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Recovering software requirements from system-user interaction traces
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Source SEKE; Vol. 27 archive
Proceedings of the 14th international conference on Software engineering and knowledge engineering table of contents
Ischia, Italy
SESSION: Reverse engineering table of contents
Pages: 447 - 454  
Year of Publication: 2002
ISBN:1-58113-556-4
Authors
Mohammad El-Ramly  University of Alberta, Edmonton, Alberta Canada
Eleni Stroulia  University of Alberta, Edmonton, Alberta Canada
Paul Sorenson  University of Alberta, Edmonton, Alberta Canada
Publisher
ACM  New York, NY, USA
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ABSTRACT

As software systems age, the requirements that motivated their original development get lost. Requirements documentation is unavailable or obsolete. Recapturing these requirements is critical for software reengineering activities. In our CelLEST process we adopt a data-mining approach to this problem and attempt to discover patterns of frequent similar episodes in the sequential run-time traces of the legacy user-interface behavior. These patterns constitute operational models of the application's functional requirements, from the end-user perspective. We have developed an algorithm, IPM, for interaction-pattern discovery. This algorithm discovers patterns that meet a user-specified criterion and is robust to insertion errors, caused by user mistakes or by the availability of alternative scenarios for the same user task. In this paper, we discuss IPM and we evaluate it with a case study.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Jonassen, I. Methods for Finding Motifs in Sets of Related Biosequences. Dr. Scient Thesis, Dept. of Informatics, Univ. of Bergen, 1996,
 
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Kapoor, R. and Stroulia, E. Simultaneous Legacy Interface Migration to Multiple Platforms. In Proc. 9th Int. Conf. on Human-Computer Interaction, Lawrence Erlbaum Associates, Aug. 2001, vol. 1, 51-55.
 
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Mortazavi-Asl, B. Discovering and Mining User Web-page Traversal Patterns. M.Sc. Thesis, The School Of Computing Sci., Simon Fraser Univ., Canada, Apr. 2001.
 
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Collaborative Colleagues:
Mohammad El-Ramly: colleagues
Eleni Stroulia: colleagues
Paul Sorenson: colleagues