DSI: an evidence-based approach to identify dynamic data structures in C programs

Abstract

Comprehension of C programs containing pointer-based dynamic data structures can be a challenging task. To tackle this challenge we present Data Structure Investigator (DSI), a new dynamic analysis for automated data structure identification that targets C source code. Our technique first applies a novel abstraction on the evolving memory structures observed at runtime to discover data structure building blocks. By analyzing the interconnections between building blocks we are then able to identify, e.g., binary trees, doubly-linked lists, skip lists, and relationships between these such as nesting. Since the true shape of a data structure may be temporarily obscured by manipulation operations, we ensure robustness by first discovering and then reinforcing evidence for data structure observations. We show the utility of our DSI prototype implementation by applying it to both synthetic and real world examples. DSI outputs summarizations of the identified data structures, which will benefit software developers when maintaining (legacy) code and inform other applications such as memory visualization and program verification.