Exploration of the scalability of LocFaults

TL;DR

This paper evaluates the scalability of LocFaults, an error localization method that uses control flow paths and minimal correction sets, demonstrating improved performance and expressiveness over existing SAT-based approaches like BugAssist.

Contribution

The paper introduces a scalable approach for error localization using control flow graph paths and minimal correction sets, with comparative analysis against BugAssist.

Findings

LocFaults outperforms BugAssist in execution time.

LocFaults provides more expressive diagnostic information.

Preliminary results show effectiveness on programs with unfolded loops.

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 scalability 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.