Deriving high-level abstractions from legacy software using example-driven clustering
Pages 188 - 199
Abstract
Much research in the past two decades has focused on automatic generation of abstractions from low-level software elements using clustering algorithms. This research is generally motivated by comprehension improvement through more abstract constructs, re-architecture of existing systems to improve their maintenance, or migration to new paradigms. In this paper, we start from a formulation of software clustering problems in a setting, where elements of a software system form a graph to be partitioned in order to derive high-level abstractions. We then propose a novel formulation where the graph partitioning solution is evaluated by the degree of its conformance with past clustering cases given as examples. We provide a concrete illustration of this formulation with the problem of object identification in procedural code.
References
[1]
G. Canfora, A. Cimitile, M. Munro and M. Tortorella, "Experiments in identifying reusable abstract data types in program code", in Workshop on Program Comprehension, pp. 36--45, 1993.
[2]
G. Czibula and G. Şerban, "Improving systems design using a clustering approach", International Journal of Computer Science and Network Security, vol. 6, no. 12, pp. 40--49, 2006.
[3]
H. Abdeen, S. Ducasse, H. Sahraoui, and I. Alloui, "Automatic package coupling and cycle minimization", in Working Conference on Reverse Engineering, pp. 103--112, 2009.
[4]
H. Sahraoui, P. Valtchev, I. Konkobo, and S. Shen, "Object identification in legacy code as a grouping problem", in International Computer Software and Applications Conference, pp. 689--696, 2002.
[5]
H. Sahraoui, W. Melo, H. Lounis, and F. Dumont, "Applying concept formation methods to object identification in procedural code", in International Conference on Automated Software Engineering, pp. 210--218, 1997.
[6]
H. Washizaki and Y. Fukazawa. "A technique for automatic component extraction from object-oriented programs by refactoring", in Science of Computer Programming, vol. 56, no.1--2, pp. 99--116, 2005.
[7]
J. Kennedy and R. Eberhart, "Particle swarm optimization", in International Conference on Neural Networks, vol. 4, pp. 1942--1948, 1995.
[8]
M. Harman and L. Tratt, "Pareto optimal search based refactoring at the design level", in Conference on Genetic and Evolutionary Computation, pp. 1106--1113, 2007.
[9]
M. Harman, R. Hierons, and M. Proctor, "A new representation and crossover operator for search-based optimization of software modularization", in Genetic and Evolutionary Computation Conference, pp. 1351--1358, 2002.
[10]
M. O'Keefee and Mel Ó Cinnéide. "Automated design improvement by example", in Conference on New Trends in Software Methodologies, Tools and Techniques, pp. 315--329, 2007.
[11]
M. Siff and T. Reps, "Identifying modules via concept analysis", in Transactions on Software Engineering, vol. 25, no. 6, pp. 749--768, 1999.
[12]
M. Wimmer, M. Strommer, H. Kargl, and G. Kramler, "Towards model transformation generation by-example", in International Conference on System Sciences, pp. 285b, 2007.
[13]
O. Seng, M. Bauer, M. Biehl, and G. Pache, "Search-based improvement of subsystem decompositions", in Conference on Genetic and Evolutionary Computation, pp. 1045--1051, 2005.
[14]
S. Allier, H. Sahraoui, S. Sadou, and S. Vaucher, "Restructuring object-oriented applications into component-oriented applications by using consistency with execution traces", in International Symposium on Component Based Software Engineering, pp. 216--231, 2010.
[15]
S. Kirkpatrick, "Optimization by simulated annealing: quantitative studies", in Journal Of Statistical Physics, vol. 34, no. 5, pp. 975--986, 1984.
[16]
S. Mancoridis, B. Mitchell, C. Rorres, Y. Chen, and E. Gansner, "Using automatic clustering to produce high-level system organizations of source code", in International Workshop on Program Comprehension, pp. 45--53, 1998.
[17]
S. Mancoridis, B. Mitchell, Y. Chen, and E. Gansner, "Bunch: A clustering tool for the recovery and maintenance of software system structures", in International Conference on Software Maintenance, pp. 50--59, 1999.
[18]
S. Mitchell, "A heuristic search approach to solving the software clustering problem", Dissertation, Drexel University, Philadelphia, PA, United States, 2002.
[19]
V. D. Blondel, A. Gajardo, M. Heymans, P. Senellart, and P. Van Dooren, "A measure of similarity between graph vertexes: Applications to synonym extraction and web searching", Society for Industrial and Applied Mathematics, vol. 46, no. 4, pp. 647--666, 2004.
[20]
V. Kelner, F. Capitanescu, O. Léonard, and L. Wehenkel, "A hybrid optimization technique coupling an evolutionary and a local search algorithm", in Journal Of Computational And Applied Mathematics, vol. 215, no.2, pp. 448--456, 2008.
[21]
V. Van Deursen and T. Kuipers, "Identifying objects using cluster and concept analysis", in International Conference on Software Engineering, pp. 246--255, 1999.
[22]
P. Andritsos and V. Tzerpos, "Software clustering based on information loss minimization.", in 10th Working Conference on Reverse Engineering, pp. 334--344, 2003.
- Deriving high-level abstractions from legacy software using example-driven clustering
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Information & Contributors
Information
Published In
November 2011
422 pages
- Conference Chairs:
- Joanna Ng,
- Christian Couturier,
- Editors:
- Marin Litoiu,
- Eleni Stroulia,
- Stephen MacKay,
- Program Chairs:
- Marin Litoiu,
- Eleni Stroulia
Sponsors
- IBM Canada Ltd. Laboratory Centre for Advanced Studies
- IBM Canada: IBM Canada
Publisher
IBM Corp.
United States
Publication History
Published: 07 November 2011
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- Research-article
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CASCON '11
Sponsor:
- IBM Canada
CASCON '11: Center for Advanced Studies on Collaborative Research
November 7 - 10, 2011
Ontario, Toronto, Canada
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Overall Acceptance Rate 24 of 90 submissions, 27%
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