Combining abductive reasoning and inductive learning to evolve requirements specifications

IEE Proceedings: Software

Volumn 150, Issue 1, 2003, Pages 25-38

  D'Avila Garcez, A S ^a   Russo, A ^b   Nuseibeh, B ^c   Kramer, J ^b  

^a CITY UNIVERSITY   (United Kingdom)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c OPEN UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; CONTROL SYSTEM ANALYSIS; LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; PROGRAM DIAGNOSTICS;

ABDUCTIVE REASONING;

COMPUTER SOFTWARE;

EID: 0038059305     PISSN: 14625970     EISSN: None     Source Type: Journal    
DOI: 10.1049/ip-sen:20030207     Document Type: Conference Paper

References (50)

1. D'AVILA GARCEZ, A.S., RUSSO, A., NUSEIBEH, B., and KRAMER, J.: 'An analysis-revision cycle to evolve requirements specifications'. Proceedings of the 16th IEEE International Conference on Automated software engineering ASE01, San Diego, USA, November 2001, pp. 354-358
2. KAKAS, A.C., KOWALSKI, R.A., and TONI, F.: 'The role of abduction in logic programming' in GABBAY, D.M., HOGGER, C.J., and ROBINSON, J.A. (Eds.): 'Handbook of Logic in Artificial Intelligence and Logic Programming' (Oxford Science Publications, 1994) Vol. 5, pp. 235-324
3. MITCHELL, T.M.: 'Machine learning' (McGraw-Hill, 1997)
4. RUSSO, A., MILLER, R., NUSEIBEH, B., and KRAMER, J: 'An abductive approach for analysing event-based requirements specifications'. Technical report TR2001/7, Department of Computing, Imperial College, 2001
5. D'AVILA GARCEZ, A.S., and ZAVERUCHA, G.: 'The connectionist inductive learning and logic programming system', Appl. Intell. J., Special Issue on Neural Networks and Structured Knowledge, 1999, 11, (1), pp. 59-77
6. RUMELHART, D.E., HINTON, G.E., and WILLIAMS, R.J.: 'Learning internal representations by error propagation' in RUMELHART, D.E., and MCCLELLAND, J.L. (Eds.): 'Parallel Distributed Processing: Explorations in the Microstructure of Cognition' (MIT Press, 1986), Vol. 1, pp. 318-362
7. BHARADWAJ, R., and HEITMEYER, C.: 'Model checking complete requirements specifications using abstraction'. Technical report NRL-7999, Naval Research Lab, 1997
8. ALCHOURRON, C.A., GARDENFORS, P., and MAKINSON, D.: 'On the logic of theory change: partial meet contraction and revision functions', J. Symbol. Log., 1985, 50, pp. 510-530
9. FLACH, P.A., KAKAS, A.C.: 'On the relation between abduction and inductive learning' in GABBAY, D.M., and KRUSE, R. (Eds.): 'Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 4: Abductive Reasoning and Learning' 2000, pp. 1-33
10. ANDREWS, R., DIEDERICH, J., and TICKLE, A.B.: 'A survey and critique of techniques for extracting rules from trained artificial neural networks', Knowl.-Based Syst., 1995, 8, (6), pp. 373-389
11. D'AVILA GARCEZ, A.S., BRODA, K., and GABBAY, D.M.: 'Symbolic knowledge extraction from trained neural networks: A sound approach', Artif. Intell, 2001, 125, pp. 155-207
12. MCCLUSKEY, T.L., and WEST, M.M.: The automated refinement of a requirements domain theory', J. Autom. Softw. Eng., 2001, 8, (2), pp. 195-218, Special Issue on Inductive Programming
13. RUSSO, A., MILLER, R., NUSEIBEH, B., and KRAMER, J.: 'An abductive approach for handling inconsistencies in SCR specifications'. Proceedings of the 3rd ICSE Workshop on Intelligent software engineering, Limerick, June 2000
14. RUSSO, A., MILLER, R., NUSEIBEH, B., and KRAMER, J.: 'An abductive approach for analysing event-based requirements specifications'. Proceedings of 18th International Conference on Logic programming ICLP02, Copenhagen, Denmark, August 2002, pp. 22-37
15. MICHALSKI, R.S.: 'Learning strategies and automated knowledge acquisition', in 'Computational models of learning' (Springer-Verlag, Symbolic Computation, 1987)
16. HIRSH, H., and NOORDEWIER, M.: 'Using background knowledge to improve inductive learning: a case study in molecular biology', IEEE Expert, 1994, 10, pp. 3-6
17. LAVRAC, N., and DZEROSKI, S.: 'Inductive logic programming: techniques and applications' (Ellis Horwood, Series in Artificial Intelligence, 1994)
18. GAMBERGER, D., and LAVRAC, N.: 'Conditions for Occam's Razor applicability and noise elimination' in SOMEREN, M., and WIDMER, G. (Eds.): 'Proceedings of the European Conference on Machine learning', Prague, Czech Republic, April 1997, pp. 108-123
19. QUINLAN, J.R.: 'Induction of decision trees', Mach. Learn., 1986, 1, pp. 81-106
20. HAYKIN, S.: 'Neural networks: A comprehensive foundation' (Prentice Hall, 1999)
21. CLOETE, I., and ZURADA, J.M. (Eds.): 'Knowledge-based neurocomputing' (The MIT Press, 2000)
22. MUGGLETON, S., and RAEDT, L.: 'Inductive logic programming: theory and methods', J. Log. Program., 1994, 19, pp. 629-679
