MOST: A Multi-objective Search-Based Testing from EFSM

Abstract

Abstract-This paper introduces a multi-objective evolutionary approach to test case generation from extended finite state machines (EFSM), named MOST. Testing from an (E)FSM generally involves executing various transition paths, until a given coverage criterion (e.g. cover all transitions) is met. As traditional test generation methods from FSM only consider the control aspects, they can produce many infeasible paths when applied to EFSMs, due to conflicts in guard conditions along a path. In order to avoid the infeasible path generation, we propose an approach that obtains feasible paths dynamically, instead of performing static reachability analysis as usual for FSM-based methods. Previous works have treated EFSM test case generation as a mono-objective optimization problem. Our approach takes two objectives into account that are the coverage criterion and the solution length. In this way, it is not necessary to establish in advance the test case size as earlier approaches. MOST constructs a Pareto set approximation, i.e., a group of optimal solutions, which allows the test team to select the solutions that represent a good trade-off between both objectives. The paper shows empirical studies to illustrate the benefits of the approach and comparing the results with the ones obtained in a related work.

A multi-objective evolutionary algorithm to obtain test cases with variable lengths

“…We consider the test purpose as a target transition of the model to be covered. These objective functions are described in a previous work [22]; here we give an overview, for the sake of completeness. F2 intends to minimize the input sequence length.…”

“…As a multi-objective approach, M-GEO vsl is aimed at solving problems when the solutions need to meet several conflicting objectives simultaneously. In the context of SBST, GEO methods have been successfully used to automatically generate test cases [1,21,22,5]. M-GEO vsl was briefly described in previous works [21,22] addressing only to test case generation.…”

“…In the context of SBST, GEO methods have been successfully used to automatically generate test cases [1,21,22,5]. M-GEO vsl was briefly described in previous works [21,22] addressing only to test case generation. In this paper, we present the generic steps for the implementation of the algorithm to be applied in a multi-objective problem where the solution length is itself an element to be optimized.…”

Test Generation from an Extended Finite State Machine as a Multiobjective Optimization Problem

“…One of the few existing multi-objective test generation techniques is the one proposed by Yano et al [39]. They have proposed a multi-objective approach for test case generation from EFSMs (MOST).…”

“…As mentioned in section 2.3.4, there are few multi-objective search based approaches that address test data generation. Yano et al [39] have also worked on test generation from EFSM. However, similar to Kalaji et al, their approach generates one test 30 3 0 path at a time and they address only two objectives, which are cost and feasibility.…”