research-article

Boa: Ultra-Large-Scale Software Repository and Source-Code Mining

Authors:

Hoan Anh Nguyen,

Tien N. NguyenAuthors Info & Claims

ACM Transactions on Software Engineering and Methodology (TOSEM), Volume 25, Issue 1

Article No.: 7, Pages 1 - 34

https://doi.org/10.1145/2803171

Published: 02 December 2015 Publication History

Abstract

In today's software-centric world, ultra-large-scale software repositories, such as SourceForge, GitHub, and Google Code, are the new library of Alexandria. They contain an enormous corpus of software and related information. Scientists and engineers alike are interested in analyzing this wealth of information. However, systematic extraction and analysis of relevant data from these repositories for testing hypotheses is hard, and best left for mining software repository (MSR) experts! Specifically, mining source code yields significant insights into software development artifacts and processes. Unfortunately, mining source code at a large scale remains a difficult task. Previous approaches had to either limit the scope of the projects studied, limit the scope of the mining task to be more coarse grained, or sacrifice studying the history of the code. In this article we address mining source code: (a) at a very large scale; (b) at a fine-grained level of detail; and (c) with full history information. To address these challenges, we present domain-specific language features for source-code mining in our language and infrastructure called Boa. The goal of Boa is to ease testing MSR-related hypotheses. Our evaluation demonstrates that Boa substantially reduces programming efforts, thus lowering the barrier to entry. We also show drastic improvements in scalability.

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Index Terms

Boa: Ultra-Large-Scale Software Repository and Source-Code Mining
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language features
        Concurrent programming structures
        Patterns

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Published In

cover image ACM Transactions on Software Engineering and Methodology

ACM Transactions on Software Engineering and Methodology Volume 25, Issue 1

December 2015

339 pages

ISSN:1049-331X

EISSN:1557-7392

DOI:10.1145/2852270

Editor:
David S. Rosenblum
National University of Singapore, Singapore

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Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 02 December 2015

Accepted: 01 July 2015

Revised: 01 June 2014

Received: 01 January 2014

Published in TOSEM Volume 25, Issue 1

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https://dl.acm.org/doi/10.1145/3639478.3640026
Kessel MAtkinson C(2024)Code search engines for the next generationJournal of Systems and Software10.1016/j.jss.2024.112065215(112065)Online publication date: Sep-2024
https://doi.org/10.1016/j.jss.2024.112065
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https://dl.acm.org/doi/10.1016/j.jss.2024.111971
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