, clean, should be easy to test if we can set up this component with the right fields. After that, it should just be a few tests based on the different code paths defined by the conditionals. Yeah, thats what I thought too. So, me, being the naive guy that I was, said, yeah, that  looks nice, should be easy to test. I don’t see the problem.

Well, then I was taken to the tests. The first thing I see is a huge test. Or atleast thats what I think it is. Then I read it more closely, and see its a private method. It seems to take in a bunch of fields (Fields with names that I distinctly remembered from just a while ago) and churn out a POJO (Plain Old Java Object). Except this POJO was not the GUI Component object I expected. So obviously, I was curious (and my testing sensors were starting to tingle).  So I followed through to where it was called (which wasn’t very hard, it was a private method) and lo and behold, my worst fears confirmed.

The POJO object generated by the private method was passed in to the constructor of the GUI component, which (on following it further down the rabbit hole) in its constructor did something like the following :

public MyGUIComponent(ComponentId id,
                      Component parent,
                      MyDataContainingPOJO pojo) {
    super(id, parent);

And of course, readData, as you would expect, is a :

  • Private method
  • Looks through the POJO
  • If it finds a field which is not null then it sets it in the Gui Component

And of course, without writing the exact opposite of this method in the unit test, it just wasn’t possible to write unit tests. And sudddenly, it became clear why they were having trouble unit testing their Gui Components. Because if they wanted to test render (Which was really their aim), they would have to set up this POJO with the correct fields (which of course, to make things more interesting / miserable, had sub POJOs with sub POJOs of their own. Yay!) to be exercised in their test.

The problem with this approach is two fold :

  1. I need tests to ensure that the parsing and reading from the POJO logic is sound, and that it correctly sets up the GUI Component.
  2. Every time I want to test the render logic, I end up testing (unintentionally, and definitely unwantedly) the parsing logic.

This also adds, as I saw, obviously complicated pre test setup logic which should not be required to test something completely different. This is a HUGE code smell. Unit testing a class should not be an arduous, painful task. It should be easy as setting up a POJO and testing a method. The minute you have to perform complicated setup to Unit test a class (Note, the keyword is unit test. You can have integration tests which need some non trivial setup.), stop! There is something wrong.

The problem here is that there is a mixing of concerns in the MyGuiComponent class. As it turns out, MyGuiComponent breaks a few fundamental rules of testability. One, it does work in the constructor. Two, it violates the law of demeter, which states that the class should ask for what it needs, not what it doesn’t need to get what it needs (Does that even make sense ?). Thirdly, it is mixing concerns. That is, it does too much. It knows both how to create itself as well as do the rendering logic. Let me break this down further :

Work in the constructor

If you scroll back up and look at the constructor for MyGuiComponent, you will see it calling readData(pojo). Now, the basic concept to test any class is that you have to create an instance of the class under test (unless it has static methods. Don’t get me started on that…). So now, every time you create an instance of MyGuiComponent, guess what ? readData(pojo) is going to get called. Every. Single. Time ! And it cannot be mocked out. Its a private method. And god forbid if you really didn’t care about the pojo and passed in a null. Guess what ? It most probably will blow up with a NullPointerException. So suddenly, that innocuous method in the constructor comes back to haunt you when you write yours tests (You are, aren’t you ?).

Law of Demeter

Furthermore, if you look at what readData(pojo) does, you would be even more concerned. At its base, MyGuiComponent only cares about 6 fields which it needs to render. Depending on the state of each of these fields, it adds widget. So why does the constructor ask for something totally unrelated ? This is a fundamental violation of the Law of Demeter. The Law of Demeter can be summed up as “Ask for what you need. If you need to go through one object to get what you need, you are breaking it.”. A much more fancier definition can be found on the web if you care, but the minute you see something like A.B().C() or something along those lines, there is a potential violation.

