Improving Efficiency and Scalability of Formula-based Debugging

TL;DR

This paper introduces two techniques, on-demand formula computation and clause weighting, to enhance the efficiency and accuracy of formula-based debugging by focusing on relevant code parts and utilizing passing test information.

Contribution

The paper presents novel methods that significantly improve the computational efficiency and fault localization accuracy of existing formula-based debugging approaches.

Findings

Both techniques improve debugging performance.

OFC reduces computational cost by focusing on relevant code.

CW leverages passing tests to enhance fault detection.

Abstract

Formula-based debugging techniques are becoming increasingly popular, as they provide a principled way to identify potentially faulty statements together with information that can help fix such statements. Although effective, these approaches are computationally expensive, which limits their practical applicability. Moreover, they tend to focus on failing test cases alone, thus ignoring the wealth of information provided by passing tests. To mitigate these issues, we propose two techniques: on-demand formula computation (OFC) and clause weighting (CW). OFC improves the overall efficiency of formula-based debugging by exploring all and only the parts of a program that are relevant to a failure. CW improves the accuracy of formula-based debugging by leveraging statistical fault-localization information that accounts for passing tests. Our empirical results show that both techniques are effective and can improve the state of the art in formula-based debugging.