Static Detection of Asymptotic Performance Bugs in Collection Traversals

This paper identifies and formalizes a prevalent class of asymptotic performance bugs called redundant traversal bugs and presents a novel static analysis for automatically detecting them. We evalu-ate our technique by implementing it in a tool called CLARITY and applying it to widely-used software packages such as the Google Core Collections Library, the Apache Common Collections, and the Apache Ant build tool. Across 1.6M lines of Java code, CLAR-ITY finds 92 instances of redundant traversal bugs, including 72 that have never been previously reported, with just 5 false positives. To evaluate the performance impact of these bugs, we manually repair these programs and find that for an input size of 50,000, all repaired programs are at least 2.45 × faster than their original code