SEJul 20, 2018

Poster: Improving Bug Localization with Report Quality Dynamics and Query Reformulation

arXiv:1807.07676v112 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of improving bug localization for software developers by analyzing report quality dynamics, though it is incremental as it builds on existing studies.

The paper investigates how the quality of bug reports, including the presence or absence of structured information like program entity names and stack traces, affects the performance of IR-based bug localization techniques, based on an empirical study of 5,500 bug reports from eight systems.

Recent findings from a user study suggest that IR-based bug localization techniques do not perform well if the bug report lacks rich structured information such as relevant program entity names. On the contrary, excessive structured information such as stack traces in the bug report might always not be helpful for the automated bug localization. In this paper, we conduct a large empirical study using 5,500 bug reports from eight subject systems and replicating three existing studies from the literature. Our findings (1) empirically demonstrate how quality dynamics of bug reports affect the performances of IR-based bug localization, and (2) suggest potential ways (e.g., query reformulations) to overcome such limitations.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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