In this case, MyGuiComponent doesn’t really care about the POJO. It only cares about some fields in the POJO, which it then assigns to its own fields. But the constructor still asks for the POJO instead of directly asking for the fields. What this means is that instead of just creating an instance of MyGuiComponent with the required fields in my test, I now have to create the POJO with the required fields and pass that in instead of just setting it directly. Convoluted, anyone ?

Mixing Concerns

Finally, what could be considered an extension of the previous one, but deserves a rant of its own. What the fundamental problem with the above class is that it is mixing concerns. It knows both how to create itself as well as how to render itself once it has been created. And the way it has been coded enforces that the creation codepath is executed every single time. To provide an analogy for how ridiculous this is, it is like a a Car asking for an Engine Number and then using that number to create its own engine. Why the heck should a car have to know how to create its engine ? Or even a car itself ? Similarly, why should MyGuiComponent know how to create itself ? Which is exactly what is happening here.


Now that we had arrived at the root of the problem, we immediately went about trying to fix it. My immediate instinct was to pull out MyGuiComponent into the two classes that I was seeing. So we pulled out a MyGuiComponentFactory, which took up the responsibility of taking in the POJO and creating a GuiComponent out of it. Now this was independently testable. We also added a builder pattern to the MyGuiComponent, which the factory leveraged.

class MyGuiComponentFactory {
    MyGuiComponent createFromPojo(ComponentId id,
                                  Component parent,
                                  MyDataContainingPOJO pojo) {
      // Actual logic of converting from pojo to
      // MyGuiComponent using the builder pattern
class MyGuiComponent {
    public MyGuiComponent(ComponentId id,
                          Component parent) {
        super(id, parent);
    public MyGuiComponent setName(String name) { = name;
        return this;

And now, suddenly (and expectedly, I would like to add), the constructor for MyGuiComponent becomse simple. There is no work in the constructor. The fields are set up through setters and the builder pattern. So now, we started writing the unit tests for the render methods. It took about a single line of setup to instantiate MyGuiComponent, and we could test the render method in isolation now. Hallelujah!!

Disclaimer :
No code was harmed / abused in the course of the above blog post. There were no separation issues whatsoever in the end, it was a clean mutual break!

July 2, 2009 at 12:57 am 1 comment

Two heads are better than one

The beginnings of this post were when a colleague asked me to send him a brief snippet about Pair Programming and its benefits. While the snippet I sent him was mostly definition oriented, it did get me thinking that it would make a great blog post. And so here it is.

Pair programming is an agile concept and is frequently used in XP (eXtreme Programming). At its core, it is nothing but having two people sit and code instead of one. And while that may seem like an obvious timesink and a doomed concept, considering two people cannot type and code at the same time, it is surprisingly effective for many reasons, some of which I will try to outline with examples from my brief experience.

When you work as part of a team, there is usually a process (sometimes a series of flaming hoops even) which you have to jump through before you can submit your new, super amazing, code which breaks all previous latency records. Or something just as amazing. And for a lot of groups, that involves a code review process, where someone familiar with the architecture of the system or understands the programming language and the problem goes through your code, points out issues (as if there are any in my code !!!) and so on. And while this is a good way to ensure that the quality of code that is submitted to your code base remains above a certain threshold, it becomes a huge timesink. Especially the more you know about the codebase, as everyone and their aunts start sending code reviews your way.

How is this solved with pair programming, you ask ? Well, consider this. While pair programming, assuming one guys starts coding away. What does the other guy do ? He (aha, you shout, as you understand even before I say it) reviews the code as you type, suggesting corrections and optimal solutions in case you start going down the wrong route. But then, you ask, isn’t that a huge waste of time, considering you are basically getting one person to just sit and permanently review ?

Here is where the beauty of pair programming really shines. Its called pair programming for a reason. For one, both programmers take turns in writing up new code, while the other looks on and makes sure the code is up to the amazingly high standards. Another, how many times have you written this super awesome function which took you half an hour to think of, only to find someone tell you in a code review to use this existing library function that does the entire same thing ? Now imagine that guy is, instead, sitting right next to you and telling you this before you even start coding this up.

