Test Case Minimization Applying Firefly Algorithm

Abstract

The objective of this study is to propose a test case minimization method performed on UML statechart to produce test cases that are optimal while considering higher coverage criteria. Current test case generation techniques consume a large amount of time and cost with less testing coverage, while generating large number or test cases, what results in difficulties in detecting the faults and errors in the tested systems. Many approaches on test case minimization use genetic algorithms, model checking, or graph search algorithms to reduce the number of generated test cases, also the using of UML diagrams to test the system requirements and design before implementing it in the coding phase. However, these studies lack concentration in achieving higher coverage criteria and minimization in the generated test cases in the same time. The proposed test case minimization method has the following steps: provide weight to the paths, calculate path coverage for each path, transform an immediate graph into an adjacency matrix, which later is used to apply firefly algorithm and generate optimal test cases. A review on of the previous similar research in this domain has been presented and analysed to identify the issues and gaps in this domain. The steps use to perform the test case minimization have been presented together with some example and formula used. Findings from this study shows that this test case minimization has successful covered more types of test coverage which are all state, all transition, all transition pairs and all-one-loop paths. At the same time, it is capable of minimizing the number of test cases.

A systematic review on search‐based test suite reduction: State‐of‐the‐art, taxonomy, and future directions

“…In this work, we found and evaluated 23 studies that focussed on swarm intelligence-based TSR approaches. It includes some meta-heuristic algorithms, such as ACO [9], firefly algorithm (FA) [55], flower pollination algorithm (FPA) [56,57], and bat algorithm [58] used for TSR. Table 9 presents the data extracted from the selected studies.…”

“…In contrast, Hashim and Dawood [55] proposed a FA‐based TSR approach and considered the path coverage as a test adequacy criterion. The authors applied their proposed approach to five different programmes (ATM, University library, Online Shopping, Airline check‐in, Retail point of sale) and compared it with GA [32] and PSO [80].…”

Test case prioritization techniques in software regression testing: An overview

“…Panthi and Mohapatra (2015) used the same methodology to minimized test cases by exploring the state diagrams. Nor Hashim and Dawood (2018) proposed a similar approach to minimized test cases and the process has been analyzed using a UML statechart diagram. This study also shows prominent results in the form of minimizing the number of test cases.…”