NDLI: A semiautomated method for classifying program analysis rules into a quality model

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A semiautomated method for classifying program analysis rules into a quality model

Content Provider	ACM Digital Library
Author	Gupta, Shrinath Singh, Himanshu Kumar
Abstract	Most of the software code quality assessment and monitoring methods uses Quality Model (QM) as an aid to capture quality requirements of the software. An important aspect concerning use of QM is classification of Program Analysis (PA) rules into QM according to their relevance to quality attributes such as maintainability, reliability etc. Currently such classification is performed manually by experts and most of the PA tools (such as FxCop for C#, FindBugs for Java, PC-Lint for C/C++) support hundreds of PA rules. Hence performing classification manually can be very effort intensive and time consuming and can lead to concerns like subjectivity and inconsistency. Hence we propose a light weight semiautomated method to expedite classification and make classification activity less effort intensive. Proposed classifier is based on natural language processing (NLP) techniques and uses a keyword matching algorithm. We have computed precision and recall for such a classifier. We have also shown results from applying technique on classifying rules from FxCop, PC-Lint, and FindBugs into the EMISQ QM. We believe that proposed approach will significantly help in reducing the time required to perform classification and hence also to incorporate newer PA tools and rules into QM based methods. .
Starting Page	266
Ending Page	270
Page Count	5
File Format	PDF
ISBN	9781450328791
DOI	10.1145/2597008.2597808
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-06-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Code analysis Classification Software quality Quality requirements Program analysis Quality model
Content Type	Text
Resource Type	Article

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