Furthermore, what if I am a new guy joining a team with a very stable, settled code base. How do I hit the deck running, other than sitting for hours reading up on documentation ? Well, I go find a senior guy who loves pair programming (which is easier than it sounds if a team loves Agile practices) and go pair with him. Instant knowledge dump, and easier transition. This was the case with Arthur, a guy who joined our group for a short period of time. Instead of spending, say two weeks reading design and architecture documents, we started pairing with him from day one. By the end of day three, he had already fixed two bugs (both of which were on the first day itself!!!) and had made quite some headway into designing his first full feature. Now this intensive pairing (some might even call it hand holding) might have caused us to loose some productivity in the first few days, but by the 4th day, we had a new engineer who was capable of working independently if need be while pairing on the initial designs and features.

Also, Pair programming helps increase discipline and productivity. How you ask ? Well, I tend to loose focus quite easily, and love to be caught up on my emails (the thousands that spam me everyday, sigh!). And replying to my IMs takes precedence, often interrupting my thought process. Now I was pairing on the other hand, out of respect to my pair, I usually end up closing all such external annoyances, and often get two to three hours of uninterrupted work. Does wonders for my productivity, which is why I often roam around look for people to pair with.

Of course, if you need to convince management why you need to do pair programming, you need but point them at the multitude of studies that have been done which show an increased quality in software developed while pairing as compared to individuals. Also, if a person ever does end up leaving the team, there is someone on the team left who has paired with him and thus there are no systems which are alien to everyone on the team ever. And hey, its fun to pair, think out loud and bounce ideas off of each other. Seemingly impossible problems may seem easier as well when you pair. Often times, I seek out a teammate to bounce ideas off of, and more often than not, he will say “Alrite, let me get my keyboard. Lets pair on this.” Then it would take two hours to churn it out, and we would have a working, tested prototype by the end of it.

Of course, on the other hand, there is the intimidation factor of pairing with someone who seems much more knowledgeable and would eat you for lunch. Not to mention possible ego clashes and the fact that some people might find it akin to tutoring if they are paired with someone new. But these are pitfalls that can be overcome quite easily with a dedicated team.

And pair programming works really great when you do Test Driven Development. TDD is the art of writing a failing test before going and writing just the amount of code to pass the test. When you practice something known as ping pong pair programming with TDD, it becomes quite interesting and fun. In this, one person writes a failing test, and then the other person goes and writes the bare minimum code to get the test to pass (That is the key, the bare minimum. Don’t do speculative programming). And then, they switch. So the guy who wrote the code the first time now writes the next test, and the other person implements the functionality. This ensures that both people get turns at writing code and tests, and can make sure they cover all the cases. You end up with well tested code, but just enough code for your need. No speculation, no unneeded generalization, nothing extra.

And of course, no agile practice post is complete without an obligatory dilbert comic, so here goes :

Dilbert on Pair Programming

June 13, 2009 at 2:30 pm 2 comments

Coverage isn’t everything

A few posts ago, I mentioned Emma and code coverage, and how it could be useful. Code coverage, in layman’s terms, is the lines of code covered by your tests. So generally, you want a high code coverage, implying that most of your code is well tested.

But since my post, I have talked with a few friends and colleagues, and one point has been brought up again and again. First, it was a discussion with my friend on his homework assignment. It was a hypothetical situation about a manager wanting 100 % code coverage before he launches his product. That discussion quickly devolved into a rant about why code coverage isn’t the alpha and the omega.

And then, just one or two days ago, I had another discussion with a colleague, who was telling / reminding me of the fact that a project having great code coverage doesn’t mean that they don’t need to test it anymore. I politely agreed and nodded my head, and both of us ended up repeating the same facts to each other. Which was that code coverage, like a lot of other things, can be faked.

The trick with code coverage is that a high code coverage number doesn’t actually tell you anything in and by itself. For it is just as easy to get a high code coverage with a single line of test which exercises the entire system as it is to do it the hard way and write a lot of small unit tests. A single unit test which executes main will most likely result in a high code coverage number, even without having any assertions.

