Quality: The Process, Part II [Beyond the build]

[continued from Expanding our repertoire]

Beyond the build

The most powerful programs for glass box testing include source code analysis, runtime checking, and automated testing tools. These are not generally included in compiler packages, so they need to be obtained separately, and can often be somewhat expensive.

Source code analysis tools, better known as “lint” tools in C and C++ development, are utilities that examine your source code and produce warnings for potential problems. The output is similar to that from a compiler, except that the tool performs deeper checks, even emulated code walkthroughs, and has a larger and more specific set of issues to check.

A decent source code analysis tool would likely be your best investment of any glass box testing tool. Unlike a compiler, which merely needs to produce object code for a specific platform, a lint tool can check for a whole range of problems, from portability to standards compliance, and some coding guidelines. The details of potential problems can even help a programmer to better understand nuances of the language.

Lint tools produce many more warnings and errors than a compiler, but they also provide great flexibility to disable individual warnings, even for specific lines of code. It is unlikely that a non-trivial program could pass through such a tool at the highest level without warnings (and sometimes thousands of them), but each issue or type of warning identifies a pitfall that can be considered and resolved.

When developing, I run source code analysis on a regular basis to catch potential errors that the compiler missed. In this way, I can remain confident that my code is relatively free of silly errors, so I can instead concentrate on the logic of the overall code, not individual mistakes. Also, anywhere that my code does something unusual, there is, by necessity, a comment indicating a suppressed lint warning.

Another way of performing some rudimentary source code analysis, especially for a cross-platform project, is to compile the source code under two different development environments. It is somewhat inconvenient, particularly during the initial setup, but if code can build and work correctly from two different compilers, chances are pretty good that the code is solid.

Runtime checking tools include a variety of programs that automatically monitor the behavior of the program as it executes. Often, these tools check memory or resource usage, but they can also watch for invalid pointers and range errors, verify API parameters and return values, and report on code coverage. The most common benefit of these tools is to identify memory and resource leaks.

A comprehensive runtime checking tool serves as an ideal supplement to a source code analysis tool. While the latter catches potential problems with the code itself, the runtime checker highlights problems with the logic of the application during execution. Some tools can insert extra code and information during the build, in a process known as “instrumentation”, and this improves the runtime testing even more.

One issue with runtime checking is that it tends to slow program execution significantly, so it is definitely not intended for a release version, nor for every debugging build. Nevertheless, like other testing techniques, it is best to use the available tools early and often. The earlier a bug is detected and identified, the easier and less costly it will be to fix.

In my development process, I use my source code analysis tools after writing or modifying no more than a couple of routines. I use my runtime checking tools, at the highest detection level, after every major feature update, or before every delivery to a client. This glass box testing takes place in the background while I do black box testing of the application and, especially, new or updated features. If any problems appear, I address those problems right away before considering the feature to be done.

[continued in Automatic or manual]

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