Broccoli: Bug localization with the help of text search engines

by   Benjamin Ledel, et al.

Bug localization is a tedious activity in the bug fixing process in which a software developer tries to locate bugs in the source code described in a bug report. Since this process is time-consuming and requires additional knowledge about the software project, information retrieval techniques can aid the bug localization process. In this paper, we investigate if normal text search engines can improve existing bug localization approaches. In a case study, we evaluate the performance of our search engine approach Broccoli against seven state-of-the-art bug localization algorithms on 82 open source projects in two data sets. Our results show that including a search engine can increase the performance of the bug localization and that it is a useful extension to existing approaches. As part of our analysis we also exposed a flaw in a commonly used benchmark strategy, i.e., that files of a single release are considered. To increase the number of detectable files, we mitigate this flaw by considering the state of the software repository at the time of the bug report. Our results show that using single releases may lead to an underestimation of the the prediction performance.


DRAST – A Deep Learning and AST Based Approach for Bug Localization

Context: Given a bug report and source code of the project, bug localiza...

A literature review on different types of empirically evaluated bug localization approaches

Today, software systems have a significant role in various domains among...

BULNER: BUg Localization with word embeddings and NEtwork Regularization

Bug localization (BL) from the bug report is the strategic activity of t...

Does the duration of rapid release cycles affect the bug handling activity?

Software projects are regularly updated with new functionality and bug f...

IncBL: Incremental Bug Localization

Numerous efforts have been invested in improving the effectiveness of bu...

PR-SZZ: How pull requests can support the tracing of defects in software repositories

The SZZ algorithm represents a standard way to identify bug fixing commi...

RLocator: Reinforcement Learning for Bug Localization

Software developers spend a significant portion of time fixing bugs in t...

Please sign up or login with your details

Forgot password? Click here to reset