Abstract
A legacy system is an operational, large-scale software system that is maintained beyond its first generation of programmers. It typically represents a massive economic investment and is critical to the mission of the organization it serves. As such systems age, they become increasingly complex and brittle, and hence harder to maintain. They also become even more critical to the survival of their organization because the business rules encoded within the system are seldom documented elsewhere.
Our research is concerned with developing a suite of tools to aid the maintainers of legacy systems in recovering the knowledge embodied within the system. The activities, known collectively as “program understanding”, are essential preludes for several key processes, including maintenance and design recovery for reengineering.
In this paper we present three pattern-matching techniques: source code metrics, a dynamic programming algorithm for finding the best alignment between two code fragments, and a statistical matching algorithm between abstract code descriptions represented in an abstract language and actual source code. The methods are applied to detect instances of code cloning in several moderately-sized production systems including tcsh, bash, and CLIPS.
The programmer's skill and experience are essential elements of our approach. Selection of particular tools and analysis methods depends on the needs of the particular task to be accomplished. Integration of the tools provides opportunities for synergy, allowing the programmer to select the most appropriate tool for a given task.
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This work is in part supported by IBM Canada Ltd., Institute for Robotics and Intelligent Systems, a Canadian Network of Centers of Excellence and, the Natural Sciences and Engineering Research Council of Canada. Based on “Pattern Matching for Design Concept Localization” by K.A.Kontogiannis, R.DeMori, M.Bernstein, M.Galler, E.Merlo, which first appeared in Proceedings of the Second Working Conference on Reverse Enginering, pp.96–103, July, 1995, © IEEE, 1995
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Kontogiannis, K.A., Demori, R., Merlo, E. et al. Pattern matching for clone and concept detection. Automated Software Engineering 3, 77–108 (1996). https://doi.org/10.1007/BF00126960
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DOI: https://doi.org/10.1007/BF00126960