Abstract
Background: Modern industry is heavily dependent on software. The complexity of designing and developing software is a serious engineering issue. With the growing size of software systems and increase in complexity, inconsistencies arise in software design and intelligent techniques are required to detect and fix inconsistencies. Aim: Current industrial practice of manually detecting inconsistencies is time consuming, error prone and incomplete. Inconsistencies arising as a result of polymorphic object interactions are hard to trace. We propose an approach to detect and fix inconsistencies in polymorphic method invocations in sequence models. Method: A novel intelligent approach based on self regulating particle swarm optimization to solve the inconsistency during software system design is presented. Inconsistency handling is modelled as an optimization problem that uses a maximizing fitness function. The proposed approach also identifies the changes required in the design diagrams to fix the inconsistencies. Result: The method is evaluated on different software design models involving static and dynamic polymorphism and inconsistencies are detected and resolved. Conclusion: Ensuring consistency of design is highly essential to develop quality software and solves a major design issue for practitioners. In addition, our approach helps to reduce the time and cost of developing software.
Highlights
Today s biggest industry is software industry in terms of manpower, complex interactions and changing tasks with evolving designs
We present an intelligent approach based on Self Regulating Particle Swarm Optimization (SRPSO) to solve the inconsistency in polymorphic methods during the software system design
The consistency checking algorithm is applied to the Unified Modeling Language (UML) models to detect method invocation inconsistency
Summary
Today s biggest industry is software industry in terms of manpower, complex interactions and changing tasks with evolving designs. With the increasing relevance of software in industries, software development has become more complex. Design and development of quality software is a major challenge for software developers and many a times, the process is manual. The complexity of designing and developing software is a serious engineering issue. With the growing size of software systems and increase in complexity, inconsistencies arise in software design and intelligent techniques are required to detect and fix inconsistencies. We propose an approach to detect and fix inconsistencies in polymorphic method invocations in sequence models. Method: A novel intelligent approach based on self regulating particle swarm optimization to solve the inconsistency during software system design is presented. Result: The method is evaluated on different software design models involving static and dynamic polymorphism and inconsistencies are detected and resolved. Our approach helps to reduce the time and cost of developing software
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