Prediction of Software Quality Model Using Gene Expression Programming
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- @InProceedings{conf/profes/SinghKM09,
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title = "Prediction of Software Quality Model Using Gene
Expression Programming",
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author = "Yogesh Singh and Arvinder Kaur and Ruchika Malhotra",
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booktitle = "10th International Conference on Product-Focused
Software Process Improvement, PROFES 2009",
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year = "2009",
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editor = "Frank Bomarius and Markku Oivo and
P{\"a}ivi Jaring and Pekka Abrahamsson",
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volume = "32",
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series = "Lecture Notes in Business Information Processing",
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pages = "43--58",
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address = "Oulu, Finland",
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month = jun # " 15-17",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, gene
expression programming",
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bibdate = "2009-06-24",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/profes/profes2009.html#SinghKM09",
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isbn13 = "978-3-642-02151-0",
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DOI = "doi:10.1007/978-3-642-02152-7_5",
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abstract = "There has been number of measurement techniques
proposed in the literature. These metrics can be used
in assessing quality of software products, thereby
controlling costs and schedules. The empirical
validation of object-oriented (OO) metrics is essential
to ensure their practical relevance in industrial
settings. In this paper, we empirically validate OO
metrics given by Chidamber and Kemerer for their
ability to predict software quality in terms of fault
proneness. In order to analyze these metrics we use
gene expression programming (GEP). Here, we explore the
ability of OO metrics using defect data for open source
software. Further, we develop a software quality metric
and suggest ways in which software professional may use
this metric for process improvement. We conclude that
GEP can be used in detecting fault prone classes. We
also conclude that the proposed metric may be
effectively used by software managers tin predicting
faulty classes in earlier phases of software
development.",
- }
Genetic Programming entries for
Yogesh Singh
Arvinder Kaur
Ruchika Malhotra
Citations