Directed Test Generation to Detect Loop Inefficiencies

Redundant traversal of loops in the context of other loops has been recently identified as a source of performance bugs in many Java libraries. This has resulted in the design of static and dynamic analysis techniques to detect these performance bugs automatically. However, while the effectiveness of dynamic analyses is dependent on the analyzed input tests, static analyses are less effective in automatically validating the presence of these problems, validating the fixes and avoiding regressions in future versions. This necessitates the design of an approach to automatically generate tests for exposing redundant traversal of loops. In this paper, we design a novel, scalable and automatic approach that addresses this goal. Our approach takes a library and an initial set of coverage-driven randomly generated tests as input and generates tests which enable detection of redundant traversal of loops. Our approach is broadly composed of three phases - analysis of the execution of random tests to generate method summaries, identification of methods with potential nested loops along with the appropriate context to expose the problem, and test generation to invoke the identified methods with the appropriate parameters. The generated tests can be analyzed by existing dynamic tools to detect possible performance issues. We have implemented our approach on top of the SOOT bytecode analysis framework and validated it on many open-source Java libraries. Our experiments reveal the effectiveness of our approach in generating 224 tests that reveal 46 bugs across seven libraries, including 34 previously unknown bugs. The tests generated using our approach significantly outperform the randomly generated tests in their ability to expose the inefficiencies, demonstrating the usefulness of our design