Model Driven Test Case Optimization of UML Combinational Diagrams Using Hybrid Bee Colony Algorithm

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Rajesh Ku. Sahoo 1,* Santosh Kumar Nanda 2 Durga Prasad Mohapatra 3 Manas Ranjan Patra 4

1. ABIT, Department of Computer Sc. & Engineering, Cuttack, Odisha, India

2. Centre for Research, Development and Consultancy, EAST, Bhubaneswar, Odisha, India

3. NIT, Department of Computer Sc. & Engineering, Rourkela, Odisha, India

4. Berhampur University, Department of Computer Sc. & Engineering, Berhampur, Odisha, India

* Corresponding author.


Received: 11 Sep. 2016 / Revised: 15 Jan. 2017 / Accepted: 2 Mar. 2017 / Published: 8 Jun. 2017

Index Terms

Software testing, automated generation of test cases, model-driven testing, UML diagrams, hybrid bee colony algorithm


To detect faults or errors for designing the quality software, software testing tool is used. Testing manually is an expensive and time taking process. To overcome this problem automated testing is used. Test case generation is a vital concept used in software testing which can be derived from requirements specification. Automation of test cases is a method where it can generate the test cases and test data automatically by using search based optimization technique. Model-driven testing is an approach that represents the behavioral model and also encodes the system behavior with certain conditions. Generally, the model consists of a set of objects that defined through variables and object relationships. This piece of work is used to generate the automated optimized test cases or test data with the possible test paths from combinational system graph. A hybrid bee colony algorithm is proposed in this paper for generating and optimizing the test cases from combinational UML diagrams.

Cite This Paper

Rajesh Ku. Sahoo, Santosh Kumar Nanda, Durga Prasad Mohapatra, Manas Ranjan Patra,"Model Driven Test Case Optimization of UML Combinational Diagrams Using Hybrid Bee Colony Algorithm", International Journal of Intelligent Systems and Applications(IJISA), Vol.9, No.6, pp.43-54, 2017. DOI:10.5815/ijisa.2017.06.05


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