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Journal of Software Engineering
  Year: 2011 | Volume: 5 | Issue: 2 | Page No.: 64-77
DOI: 10.3923/jse.2011.64.77
A Framework for Automatically Mining Source Code
Shaheen Khatoon, Guohui Li and Rana Muhammad Ashfaq

Abstract:
Mining source code by using different data mining techniques to extract the informative patterns like programming rules, variable correlation, code clones and frequent API usage is an active area of research. However, no practical framework for integrating these tasks has been attempted. To achieve this objective an integrated framework is designed that can detect different types of bugs to achieve software quality and assist developer in reusing API libraries for rapid software development. Proposed framework automatically extracts large variety of programming patterns and finds the locations where the extracted patterns are violated. Violated patterns are reported as programming rule violation, copy paste code related bugs and inconsistent variable update bugs. Although, the bugs are different but the framework can detect these bugs in one pass and produces higher quality software systems within budget. The framework also helps in code reusing by suggesting the programmer how to write API code to facilitate rapid software development. Proposed framework is validated by developing a prototype that developed in C# (MS Visual Studio, 2008) and evaluated on large application like ERP. Results shows proposed technique greatly reduced time and cost of manually checking defects from source code by programmers.
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How to cite this article:

Shaheen Khatoon, Guohui Li and Rana Muhammad Ashfaq, 2011. A Framework for Automatically Mining Source Code. Journal of Software Engineering, 5: 64-77.

DOI: 10.3923/jse.2011.64.77

URL: https://scialert.net/abstract/?doi=jse.2011.64.77

 
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