TRAM: An approach for assigning bug reports using their Metadata

Shadi Banitaan; Mamdouh Alenezi; IEEE

doi:10.1109/ICCITechnology.2013.6579552

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Conference proceeding

TRAM: An approach for assigning bug reports using their Metadata

Shadi Banitaan, Mamdouh Alenezi and IEEE

2013 Third International Conference on Communications and Information Technology (ICCIT), pp.215-219

06/2013

DOI: https://doi.org/10.1109/ICCITechnology.2013.6579552

Abstract

Accuracy

bug triage

classification

Computer bugs

mining bug repositories

Predictive models

Software

Software engineering

term selection method

Training

Vectors

Bug triage is an essential phase in the bug fixing process. The aim of bug triage is to assign an experienced developer to a new coming bug report. Existing bug triage approaches are mainly based on machine learning techniques. These approaches suffer from low prediction accuracy. In this paper, we propose TRAM (TRiaging Approach using bug reports Metadata). The goal is to improve the prediction accuracy of bug triage by utilizing the most discriminating terms of bug reports, the components in which the bugs belong to, and the reporter who filed the bug.We perform experimental evaluation on open-source projects namely Freedesktop, NetBeans, Eclipse, and Firefox. The results show that TRAM outperforms existing machine learning-based approaches in terms of classification accuracy. TRAM improves the F-score by approximately 34%, 40%, 20%, and 21% for Freedesktop, NetBeans, Eclipse, and Firfox respectively.

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Title: TRAM: An approach for assigning bug reports using their Metadata
Creators - without role: Shadi Banitaan - University of Detroit Mercy
Mamdouh Alenezi - Prince Sultan University
IEEE
Publication Details: 2013 Third International Conference on Communications and Information Technology (ICCIT), pp.215-219
Publisher: IEEE
Identifiers: 9927400308331
Academic Unit: Prince Sultan University
Language: English
Resource Type: Conference proceeding