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Raw lines of code (LOC) is a metric that does not, at first glance, seemextremely useful for automated test generation. It is both highlylanguage-dependent and not extremely meaningful, semantically, within alanguage: one coder can produce the same effect with many fewer lines thananother. However, relative LOC, between components of the same project, turnsout to be a highly useful metric for automated testing. In this paper, we makeuse of a heuristic based on LOC counts for tested functions to dramaticallyimprove the effectiveness of automated test generation. This approach isparticularly valuable in languages where collecting code coverage data to guidetesting has a very high overhead.We apply the heuristic to property-basedPython testing using the TSTL (Template Scripting Testing Language) tool. Inour experiments, the simple LOC heuristic can improve branch and statementcoverage by large margins (often more than 20%, up to 40% or more), and improvefault detection by an even larger margin (usually more than 75%, and up to 400%or more). The LOC heuristic is also easy to combine with other approaches, andis comparable to, and possibly more effective than, two well-establishedapproaches for guiding random testing.

Using Relative Lines of Code to Guide Automated Test Generation for Python