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

delete2015-12-02
delete70
PRE
AI
R
Robert Dyer *
H
Hoan Anh Nguyen
H
Hridesh Rajan
T
Tien N. Nguyen
DOI:10.1145/2803171delete
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摘要

摘要

En 中文
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.
Keyword:
Boa
mining software repositories
domain-specific language
scalable
ease of use
lower barrier to entry
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期刊

A
ACM Transactions on Software Engineering and Methodology
IF:
6.2
论文数:
1.2K
被引数:
3.4K

机构

U
University System of Ohio
学者数:
15.4W
论文数: 13.0W
被引数: 200
B
Bowling Green State University
学者数:
1.2K
论文数: 961
被引数: 2.2K
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