Toward comprehensible software defect prediction models using fuzzy logic

Hamdi A. Al-Jamimi

doi:10.1109/ICSESS.2016.7883031

Toward comprehensible software defect prediction models using fuzzy logic

Hamdi A. Al-Jamimi^*

^*Corresponding author for this work

Vice President for Research and Innovation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Scopus citations

Abstract

Software defect prediction is a discipline that predicts the defects proneness of future modules. Software metrics are used for this kind of predication. However, the predication metrics are associated with uncertainty, thus the metrics need to be expressed in linguistic terms to overcome ambiguity and uncertainty. Two types of knowledge are utilized as input to the prediction models: software metrics and expert's opinions. This paper proposes a framework for developing fuzzy logic-based software predication model using different set of software metrics. It aims to provide a generic set of metrics to be used for software defects prediction. The performance of the proposed Fuzzy-based models has been validated using real software projects data where Takagi-Sugeno fuzzy inference engine is used to predict software defects. Validation results are satisfactory.

Original language	English
Title of host publication	ICSESS 2016 - Proceedings of 2016 IEEE 7th International Conference on Software Engineering and Service Science
Editors	M. Surendra Prasad Babu, Li Wenzheng
Publisher	IEEE Computer Society
Pages	127-130
Number of pages	4
ISBN (Electronic)	9781467399036
DOIs	https://doi.org/10.1109/ICSESS.2016.7883031
State	Published - 2 Jul 2016

Publication series

Name	Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
Volume	0
ISSN (Print)	2327-0586
ISSN (Electronic)	2327-0594

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Defect Density
Fuzzy Inference System
Software Defect Prediction
Software Metrics

ASJC Scopus subject areas

Software

Access to Document

10.1109/ICSESS.2016.7883031

Cite this

Al-Jamimi, H. A. (2016). Toward comprehensible software defect prediction models using fuzzy logic. In M. S. P. Babu, & L. Wenzheng (Eds.), ICSESS 2016 - Proceedings of 2016 IEEE 7th International Conference on Software Engineering and Service Science (pp. 127-130). Article 7883031 (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS; Vol. 0). IEEE Computer Society. https://doi.org/10.1109/ICSESS.2016.7883031

Al-Jamimi, Hamdi A. / Toward comprehensible software defect prediction models using fuzzy logic. ICSESS 2016 - Proceedings of 2016 IEEE 7th International Conference on Software Engineering and Service Science. editor / M. Surendra Prasad Babu ; Li Wenzheng. IEEE Computer Society, 2016. pp. 127-130 (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS).

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abstract = "Software defect prediction is a discipline that predicts the defects proneness of future modules. Software metrics are used for this kind of predication. However, the predication metrics are associated with uncertainty, thus the metrics need to be expressed in linguistic terms to overcome ambiguity and uncertainty. Two types of knowledge are utilized as input to the prediction models: software metrics and expert's opinions. This paper proposes a framework for developing fuzzy logic-based software predication model using different set of software metrics. It aims to provide a generic set of metrics to be used for software defects prediction. The performance of the proposed Fuzzy-based models has been validated using real software projects data where Takagi-Sugeno fuzzy inference engine is used to predict software defects. Validation results are satisfactory.",

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Al-Jamimi, HA 2016, Toward comprehensible software defect prediction models using fuzzy logic. in MSP Babu & L Wenzheng (eds), ICSESS 2016 - Proceedings of 2016 IEEE 7th International Conference on Software Engineering and Service Science., 7883031, Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS, vol. 0, IEEE Computer Society, pp. 127-130. https://doi.org/10.1109/ICSESS.2016.7883031

Toward comprehensible software defect prediction models using fuzzy logic. / Al-Jamimi, Hamdi A.
ICSESS 2016 - Proceedings of 2016 IEEE 7th International Conference on Software Engineering and Service Science. ed. / M. Surendra Prasad Babu; Li Wenzheng. IEEE Computer Society, 2016. p. 127-130 7883031 (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS; Vol. 0).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Al-Jamimi HA. Toward comprehensible software defect prediction models using fuzzy logic. In Babu MSP, Wenzheng L, editors, ICSESS 2016 - Proceedings of 2016 IEEE 7th International Conference on Software Engineering and Service Science. IEEE Computer Society. 2016. p. 127-130. 7883031. (Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS). doi: 10.1109/ICSESS.2016.7883031

Toward comprehensible software defect prediction models using fuzzy logic

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this