NDLI: An industrial case study of classifier ensembles for locating software defects

Content Provider	Springer Nature Link
Author	Mısırlı, Ayşe Tosun Bener, Ayşe Başar Turhan, Burak
Copyright Year	2011
Abstract	As the application layer in embedded systems dominates over the hardware, ensuring software quality becomes a real challenge. Software testing is the most time-consuming and costly project phase, specifically in the embedded software domain. Misclassifying a safe code as defective increases the cost of projects, and hence leads to low margins. In this research, we present a defect prediction model based on an ensemble of classifiers. We have collaborated with an industrial partner from the embedded systems domain. We use our generic defect prediction models with data coming from embedded projects. The embedded systems domain is similar to mission critical software so that the goal is to catch as many defects as possible. Therefore, the expectation from a predictor is to get very high probability of detection (pd). On the other hand, most embedded systems in practice are commercial products, and companies would like to lower their costs to remain competitive in their market by keeping their false alarm (pf) rates as low as possible and improving their precision rates. In our experiments, we used data collected from our industry partners as well as publicly available data. Our results reveal that ensemble of classifiers significantly decreases pf down to 15% while increasing precision by 43% and hence, keeping balance rates at 74%. The cost-benefit analysis of the proposed model shows that it is enough to inspect 23% of the code on local datasets to detect around 70% of defects.
Starting Page	515
Ending Page	536
Page Count	22
File Format	PDF
ISSN	09639314
Journal	Software Quality Journal
Volume Number	19
Issue Number	3
e-ISSN	15731367
Language	English
Publisher	Springer US
Publisher Date	2011-01-13
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Defect prediction Ensemble of classifiers Static code attributes Embedded software Programming Languages, Compilers, Interpreters Software Engineering/Programming and Operating Systems Operating Systems Data Structures, Cryptology and Information Theory
Content Type	Text
Resource Type	Article
Subject	Safety, Risk, Reliability and Quality Media Technology Software

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