A classification scheme for studies on fault-prone components

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2188, Issue , 2001, Pages 341-355

  Runeson, Per ^a   Ohlsson, Magnus C ^a   Wohlin, Claes ^b  

^a LUND UNIVERSITY   (Sweden)

^b BLEKINGE INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

KNOWLEDGE BASED SYSTEMS; SOFTWARE ENGINEERING;

CLASSIFICATION EFFICIENCY; CLASSIFICATION SCHEME; EVALUATION SCHEME; FAULT-PRONE COMPONENTS; KNOWLEDGE BASE; MISCLASSIFICATIONS;

CLASSIFICATION (OF INFORMATION);

EID: 84977534564     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44813-6_29     Document Type: Conference Paper

References (14)

1. Briand, L.C., Basili, V.R. and Hetmanski, C.J., “Developing Interpretable Models with Optimized Set Reduction for Identifying High-Risk Software Components”, IEEE Transactions on Software Engineering, 19(11), 1993, 1028–1044.
2. Khoshgoftaar, T.M and Lanning, D.L, “A Neural Network Approach for Early Detection of Program Modules Having High Risk in the Maintenance Phase”, Journal of Systems and Software, 29(1), 1995, 85–91.
3. Khoshgoftaar, T.M., Allen, E.B., Kalaichelvan, K.S and Goel, N., “Early Quality Prediction: A Case Study in Telecommunications”, IEEE Software (January 1996), 65–71.
4. Khoshgoftaar, T.M, Allen, E.B., Halstead, R. and Trio, G.P., “Detection of Fault-prone Software Modules During a Spiral Life Cycle”, Proceedings of the International Conference on Software Maintenance, (Monterey, California, USA, November 96) 69-76.
5. Ohlsson, N., Helander, M. and Wohlin, C., “Quality Improvement by Identification of Fault-Prone Modules using Software Design Metrics”, In Proceedings Sixth International Conference on Software Quality, (Ottawa, Ontario, Canada, 1996), 1–13.
6. Ohlsson, N. and Alberg, H., “Predicting Fault-Prone Software Modules in Telephone Switches”, IEEE Transactions on Software Engineering, 22(12), 1996, 886–894.
7. Ohlsson, N. and Wohlin, C., “Experiences of Fault Data in a Large Software System”, Information Technology Management: An International Journal, 2(4), 1998, 163–171.
8. Schneidewind, N. F., “Software Metrics Model for Integrating Quality Control and Prediction”, in Proceedings Fourth International Software Metrics Symposium, (Albuquerque, NM, USA, November 1997) 402–415.
9. Zhao, Ming, Wohlin, C., Ohlsson, N. and Xie, Min, “A Comparison between Software Design and Code Metrics for the Prediction of Software Fault Content”, Information and Software Technology, 40(14), 1998, 801–809.
10. Khoshgoftaar, T.M. and Allen, E.B., “The Impact of Cost of Misclassification on Software Quality Modeling”, in Proceedings Fourth International Software Metrics Symposium, (Albuquerque, NM, USA, November 1997), 54–62.
11. Fenton, N.E. and Pfleeger, S.L., Software Metrics: A Rigorous and Practical Approach, Thomson Computer Press, 1996.
12. Ohlsson, M.C. and Wohlin, C., “Identification of Green, Yellow and Red Legacy Components”, In Proceeding of International Conference on Software Maintenance, (Bethesda, Washington D.C, USA, November 1998), 6–15.
13. ITU, “Recommendation Z.100: SDL – Specification and Description Language”, 1988.
14. McCabe, T. J., “A Complexity Measure”, IEEE Transactions on Software Engineering, 4(2), 1976, 308–320.