Building high-quality software fault predictors

Software - Practice and Experience

Volumn 36, Issue 9, 2006, Pages 949-969

  Nikora, Allen P ^a   Munson, John C ^b  

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^b University of Idaho   (United States)

Author keywords

Software fault modeling; Software measurement

Indexed keywords

CODES (SYMBOLS); COMPUTER SCIENCE; COMPUTER SOFTWARE; MATHEMATICAL MODELS; SOFTWARE ENGINEERING; STANDARDIZATION;

FAULT-COUNTING TECHNIQUE; JET PROPULSION LABORATORY; SOFTWARE FAULT MODELING; SOFTWARE MEASUREMENT;

FAULT TOLERANT COMPUTER SYSTEMS;

EID: 33746255379     PISSN: 00380644     EISSN: 1097024X     Source Type: Journal    
DOI: 10.1002/spe.737     Document Type: Conference Paper

References (24)

1. Munson J, Nikora A. Estimating rates of fault insertion and test effectiveness in software systems. Proceedings of the 4th ISSAT International Conference on Reliability and Quality in Design, August 1998. International Society of Science and Applied Technologies: New Brunswick, NJ, 1998; 263-269.
2. Nikora A, Munson J. Determining fault insertion rates for evolving software systems. Proceedings of the 1998 IEEE International Symposium of Software Reliability Engineering, Paderborn, November 1998. IEEE Press: Piscataway, NJ, 1988; 306-315.
3. Nikora A, Munson J. Developing fault predictors for evolving software systems. Proceedings of the 9th International Software Metrics Symposium, Sydney, September 2003. IEEE Press: Piscataway, NJ, 2003; 338-350.
4. Munson J, Nikora A. Toward a quantifiable definition of software faults. Proceedings of the 13th IEEE International Symposium on Software Reliability Engineering, Annapolis, MD, November 2002. IEEE Press: Piscataway, NJ, 2002; 388-395.
5. Dvorak D, Rasmussen R, Reeves G, Sacks A. Software architecture themes in JPL's mission data system. AIAA Space Technology Conference and Exposition, Albuquerque, NM, September 1999. American Institute of Aeronautics and Astronautics: Reston, VA, 1999.
6. Khoshgoftaar T, Allen E. Modeling software quality with classification trees. Recent Advances in Reliability and Quality Engineering (Lecture Notes in Computer Science, vol. 1845), ch. 15, Pham H (ed.). World Scientific: Singapore, 2001; 247-270.
7. Gokhale S, Lyu M. Regression tree modeling for the prediction of software quality. Proceedings of the 3rd ISSAT International Conference on Reliability and Quality in Design, Anaheim, CA, March 1997. International Society of Science and Applied Technologies: New Brunswick, NJ, 1997; 31-36.
8. Schneidewind N. Software metrics model for integrating quality control and prediction. Proceedings of the 8th International Symposium on Software Reliability Engineering, Albuquerque, NM, November 1997. IEEE Press: Piscataway, NJ, 1997; 402-415.
9. Khoshgoftaar T. An application of zero-inflated poisson regression for software fault prediction. Proceedings of the 12th International Symposium on Software Reliability Engineering, Hong Kong, November 2001. IEEE Press: Piscataway, NJ, 2001; 66-73.
10. Schneidewind N. Investigation of logistic regression as a discriminant of software quality. Proceedings of the 7th International Software Metrics Symposium, London, April 2001. IEEE Press: Piscataway, NJ, 2001; 328-337.
11. IEEE Standard Glossary of Software Engineering Terminology. IEEE Std 729-1983, Institute of Electrical and Electronics Engineers, 1983.
12. IEEE Standard Dictionary of Measures to Produce Reliable Software. IEEE Std 982.1-1988, Institute of Electrical and Electronics Engineers, 1989.
13. Nikora A, Munson J. Finding fault with faults: A case study, with J. Munson. Proceedings of the Annual Oregon Workshop on Software Metrics, Coeur d'Alene, ID, May 1997. OCATE: Portland State University, Portland, OR, 1997.
14. The Darwin software engineering measurement appliance, Cylant Technology, 2000.
15. Munson J. Software Engineering Measurement. CRC Press: Boca Raton, FL, 2002.
16. Munson J, Khoshgoftaar T. Regression modeling of software quality. Information and Software Technology 1990; 32(2): 105-114.
17. Hall G, Munson J. Software evolution: Code delta and code churn. Journal of Systems and Software 2000; 54(2):111-118.
18. Dillon W, Goldstein M. Multivariate Analysis: Methods and Applications. Wiley Interscience: New York, 1984.
19. Ximbiot. CVS-Concurrent Versions System v. 1.11.21. http://ximbiot.com/ cvs/manual/cvs-1.11.21/cvs.html [10 March 2006].
20. Nikora A, Munson J. Understanding the nature of software evolution. Proceedings of the International Conference on Software Maintenance, Amsterdam, September 2003. IEEE Press: Piscataway, NJ, 2003; 83-93.
21. Computer Associates. AllFusion Harvest Change Manager Features, Descriptions & Benefits. http://www3.ca.com/Files/FactSheet/ af_harvest_cm_fdb.pdf [11 February 2002].
22. Boehm B. Software Engineering Economics. Prentice-Hall: Englewood Cliffs, NJ, 1981.
23. Brants T. TnT-a statistical part-of-speech tagger. Proceedings of the Sixth Applied Natural Language Processing Conference ANLP-2000, Seattle, WA, April 2000. Association for Computational Linguistics: East Stroudsburg, PA, 2000; 224-231.
24. Santorini B. Part-of-speech tagging guidelines for the penn treebank project (3rd revision, 2nd printing). http://www.cis.upenn.edu/~treebank/home. html [February 1995].