Abstract

A sequence diagram is a modeling approach for visualizing the behavioral execution of a system. The objective of this research is to investigate the problem of security in a behavioral model (sequence diagram) through the application of model refactoring. We propose detection and correction techniques, empirical evaluation of the proposed techniques and assessment of security improvement in sequence diagrams. The detection of security bad smells is achieved through the adaptation of a genetic algorithm, while correction is accomplished by the model transformation approach. The results show significant detection recall and correction efficacy of the proposed detection and correction approaches, respectively. Our results show that the proposed approach is effective in detecting and correcting bad smells and can improve the security of UML Sequence Diagram.

Highlights

  • The Unified Modeling Language (UML) is a widely used analysis and design language due to its support for a number of software quality attributes [2]

  • Since a sequence diagram is developed at the design phase, any bad smells in a sequence diagram can propagate to subsequent software artifacts

  • WORK The quality of sequence diagrams significantly affects the quality of other software artifacts

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Summary

Introduction

The Unified Modeling Language (UML) is a widely used analysis and design language due to its support for a number of software quality attributes [2]. It allows the designers to develop analysis and design models ensuring important quality attributes. A sequence diagram is a popular technique to visually represent the behavioral dynamics of a system in the forms of lifelines and their interactions. Since a sequence diagram is developed at the design phase, any bad smells in a sequence diagram can propagate to subsequent software artifacts. Refactoring is a technique that improves the quality of a software artifact without altering its behavior [3]. The correction of bad smells in sequence diagrams is extremely important to enhance the quality of this behavioral model

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