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Automated Static Analysis Tools (ASATs) are part of software development bestpractices. ASATs are able to warn developers about potential problems in thecode. On the one hand, ASATs are based on best practices so there should be anoticeable effect on software quality. On the other hand, ASATs suffer fromfalse positive warnings, which developers have to inspect and then ignore ormark as invalid. In this article, we ask the question if ASATs have ameasurable impact on external software quality, using the example of PMD forJava. We investigate the relationship between ASAT warnings emitted by PMD ondefects per change and per file. Our case study includes data for the historyof each file as well as the differences between changed files and the projectin which they are contained. We investigate whether files that induce a defecthave more static analysis warnings than the rest of the project. Moreover, weinvestigate the impact of two different sets of ASAT rules. We find that, buginducing files contain less static analysis warnings than other files of theproject at that point in time. However, this can be explained by the overalldecreasing warning density. When compared with all other changes, we find astatistically significant difference in one metric for all rules and twometrics for a subset of rules. However, the effect size is negligible in allcases, showing that the actual difference in warning density between buginducing changes and other changes is small at best.

Are automated static analysis tools worth it? An investigation into relative warning density and external software quality