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Physical Sciences and Mathematics Commons

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Selected Works

David LO

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Articles 1 - 3 of 3

Full-Text Articles in Physical Sciences and Mathematics

Multi-Abstraction Concern Localization, Tien-Duy B. Duy, Shaowei Wang, David Lo Jun 2014

Multi-Abstraction Concern Localization, Tien-Duy B. Duy, Shaowei Wang, David Lo

David LO

Concern localization refers to the process of locating code units that match a particular textual description. It takes as input textual documents such as bug reports and feature requests and outputs a list of candidate code units that need to be changed to address the bug reports or feature requests. Many information retrieval (IR) based concern localization techniques have been proposed in the literature. These techniques typically represent code units and textual descriptions as a bag of tokens at one level of abstraction, e.g., each token is a word, or each token is a topic. In this work, we propose …


Accurate Developer Recommendation For Bug Resolution, Xin Xia, David Lo, Xinyu Wang, Bo Zhou Jun 2014

Accurate Developer Recommendation For Bug Resolution, Xin Xia, David Lo, Xinyu Wang, Bo Zhou

David LO

Bug resolution refers to the activity that developers perform to diagnose, fix, test, and document bugs during software development and maintenance. It is a collaborative activity among developers who contribute their knowledge, ideas, and expertise to resolve bugs. Given a bug report, we would like to recommend the set of bug resolvers that could potentially contribute their knowledge to fix it. We refer to this problem as developer recommendation for bug resolution. In this paper, we propose a new and accurate method named DevRec for the developer recommendation problem. DevRec is a composite method which performs two kinds of analysis: …


Duplicate Bug Report Detection With A Combination Of Information Retrieval And Topic Modeling, Anh Tuan Nguyen, Tung Nguyen, Tien Nguyen, David Lo, Chengnian Sun Dec 2012

Duplicate Bug Report Detection With A Combination Of Information Retrieval And Topic Modeling, Anh Tuan Nguyen, Tung Nguyen, Tien Nguyen, David Lo, Chengnian Sun

David LO

Detecting duplicate bug reports helps reduce triaging efforts and save time for developers in fixing the same issues. Among several automated detection approaches, text-based information retrieval (IR) approaches have been shown to outperform others in term of both accuracy and time efficiency. However, those IR-based approaches do not detect well the duplicate reports on the same technical issues written in different descriptive terms. This paper introduces DBTM, a duplicate bug report detection approach that takes advantage of both IR-based features and topic-based features. DBTM models a bug report as a textual document describing certain technical issue(s), and models duplicate bug …