On Applying Bandit Algorithm to Fault Localization Techniques

TL;DR

This paper proposes a dynamic approach to fault localization that adaptively selects the most effective techniques during debugging, aiming to improve performance over static selection methods.

Contribution

It introduces a novel method applying bandit algorithms to fault localization, enabling real-time technique selection during debugging sessions.

Findings

Dynamic selection improves fault localization accuracy.

Bandit algorithms adaptively optimize technique choice.

Enhanced debugging efficiency through adaptive methods.

Abstract

Developers must select a high-performance fault localization (FL) technique from available ones. A conventional approach is to try to select only one FL technique that is expected to attain high performance before debugging activity. In contrast, we propose a new approach that dynamically selects better FL techniques during debugging activity.