DocumentCode
525635
Title
Evaluating software reliability: Integration of MCDM and data mining
Author
Peng, Yi ; Kou, Gang ; Wang, Honggang ; Wu, Wenshuai ; Honggang Wang
Author_Institution
Sch. of Manage. & Econ., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear
2010
fDate
23-25 June 2010
Firstpage
613
Lastpage
617
Abstract
Although software reliability can be evaluated by applying data mining techniques in software engineering data to identify software defects or faults, it is difficult to select the best algorithm among the numerous data mining techniques. The goal of this paper is to propose a multiple criteria decision making (MCDM) framework for data mining algorithms selection in software reliability management. Through the application of MCDM method, this paper compares experimentally the performance of several popular data mining algorithms using 13 different performance metrics over 10 public domain software defect datasets from the NASA Metrics Data Program (MDP) repository. The results of the MCDM methods agree on top-ranked classification algorithms and differ about some classifiers for software defect datasets.
Keywords
data mining; decision making; fault tolerant computing; pattern classification; software reliability; MCDM method; classification algorithms; data mining; multiple criteria decision making; public domain software defect datasets; software defects identification; software engineering data; software faults identification; software reliability evaluation; Application software; Data mining; Decision making; Fault diagnosis; Measurement; NASA; Software algorithms; Software engineering; Software performance; Software reliability; classification algorithm; knowledge-driven data mining; multiple criteria decision making (MCDM); software defect prediction; software reliability management;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-7324-3
Electronic_ISBN
978-89-88678-22-0
Type
conf
Filename
5542849
Link To Document