Abstract
Software Testing using the object-oriented approach is always a challenging job for the researchers in recent days. To produce quality software, Automation of Software Testing plays a vital role. This chapter concentrates on an innovative idea to produce test scenarios by combining UML sequence and state machine diagrams. First, the author designed the case study of the model into its sequence diagram (SD) and state machine diagram (SMD). Subsequently, the SD and SMD are converted into a sequence diagram graph (SDG) and state machine diagram graph (SMDG). Then these diagrams are combined to generate an intermediate graph known as a state-sequence intermediate graph (SSIG). To examine the active performance of the system and to generate the test scenarios, the graph was traversed using a depth-first search (DFS) method. Various coverage criteria like all transition paths, message sequence path coverage, all sate coverage, and an XML parser are used to generate the test scenarios. In this chapter, a case study of the Library book issue system is addressed and the above model is implemented in it. The authors observed that all transition path coverage shows better results in our proposed model.
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Panigrahi, S.S., Jena, A.K. (2020). Test Scenarios Generation Using Combined Object-Oriented Models. In: Automated Software Engineering: A Deep Learning-Based Approach. Learning and Analytics in Intelligent Systems, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-030-38006-9_4
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