23. THRUN, S.B., BALA, J., BLOEDORN, E., BRATKO, I., CESTNIK, B., and CHENG, J., et al.: 'The MONK's problems: A performance comparison of different learning algorithms'. Technical Report CMU-CS-91-197, Carnegie Mellon University, 1991
24. D'AVILA GARCEZ, A.S., BRODA, K., and GABBAY, D.M.: 'Neural-symbolic learning systems: Foundations and applications'. Perspectives in Neural Computing (Springer-Verlag, 2002)
25. LLOYD, J.W.: 'Foundations of logic programming' (Springer-Verlag, 1987)
26. GELFOND, M., and LIFSCHITZ, V: 'The stable model semantics for logic programming'. Proceedings of the 5th Logic programming Symposium, Seattle, USA, August 1988, pp. 1070-1080
27. BOSE, N.K., and LIANG, P.: 'Neural networks fundamentals with graphs, algorithms, and applications' (McGraw-Hill, 1996)
28. KIRBY, J.: 'Example NRL/SCR software requirements for an automobile cruise control and monitoring system'. Technical Report TR-87-07, Wang Institute of Graduate Studies, 1987
29. SHAW, M.: 'Comparing architectural design styles', IEEE Softw., 1995, 12, (6), pp. 27-41
30. D'AVILA GARCEZ, A.S., BRODA, K., GABBAY, D.M.: 'Metalevel priorities and neural networks' in FRASCONI, P., GORI, M., KURFESS, F., and SPERDUTI, A. (Eds.): 'Proceedings of ECAI2000, Workshop on the Foundations of Connectionist-Symbolic Integration', Berlin, Germany, August 2000, pp. 38-49
31. KAKAS, A.C., and MICHAEL, A.: 'Integrating abductive and constraint logic programming'. Proceedings of the 12th International Conference on Logic programming, Tokyo, Japan, June 1995, pp. 399-413
32. TOWELL, G.G., and SHAVLIK, J.W.: 'Knowledge-based artificial neural networks', Artif. Intell., 1994, 70, (1), pp. 119-165
33. MITCHELL, T.M., and THRUN, S.B.: 'Explanation-based learning: a comparison of symbolic and neural network approaches'. 10th International Conference on Machine learning, Amherst, MA, March 1993
34. OWRE, S., RUSHBY, J., SHANKAR, N., and VON HENKE, F.: 'Formal verification for fault-tolerant architecture: prolegomena to the design of pvs', IEEE Trans. Softw. Eng., 1995, 21, (2), pp. 107-125
35. HEITMEYER, C.L., KIRBY, J., LABAW, B.G., ARCHER, M., and BHARADWAJ, R.: 'Using abstraction and model checking to detect safety violations in requirements specifications', IEEE Trans. Softw. Eng., 1998, 24, (11), pp. 927-947
36. VAN LAMSWEERDE, A., DARIMONT, R., and LETIER, E.: 'Managing conflicts in goal-driven requirement engineering', IEEE Trans. Softw. Eng., 1998, 24, (11), pp. 908-926
37. MENZIES, T.: 'Applications of abduction: knowledge level modeling', Int. J. Hum. Comput. Stud., 1996, 45, pp. 305-355
38. ZOWGHI, D., and OFFEN, R.: 'A logical framework for modeling and reasoning about the evolution of requirements'. Proceedings of the 3rd IEEE International Symposium on Requirements engineering, Annapolis, USA, January 1997, pp. 247-259
39. SATOH, K.: 'Computing minimal revised logical specification by abduction'. Proceedings of International Workshop on the Principles of software evolution, Kyoto, Japan, April 1998, pp. 177-182
40. VAN LAMSWEERDE, A., and WILLEMET, L.: 'Inferring declarative requirements specifications from operational scenarios', IEEE Trans. Softw. Eng., 1998, 24, (12), pp. 1089-1114
41. GARG, P.K., and BHANSALI, S.: 'Process programming by hindsight'. Proceedings of ICSE14, Melbourne, May 1992, pp. 280-293
42. MCCLUSKEY, T.L., and WEST, M.M.: 'The automated refinement of a requirements domain theory'. Technical Report, School of Computing and Mathematics University of Huddersfield, Huddersfield, UK, 1999
43. NUSEIBEH, B., EASTERBROOK, S., and RUSSO, A.: 'Making inconsistency respectable in software development', J. Syst. Softw., 2001, 56, (11), pp. 171-180
44. HUNTER, A., and NUSEIBEH, B.: 'Managing inconsistent specifications: Reasoning, analysis and action', Trans. Softw. Eng. Methodol, ACM Press, 1998, pp. 335-367
45. GHEZZI, C., and NUSEIBEH, B. (Eds.): IEEE Trans. Softw. Eng., Special Issue on Managing Inconsistency in Software Development. November 1999.
46. GABBAY, D.M., and HUNTER, A.: 'Making inconsistency respectable: a logical framework for inconsistency in reasoning. Part 1: a position paper' in 'Fundamentals of AI Research' (Springer-Verlag, 1991), pp. 19-32
47. EASTERBROOK, S.: 'Learning from inconsistency'. 8th International Workshop on Software specification and design, Paderborn, Germany, March 1996, pp. 136-140
48. THRUN, S.: 'Explanation-based neural network learning: a lifelong learning approach' (Kluwer Academic Publishers, Boston, MA, 1996)
49. MOONEY, R.J., and ZELLE, J.M.: 'Integrating ILP and EBL', SIGART Bull., 1994, 5, pp. 12-21
50. UCHITEL, S., and KRAMER, J.: 'A workbench for synthesising behaviour models from scenarios'. Proceedings of IEEE International Conference on Software Engineering ICSE01, Toronto, Canada, May 2001