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Classification of software quality with tree modeling using C4.5 algorithm

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Date Issued:
2001
Summary:
Developing highly reliable software is a must in today's competitive environment. However quality control is a costly and time consuming process. If the quality of software modules being developed can be predicted early in their life cycle, resources can be effectively allocated improving quality, reducing cost and development time. This study examines the C4.5 algorithm as a tool for building classification trees, classifying software module either as fault-prone or not fault-prone. The classification tree models were developed based on four consecutive releases of a very large legacy telecommunication system. The first two releases were used as training data sets and the subsequent two releases were used as test data sets to evaluate the model. We found out that C4.5 was able to build compact classification trees models with balanced misclassification rates.
Title: Classification of software quality with tree modeling using C4.5 algorithm.
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Name(s): Ponnuswamy, Viswanathan Kolathupalayam.
Florida Atlantic University, Degree grantor
Khoshgoftaar, Taghi M., Thesis advisor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2001
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 134 p.
Language(s): English
Summary: Developing highly reliable software is a must in today's competitive environment. However quality control is a costly and time consuming process. If the quality of software modules being developed can be predicted early in their life cycle, resources can be effectively allocated improving quality, reducing cost and development time. This study examines the C4.5 algorithm as a tool for building classification trees, classifying software module either as fault-prone or not fault-prone. The classification tree models were developed based on four consecutive releases of a very large legacy telecommunication system. The first two releases were used as training data sets and the subsequent two releases were used as test data sets to evaluate the model. We found out that C4.5 was able to build compact classification trees models with balanced misclassification rates.
Identifier: 9780493418179 (isbn), 12855 (digitool), FADT12855 (IID), fau:9729 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 2001.
Subject(s): Computer software--Quality control
Software measurement
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/12855
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.