Travioli: A Dynamic Analysis for Detecting Data-Structure Traversals

Abstract

Traversal is one of the most fundamental operations on data structures, in which an algorithm systematically visits some or all of the data items of a data structure. We propose a dynamic analysis technique, called Travioli, for detecting data-structure traversals. We introduce the concept of acyclic execution contexts, which enables precise detection of traversals of arrays and linked data structures such as lists and trees in the presence of both loops and recursion. We describe how the information reported by Travioli can be used for visualizing data-structure traversals, manually generating performance regression tests, and for discovering performance bugs caused by redundant traversals. We evaluate Travioli on five real-world JavaScript programs. In our experiments, Travioli produced fewer than 4% false positives. We were able to construct performance tests for 93.75% of the reported true traversals. Travioli also found two asymptotic performance bugs in widely used JavaScript frameworks D3 and express.