Similarly, consider the following example :

void someMethod(int a, String b) {

if (a < someThreshold || isValid(b)) {
// Do first thing
} else if (a == someThreshold && isNumber(b)) {
// DO second thing

Now, it is possible to to write just two unit tests, and still attain 100% coverage. Here, if I call this test with a < someThreshold and a == someThreshold, I get 100% coverage. That does not mean though, that I have covered all possible cases. I mean, in my example, I didn’t even touch b.

And these are exactly the type of things which can demean the value of code coverage. Any manager worth his salt should understand this aspect of code coverage. It is possible and not too difficult to attain a very high code coverage even with a sub par quality product. The trick is in understanding how the tests are written, and how comprehensive they are.

Code coverage is a great tool to find out spots which are completely untested, and projects which develop their code in a Test Driven fashion often end up with high code coverage. But that does not imply that projects with a high code coverage are of the greatest quality. Careful consideration of their testing practices and comprehensiveness is essential in these cases. Track stuff like bugs, amount of test code written compared to amount of production code, etc to get a overall picture, rather than relying on just one metric.

September 30, 2008 at 11:09 am 3 comments

My code’s untestable !!

I have frequently heard this complaint, from some really great engineers in the past year. My code’s untestable, there’s no way i can test this, the only way to test my code is to write a full on end to end test. And in some cases, it was actually true. But the thing is, it doesn’t need to be that way. There are always ways to twist and turn the untestable code into testable code, in other words refactor.

But before you get excited, and go aha, thats what I am going to do, hold your horses for a second. What are you going to go refactor ? Well, don’t scratch your heads, there are a few things to look out for. Similar to the code smells we had, there are similar smells we can look for, which indicate that the code is untestable. And there are a few standard ways to tackle them, and make your classes testable. So without further adieu, lets take a look at the more common and annoying testability smells.

  1. Constructor doing work :
    This is one of the biggest things preventing a class from being testable. There are many names to this smell, including constructor doing work,  Breaking the law of demeter, etc. but all it comes down to is the constructor doing more than just assigning stuff to local variables. For example, something like :

    XPathConvertor() {
    this.xpathDatabase = XPathDatabaseFactory.getDatabase();
    XPathMapper mapper = new SimpleXPathMapper(“Simple Mapper”);
    this.xpathTranslator = XPathTranslatorFactory.getTranslator(this.xpathDatabase, mapper);

    While the above may seem a contrived example, or too simple, it exhibits what is at the centre of most bad constructors. One, its a default constructor. Then it goes out, grabs a database out from ether (Static factory method call), and then creates a mapper, and then passes those two to get a XpathTranslator object. Now, take my word for it, but the XPathConvertor only needs xpathTranslator. SO what is it doing with the darn database and the mapper. This is breaking the law of demeter, which states that “The constructor should only ask for what it needs, and nothing else.”

    Why is this bad ? Well, for one, if the thing your constructor is creating is a heavy piece of service like a database or something, there’s a huge hit in your test. Your test is no longer a unit test, but an integration test. Each call now has to travel to the DB and back, and just makes everything slower. Secondly, there are some cases in which it picks up a service which you just can’t work with in a test. Something which either needs the whole production setup, or just doesn’t work in a unit test. And since it reaches into static factories to get that, there’s no way for you to slip in your mock.

    So instead, start passing in what is needed to your constructor. This forms the basis of Dependency Injection, or slipping in a fake, or whatever you want to call it. Basically, your constructor takes in what it needs, and all it does is assign stuff to local variables. No work is done there. So the above code becomes something like :

    XPathConvertor(XPathTranslator translator) {
    this.xpathTranslator = translator;

    So much cleaner, and only has what it needs. So in our test, you can create a translator and pass it in which uses a mock db, or pass in a fake translator or whatever. The point is, testing becomes easier.

  2. Global State :
    The second biggest complaint with untestable code. It usually has to do with Global state. Or as some people like to call it, putting things in and pulling things out of ether. This might be anything from using global static singletons to static method calls inbetween your method.

