A Comprehensive Study of Pseudo-tested Methods

TL;DR

This study investigates pseudo-tested methods, which are covered by tests but not effectively tested, confirming their prevalence and analyzing their characteristics to inform future targeted testing strategies.

Contribution

It replicates and extends previous research on pseudo-tested methods with new data, tools, and detailed manual analysis, providing deeper insights into their nature and testing gaps.

Findings

Pseudo-tested methods are present in all studied projects.

They are significantly less tested than other methods.

Developers often choose not to fix the testing gaps due to cost.

Abstract

Pseudo-tested methods are defined as follows: they are covered by the test suite, yet no test case fails when the method body is removed, i.e., when all the effects of this method are suppressed. This intriguing concept was coined in 2016, by Niedermayr and colleagues, who showed that such methods are systematically present, even in well-tested projects with high statement coverage. This work presents a novel analysis of pseudo-tested methods. First, we run a replication of Niedermayr's study with 28K+ methods, enhancing its external validity thanks to the use of new tools and new study subjects. Second, we perform a systematic characterization of these methods, both quantitatively and qualitatively with an extensive manual analysis of 101 pseudo-tested methods. The first part of the study confirms Niedermayr's results: pseudo-tested methods exist in all our subjects. Our in-depth characterization of pseudotested methods leads to two key insights: pseudo-tested methods are significantly less tested than the other methods; yet, for most of them, the developers would not pay the testing price to fix this situation. This calls for future work on targeted test generation to specify those pseudo-tested methods without spending developer time.