Who should fix this bug?

By John Anvik, Lyndon Hiew, Gail C. Murphy. International Conference on Software Engineering, 2006

1,112 citations recorded by the source corpus.

Subfields: Information Systems, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/b3b3c562a45d7710d6f62ad8f210ebca9a47d23f

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In Information Systems

In Information Systems and Management

Citations in the corpus

AR-miner: mining informative reviews for developers from mobile app marketplace (2014, background): “In this section, we first give an overview of our proposed AR-Miner framework to address the problem stated in Section 3, and then present each step of our framework in detail.”
A Hidden Markov Model to detect coded information islands in free text (2013, background): “Traceability recovery [6], impact analysis [9], bug report assignment [10], [11], code/text summarization [12], [13] are approaches that could benefit from methods that are able to discriminate noisy data and relevant information.”
A systematic study of automated program repair: Fixing 55 out of 105 bugs for $8 each (2012, background): “Developers for large software projects must confirm, triage, and localize defects before fixing them and validating the fixes.”
The road ahead for Mining Software Repositories (2008, background): “Anvik and Murphy speed up the bug triage efforts by using prior bug reports to determine the most suitable developers to which a bug should be assigned [ 5 ].”
Improving bug triage with bug tossing graphs (2009, methodology): “To assign developers to bug reports, again several approaches used natural language processing [3, 5, 10, 13], however only with moderate success, about 5060% accuracy.”
An approach to detecting duplicate bug reports using natural language and execution information (2008, background): “Second, it helps the software evolve according to users' requests, and meet the requirements of more users 1 [1].”
It's not a bug, it's a feature: How misclassification impacts bug prediction (2013, methodology): “But bug fixes have also been used to estimate development efforts [19], [20], [21], [22], bug triage [23], [24] or automatic bug assignment [25], [26].”
Duplicate bug reports considered harmful … really? (2008, methodology): “To test hypothesis H2, we build prediction models for automate bug triaging [2] and compare the results of models trained with and without duplicate reports (Section 5).”
Automated duplicate detection for bug tracking systems (2008, background): “Previous studies report that as many as 36% of bug reports were duplicates or otherwise invalid [2].”
Modeling bug report quality (2007, methodology): “Previous studies have found that as many as 36% of bug reports were duplicates or otherwise invalid [3].”
How Long Will It Take to Fix This Bug? (2007, neutral): “[2], which in part motivated this research.”
Easy over hard: a case study on deep learning (2017, background): “) how long it will take to integrate the new code [17], where bugs are most likely to occur [54], who should fix the bug [2], or how long it will take to develop their code [34, 35, 50].”
Towards more accurate retrieval of duplicate bug reports (2011, methodology): “[15], Cubranic and Murphy [16], Pordguski et al [17], and Francis et al.”
Where should the bugs be fixed? More accurate information retrieval-based bug localization based on bug reports (2012, background): “Many researchers mine bug report information to solve software engineering problems such as duplicate bug detection [33, 35], automatic bug triage [4, 7], bug report quality analysis [6, 7], and defect prediction [20, 37].”
An exploratory study of the pull-based software development model (2014, methodology): “The feature selection was based on prior work in the areas of patch submission and acceptance [24, 4, 32, 3], code reviewing [28], bug triaging [1, 14] and also on semistructured interviews of Github developers [9, 26, 22].”
The impact of tangled code changes (2013, background): “Such mined information can be used to predict related changes [1], to predict future defects [2], [3], to analyze who should be assigned a particular task [4], [5], or to gain insights about specific projects [6].”
Global Software Engineering: The Future of Socio-technical Coordination (2007, positive): “Anvik and colleagues [2] use machine-learning techniques in the design of a tool that uses past history of bug fixes to assist open source bug triagers identify appropriate developers for fixing an incoming bug.”