Automated composition of sequence diagrams

Software design is a significant stage in software development life cycle as it creates a blueprint for the implementation of the software. Design-errors lead to costly and insufficient implementation. Hence, it is crucial to provide solutions to discover the design error in early stage of the system development and solve them. Inspired by various engineering disciplines, the software community proposed the concept of modelling in order to reduce these costly errors. Modelling provides a platform to create an abstract representation of the software systems concluding to the birth of various modelling languages such as Unified Modelling Language (UML), Automata, and Petri Net. Due to the modelling raises the level of abstraction throughout the analysis and design process, it enables the system discovers to efficiently identify errors. Since modern systems become more complex, models are often produced part-by-part to help reduce the complexity of the design. This often results in partial specifications captured in models focusing on a subset of the system. To produce an overall model of the system, such partial models must be composed together. Model composition is the process of combining partial models to create a single coherent model. Due to manual model composition is error prone, time-consuming and tedious, it must be replaced by automated model compositions. This thesis presents a novel approach for an automatic composition technique for creating behaviour models, such as a sequence diagram, from partial specifications captured in multiple sequence diagrams with the help of constraint solvers