    How is this bad ? Consider some method you are testing. What if it suddenly reaches out into the ether, and grabs some object and uses it to perform its calculations. You say, ok, I can somehow add a setter which allows me to set its state. Now what if there are multiple tests running in parallel…. Yes, exactly. Not good. Furthermore, you can’t mock a static method, which makes life miserable.

    Consider this question then, why does it need to be static ? What benefit are you getting, other than the fact that you don’t need to create an object ? Is it really worth making code untestable in order to reduce one line of code of creating an object ? The answer 9 times out of 10, I find, is no.

September 4, 2008 at 2:53 pm Leave a comment

Fakes and Mocks and Stubs, Oh My!!!

So we covered how to use EasyMock to write tests in one of the previous posts, but Mocking is not the only option when you want to test something that depends on a slow and expensive service. Mocking allows you to expect calls and return values when a call is made, and make sure the number of calls were correct and the order, but sometimes, you want a bit more, or not even that much. So in those cases, you have the options of using Stubs or Fakes. So without further delay, your options are :

  1. Mocks :
    Well, Mocks… What can I say. I have already ranted and raved about the awesomeness that is Mocks. Mocks and Mocking frameworks allow you to replace heavy and expensive services with Mocks, with which you can set expectations on what calls are made to the service, and return values. This gives you the advantage of knowing exactly what is called and returned, and makes your test deterministic and super fast. You can even set expectations on the number of calls and the order, though this is something that is not extremely recommended, since that makes the test dependent on the implementation, which is never a good thing.

    Advantages :

    • Fast, Reliable
    • Deterministic
    • Lightweight
    • Control over expectations and return values.

    Disadavantages :

    • Can become dependent on implementation of method being tested.
    • Can become a mockery if not careful, that is, can be testing interaction between mocks and nothing of the actual code. Especially when all that the method under test is doing is delegating to a bunch of service calls.
    • Can involve complicated setup for expectations, especially with unwieldy objects
  2. Stubs :
    Now, whereas with Mocks, you can specify what calls will be received and what will be returned making them somewhat intelligent, Stubs are at the other end of the spectrum. The dumbest of the dumb, the easiest of the easiest, these just stub out the methods of your expensive and heavy class. So a null Stub could return null for each method, or just return some constant value each time it is called. That means that regardless of what the method is called with, it returns the exact same thing, day in and day out. It doesn’t adjust, it doesn’t react, just returns. Of course, this means that you might not be able to test all the cases you want to inspect / test. But its simple, its easy, and of course, its fast.

    Advantages :

    • Fast, reliable
    • Simple
    • Consistent

    Disadvantages :

    • Dumb
    • Can’t exercise different cases without different stubs
    • Returns only one value consistently
  3. Fakes :
    And finally, we come to the smartest (figuratively) of the lot. The Fakes. For once, being a fake can be good. While Stubs return the same thing again and again, and mocks return what you tell it to, Fakes are smarter. The easiest way to explain a Fake is with an example. Say your code depends on a heavy service like a Database. A FakeDatabase would be an in-memory implementation of the DB, thus making it faster while at the same time, providing the same logic as the normal DB would. There are different types of Fakes, like a listening / recording Fake which records all the values passed to it.

    Advantages :

    • Can test while preserving behavior of dependencies
    • Faster than using actual services
    • Can test complicated logic
    • Most comprehensive testing approach

    Disadvantages :

    • Can be complicated to set up
    • Not as fast as mocks / stubs
    • Not as easy to define expectations
    • When / Where do you test the fake (especially the complicated ones) ?

Thats my 2 cents on the different approaches to testing with dependencies. Now that we know what we can do with those darn heavy dependencies, I’ll talk more on how to make sure you can use these different approaches to test your code soon.

August 21, 2008 at 3:50 am 3 comments

Your code smells!!!

