Exploration of the scalability of LocFaults approach for error localization with While-loops programs

TL;DR

This paper investigates the scalability of the LocFaults error localization method for programs with While-loops, demonstrating improved performance and more expressive results compared to existing SAT-based approaches.

Contribution

The paper presents an analysis of LocFaults' scalability on loop-heavy programs, highlighting its efficiency and richer diagnostic information over prior methods like BugAssist.

Findings

LocFaults outperforms BugAssist in execution time on loop-unfolded programs.

LocFaults provides more detailed and user-friendly error localization information.

Preliminary results show promising scalability for LocFaults with increasing loop complexity.

Abstract

A model checker can produce a trace of counterexample, for an erroneous program, which is often long and difficult to understand. In general, the part about the loops is the largest among the instructions in this trace. This makes the location of errors in loops critical, to analyze errors in the overall program. In this paper, we explore the scala-bility capabilities of LocFaults, our error localization approach exploiting paths of CFG(Control Flow Graph) from a counterexample to calculate the MCDs (Minimal Correction Deviations), and MCSs (Minimal Correction Subsets) from each found MCD. We present the times of our approach on programs with While-loops unfolded b times, and a number of deviated conditions ranging from 0 to n. Our preliminary results show that the times of our approach, constraint-based and flow-driven, are better compared to BugAssist which is based on SAT and transforms the entire program to a Boolean formula, and further the information provided by LocFaults is more expressive for the user.