Abstract
Unified Modeling Language models are the de facto industry standard for object-oriented modeling of the static and dynamic aspects of software systems. To ensure software quality, it is essential to maintain consistency between the models. Inconsistencies among the diagrams of a model may result in serious faults which are hard to detect and may lead to project failure. Complex systems require large number of diagrams and hence detection of inconsistencies among the diagrams has a significant role during the design phase of software development. In this paper we describe a method for detection of inconsistencies among the class and activity diagrams using particle swarm optimization technique. Particle Swarm Optimization (PSO) is a soft computing technique that provides solutions to optimization problems by maximizing certain objectives in a complex search space. The PSO algorithm is applied to detect inconsistency and to optimize the consistency value of the attributes to ensure consistency. The application of PSO algorithm provides consistent, optimized diagrams that result in the generation of more accurate code.
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George, R., Samuel, P. (2016). Particle Swarm Optimization Method Based Consistency Checking in UML Class and Activity Diagrams. In: Snášel, V., Abraham, A., Krömer, P., Pant, M., Muda, A. (eds) Innovations in Bio-Inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-28031-8_10
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DOI: https://doi.org/10.1007/978-3-319-28031-8_10
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