Using Code Coverage Tools in the Linux Kernel

Defining software reliability is hard enough, let alone ensuring it. However, most all software developers agree on the importance of testing. The often unspoken assumption with testing is that the test programs cover a majority of the source code written. A test covers a line of code if running the test executes the line. Coverage analysis measures how much of the target code is run during a test and is a useful mechanism for evaluating the effectiveness of a system test or benchmark. The GNU development tool gcov allows developers to obtain coverage results for programs compiled with the GNU gcc compiler. In this article, we learn how to instrument the Linux r © kernel to generate code coverage data, and how to visualize results with tools from the Linux Test Project (LTP) [4]. 1 Coverage Basics Code coverage analysis is the process that allows us to determine the percentage of code within an appli-cation that was executed during the test process. The data gathered by using coverage analysis can be used to measure and improve the test process [6]. Coverage analysis can be performed in a variety of ways for producing different views of how a test process executes the code. A few types of coverage analysis are discussed here