Well, I am back from a sailing excursion to the San Juan Islands. I wanted to go to the Gulf Islands, but considering an unexpected ordeal with a kidney stone just before taking off on the trip I decided it might be better to be a bit closer…just in case. The weather was great, and we spent a lot of time exploring Stuart and James Islands, and dropped into Roche Harbor the first night and Friday Harbor the last night in the islands. We limited out on Dungeness crabs on all but 2 days where we only managed to get 3 legal size crabs on those 2 days. Basically this translates to a lot of crab cakes in the freezer…yum! This was the first time my daughter went crabbing with me. My daughter would ride out in the dinghy with me to check the pots, and would point out the male crabs for me, but she wouldn’t reach in an help me throw back the females or undersized males. Come to think about it, she didn’t help me cook and clean the crabs either…she just ate the crab cakes we made on the boat. I think the rules might have to change next year! All in all it was a great month decompressing and recharging, and contemplating my personal and professional future.
But enough about me. My last 2 posts have been discussing code coverage analysis. The primary purpose of using code coverage tools as either a developer or as a tester is not to try to obtain some magical ROMA number. The biggest value of measuring code coverage is to help us analyze untested areas of code and make informed decisions of whether or not we need to design additional tests to increase test coverage and help reduce exposure to risk.
The last post illustrated how we might use code coverage results to help us design additional tests we might have missed during the execution of any pre-defined tests (automated or manual) and additional exploratory testing efforts. But remember, the goal is simply not to design tests in order to get the tool to report 100% code coverage. In fact, in just about any complex system executing 100% of the statements in code may not be feasible or provide any practical value. This is generally referred to as unreachable code.
For example, let’s look at this (albeit antiquated) code snippet.

The code coverage tool is indicating that this conditional statement has been exercised to its true outcome, but not it’s false outcome. This was a common approach used in 16-bit applications to prevent multiple instances of the same application on a single machine. However, in the 32-bit world hPrevInstance always returns null, which means there is no practical way to make this conditional statement return false.
This is a bit of an obscure example, but is used to illustrate why a greater understanding of the programming language used by the development team would help testers from banging their heads against the wall ‘trying’ different things until someone realizes we could never make this conditional statement return false. By analyzing this section of the code coverage results we might suggest refactoring for a Win32/64 environment, or at least be able to explain why this conditional will not return false. (Remember…it’s all about information.)
Another example of unreachable code is sometimes caused by coding style or possibly unnecessary code. For example, the following lines are also in the WinMain() function that is called when the ‘user’ launches the application.

In this situation when the application initially starts and calls the WinMain() function these 2 conditional statements in WinMain() determine whether the Frog and Car bitmaps are true. Since we just launched the application and the bitmaps have not yet been loaded by any other calls to LoadBitmap() then the conditional statements in lines 104 and 109 will never go true, and lines 105 and 110 will never be executed. Again, following an analysis of the section of the code we can provide information regarding why we can’t design a test to cause these conditional statements to return true without fault injection or code mutation. Additional information that we might provide based on our analysis of the code coverage results may be a suggestion to refactor this code to improve testability.
A similar example of unreachable code is a common coding style involving switch statements where developers included a case statement for each possible value, and also included a default statement. For example in the last post we saw how we saw this code chunk which is essentially the menu structure.

When the menu item is selected the submenu displays the submenu items Start and Exit. When the submenu is displayed the only actions possible is to select the Start submenu item (line 270), or the Exit submenu item (line 274). Without fault injection there is no practical way to execute the default statement in line 277. Again, this may be another example where refactoring could improve testability because if the default statement is removed control flow would simply pass out of the switch block.
However, this is not always the case with switch statements. Here is an example in which a modal message box is displayed and draws 2 buttons; a yes button to restart the game, and a no button to quit the game. But notice that the default case statement (line 295) has not been executed.

In this situation if we launch the game, move the frog to get hit by a car this modal message box will display showing the ‘end user’ 2 possible buttons to press (in this case the ESC key or the Close control button in the upper right corner of the modal dialog are not possible options). However, if we put the game into a state where this modal dialog is displayed and then kill the application process using Windows Task Manager control flow will pass to line 295 as the process terminates.
Of course, it may not be practical or reasonable to terminate the application process from every possible machine state. Also, this simply increases the costs of testing without adding any real practical value. Providing this information to the decision makers along with suggestions to refactor and improve testability to reduce overall testing costs is another way code coverage analysis can be a valuable tool in a tester’s toolbox.
Another example of hard to reach code. In this case the conditional statement is if the RegisterClass() function fails then we want to return false.

The RegisterClass() function is also called within the WinMain() function when the application initially launches. So, while analyzing the code coverage results the question we ask ourselves is, “Without fault injection can we make the conditional statement in line 88 return true, and if so how?”
Well, we can. All we have to do is launch about 450 instances of this application to cause line 88 return true. Now, we have to ask ourselves, “What value does this test provide?” Especially since the code design should only allow 1 instance of the application (although it fails to do that because it is a 16-bit app running on a 32-bit environment and that is the nature of hPrevInstance as explained earlier.
From a testing perspective the primary goal of code coverage is not to achieve some magic number; the objective of code coverage is to analyze code coverage results in order to
- Improve test coverage
- Reduce overall risk
- Potentially increase testability of the project
The code coverage number is not really useful information to anyone. It is the analysis of the code coverage results that can help us decide whether we need to design additional tests, identify areas of the code that can’t be executed without even more expensive testing such as fault injection and/or code mutation, or refactor the code to improve testability (which often increases the code coverage measure).
But, this is not to suggest that we should employ code coverage and analyze the results for all software projects. Analyzing code coverage results and designing additional tests from a white box perspective, or refactoring code are all additional expenses for any project. For each project we (or our managers) must decide whether the cost is worth the improved coverage and potentially a reduction in overall risk.
Another way to look at it…it is our responsibility as testers to provide valued information to the decision makers. If the only information we are providing is that we achieved 80% code coverage then we really aren’t doing an effective job. Yes, many managers are number focused; however, the valuable information is in the rest of the story about the 20% that has not been executed.