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Analyzing ultra-large-scale code corpus with boa

Published: 19 October 2012 Publication History

Abstract

Analyzing the wealth of information contained in software repositories requires significant expertise in mining techniques as well as a large infrastructure. In order to make this information more reachable for non-experts, we present the Boa language and infrastructure. Using Boa, these mining tasks are much simpler to write as the details are abstracted away. Boa programs also run on a distributed cluster to automatically provide massive parallelization to users and return results in minutes instead of potentially days.

References

[1]
Apache Software Foundation. Hadoop: Open source implementation of MapReduce. http://hadoop.apache.org/.
[2]
J. Dean and S. Ghemawat. MapReduce: simplified data processing on large clusters. In Proceedings of the 6th Symposium on Opearting Systems Design & Implementation - Volume 6, OSDI'04, 2004.
[3]
R. Pike, S. Dorward, R. Griesemer, and S. Quinlan. Interpreting the data: Parallel analysis with Sawzall. Sci. Program., 13(4):277--298, 2005.
[4]
A. Urso. Sizzle: A compiler and runtime for Sawzall, optimized for Hadoop. https://github.com/anthonyu/Sizzle.

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Published In

cover image ACM Conferences
SPLASH '12: Proceedings of the 3rd annual conference on Systems, programming, and applications: software for humanity
October 2012
252 pages
ISBN:9781450315630
DOI:10.1145/2384716

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 October 2012

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  1. mapreduce
  2. software repository mining

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