State Profiling of Internal Variables

Execution profiles form the basis of many dynamic program analysis techniques developed to solve problems in fields such as software testing, fault localization, and program comprehension. A typical profile comprises information that approximates the execution path of a program, specifically, the frequency of occurrence of program elements that are structural in nature, such as statements, branches, and def-use pairs. It is plausible that some defects might not be characterized by a failing path or a set of structural program elements. In such cases, execution profiles that are based on structural elements would not be of much benefit. We argue for the need to leverage the state of the subject program, i.e., to analyze the values of representative internal variables that approximate the program state. For that purpose we: 1) built a profiling tool that captures the values taken by select variables, 2) devised three metrics to quantify the dissimilarities between our state-based execution profiles, and 3) conducted ten case studies to demonstrate the effectiveness of our tool and metrics. The majority of our case studies (8 out of 10), using all metrics, showed that failing profiles are most dissimilar from passing profiles.