I was planning to talk about Dependency Injection or the difference between Mocks, Stubs and Fakes, but I think I would prefer to get this one out first. For those of you who haven’t heard the term before, a code smell is something that indicates there is something wrong with the source code, be they design problems or signs that the code needs refactoring. So in this post, I would like to mention a few common code smells, their identifying patterns and how to fix them. So without any further delay, lets start :

  1. Too many comments
    The Problem : Lets start with the easiest to identify code smell. Comments are good, if they are describing a class or a method. But when you start having comments in your code explaining what a particular block of code does, you know you are in trouble.
    The Fix : If there is a block of code which does some complicated stuff, and you feel you need to comment it to make it easily understood, pull it out into a well named method, and let the method name describe what it does.
  2. Long Class / Method
    The Problem :
    These two code smells actually are similar. If you have a method which goes beyond 10 – 15 lines, then you have a long method. While there is nothing technically wrong with long methods, its not as easy to comprehend as a nice small method, and can make maintenance a pain in the rear. Long classes also are similar, having too many things that its trying to do. If you generally try describing a class and have to use ands and ors, then you have a long class.
    The Fix : Pull out parts of the long method into smaller well named methods. The advantage is two fold. One, your method is much more readable now. And two, you can now test individual methods you have pulled out, making testing a much easier task than one giant method. Same with classes, break it up into multiple smaller easily testable classes.
  3. Primitive Obsession
    The Problem :
    How many times have you had to write a class which takes in, say a phone number ? And how many times have you passed in a String or a long to the class which asks for the phone number ? If you raised your hand, then congrats, you have a code smell known as primitive obsession. This happens when instead of creating an object, you pass around primitives, and write functions to operate and convert that primitive from one form to another. So you might have to create utility classes which give you a phone number with brackets from a string, and so on and so forth.
    The Fix : Just give the poor thing a class. If you operate on phone numbers, create a PhoneNumber class which has methods to operate on the number. Makes it easier for anyone using the class as well, and of course, its testable :D.
  4. Feature Envy / Inappropriate Intimacy
    The Problem :
    Feature Envy is when a method on a class is more interested in other classes than the class to which it belongs. The reason for this could be as simple as the method being in the wrong class to something more non trivial. Inappropriate intimacy is when two classes are so tightly coupled that one depends on the other to work a particular way for it to work.
    The Fix : For feature envy, just move the method to where it belongs. If it does work solely on some other class, then maybe it belongs on that class instead of where it is currently. For inappropriate intimacy, you need to figure out if the problem is something simple or something more complicated. It might be that the interfaces weren’t selected appropriately, or you might need to introduce a layer to keep the coupling loose, or even refactor the code to make sure it does not depend on another tightly coupled class.
  5. Lazy class / Dead code / Duplicate code / Speculative Generality
    The Problem
    : All of the above are usually simple code smells which indicate you have code which you don’t need. Lazy class is when a class doesn’t do enough to justify its existence. Dead code is obvious, code which is not used or dead. Duplicate code, duh, Its duplicated. Speculative generality is the most interesting of the lot. Its when you write some code for something which you don’t need yet, but may need at some point in the future.
    The Fix : For the first three code smells, the fix is trivial. Delete it. Dont even think about it, just blindly delete it. Duplicate code is a pain to maintain as well, pull it out into a method and then delete the duplicates. Speculative generality is one thing people don’t realize they are doing or feel they need to do it now since otherwise, it might become difficult to do in the future. The interesting thing is that the feature they added speculatively is rarely ever used. Its an additional overhead to maintain and test for something you never use. Don’t do it. If you can implement it now, you can implement it when you need it. Just delete that darn code.

There are a lot more code smells than I could list out here, but these are a few of the most common ones you should keep a lookout for. Google search Code smells if you want to learn more about these insidious creations :D. Next time, before I start dependency injection, I think I will rant about things which make code untestable. So in a sense, Testability code smells.

August 11, 2008 at 12:58 am 4 comments

Older Posts


Blog Stats

  • 5,606 hits



July 2018
« Jul