Abstract
Code coverage is a common measure for quantitatively assessing the quality of software testing. Code coverage indicates the fraction of code that is actually executed by tests in a test suite. While code coverage has been around since the 60's there has been little work on how to effectively analyze code coverage data measured in system tests. Raw data of this magnitude, containing millions of data records, is often impossible for a human user to comprehend and analyze. Even drill-down capabilities that enable looking at different granularities starting with directories and going through files to lines of source code are not enough. Substring hole analysis is a novel method for viewing the coverage of huge data sets. We have implemented a tool that enables automatic substring hole analysis. We used this tool to analyze coverage data of several large and complex IBM software systems. The tool identified coverage holes that suggested interesting scenarios that were untested. © 2009 IEEE.