An Application of a rule-based model in software quality classification

Proceedings - 6th International Conference on Machine Learning and Applications, ICMLA 2007

Volumn , Issue , 2007, Pages 204-210

  Bullard, Lofton A ^a   Khoshgoftaar, Taghi M ^a   Kehan, Gao ^b  

^a FLORIDA ATLANTIC UNIVERSITY   (United States)

^b EASTERN CONNECTICUT STATE UNIVERSITY   (United States)

Author keywords

Discretization; Reducts; Rough set; Rule based classification model; Software quality classification

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); COMPUTER SOFTWARE SELECTION AND EVALUATION; DECISION THEORY; FUZZY SETS; LEAD; LEARNING SYSTEMS; PARTITIONS (BUILDING); ROBOT LEARNING; SET THEORY; TELECOMMUNICATION SYSTEMS; TELEPHONE SYSTEMS;

ATTRIBUTE VALUES; BOOLEAN PREDICATES; CASE STUDIES; CLASSIFICATION ERRORS; CLASSIFICATION MODELS; DECISION RULES; EMPIRICAL VALIDATION; INTERNATIONAL CONFERENCES; MACHINE-LEARNING; MODEL SELECTIONS; NEW MODEL; OVER-FITTING; ROUGH SETS; RULE BASED CLASSIFICATION; RULE-BASED; SOFTWARE QUALITY CLASSIFICATION;

ROUGH SET THEORY;

EID: 47349111697     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2007.14     Document Type: Conference Paper

References (19)

1. V. R. Basili, L. C. Briand, and W. L. Melo. A validation of object-oriented design metrics as quality indicators. IEEE Transactions on Software Engineering, 22(10):751-761, October 1996.
2. J. G. Bazan, M. S. Szczuka, and J. Wroblewski. A new version of rough set exploration system. In J. J. A. et. al., editor, Rough Sets and Current Trends in Computing, Third International Conference, RSCTC 2002, Proceedings, pages 397-404, Malvern, PA, USA, October 14-16 2002.
3. C. Ebert. Classification techniques for metric-based software development. Software Quality Journal, 5(4):255-272, December 1996.
4. G. R. Finnie, G. E. Wittig, and J. M. Desharnais. A comparison of software effort estimation techniques: Using function points with neural networks, case-based reasoning, and regression models. Journal of Systems and Software, 39:281-289, 1997.
5. N. S. Hoa and N. H. Son. Discretization methods in data mining. In Rough Sets in Knowledge Discovery 1, pages 451-482. Physica-Verlag, 1998.
6. T. M. Khoshgoftaar and E. B. Allen. Logistic regression modeling of software quality. International Journal of Reliability, Quality and Safety Engineering, 6(4):303-317, December 1999.
7. T. M. Khoshgoftaar, E. B. Allen, and J. Deng. Using regression trees to classify fault-prone software modules. IEEE Transactions on Reliability, 51(4):455-462, December 2002.
8. T. M. Khoshgoftaar and N. Seliya. Analogy-based practical classification rules for software quality estimation. Empirical Software Engineering Journal, 8(4):325-350, December 2003.
9. J. Komorowski, L. Polkowski, and A. Skowron. Rough sets: a tutorial. Springer-Verlag, 1998.
10. C. Mair, G. Kadoda, M. Lefley, K. Phalp, C. Schofield, M. Shepperd, and S. Webster. An investigation of machine learning based prediction systems. Journal of Systems and Software, 53(1):23-29, 2000.
11. M. Mao. Software quality classification using rule-based modeling. Master's thesis, Florida Atlantic University, Boca Raton, FL, USA, May 2002. Advised by Taghi M. Khoshgoftaar.
12. J. C. Munson and T. M. Khoshgoftaar. The detection of fault-prone programs. IEEE Transactions on Software Engineering, 18(5):423-433, May 1992.
13. S. H. Nguyen, A. Skowron, and P. Synak. Discovery of data patterns with applications to decomposition and classification problems. In L. Polkowski and A. Skowron, editors, Rough Sets in Knowledge Discovery 2: Applications, Case Studies and Software Systems, volume 19 of Studies in Fuzziness and Soft Computing, chapter 4, pages 55-97. Physica-Verlag, Heidelberg, Germany, 1998.
14. Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic, 1992.
15. N. Shan and W. Ziarko. Data-based acqusition and incremental modification of classification rules. In Computational Intelligence, pages 357-370, 1995.
16. A. Skowron. Extracting laws from decision tables: A rough set approach. In Computational Intelligence, volume 11, pages 371-387, 1995.
17. D. Slezak and J. Wroblewski. Covering with reducts - a fast algorithm for rule generation. In Proceedings: RSCTC, volume 1424, pages 402-407. Springer Verlag, 1998.
18. Z. Xu, T. M. Khoshgoftaar, and E. B. Allen. Application of fuzzy expert systems in assessing operational risk of software. Information and Software Technology Journal, 45(7):373-388, May 2003.
19. S. Zhong, T. M. Khoshgoftaar, and N. Seliya. Analyzing software measurement data with clustering techniques. IEEE Intelligent Systems, 19(2):20-27, 2004.