A tabu search algorithm for structural software testing

Abstract

This paper presents a tabu search metaheuristic algorithm for the automatic generation of structural software tests. It is a novel work since tabu search is applied to the automation of the test generation task, whereas previous works have used other techniques such as genetic algorithms. The developed test generator has a cost function for intensifying the search and another for diversifying the search that is used when the intensification is not successful. It also combines the use of memory with a backtracking process to avoid getting stuck in local minima. Evaluation of the generator was performed using complex programs under test and large ranges for input variables.Results show that the developed generator is both effective and efficient.

Test Cost Optimization Using Tabu Search

“…Using these automation tools cost can be reduced and saves the time [3,7]. Another approach suggests the use of tabu search algorithm for generation of structural software tests [4]. It also combines the use of memory with a backtracking process to avoid getting stuck in local minima [8].…”

“…But here we are using Tabu Search [4]. Tabu Search will choose appropriate test paths and concepts of Dijkstra algorithm will be implemented in Aspiration Criteria to optimize the cost.…”

A Modified Staged Continuous Tabu Search Algorithm

“…This method was also reported to be used in facility layout to improve the efficiency of material handing within a manufacturing system [4]. In addition, TS algorithm was reported to be used for structural software testing [5].…”

“…This method was also reported to be used in facility layout to improve the efficiency of material handing within a manufacturing system [4]. In addition, TS algorithm was reported to be used for structural software testing [5].Although TS algorithm can get global optimum by tabu list, the probability of being trapped in a local optimum still exists. Many method were proposed to solve this kind shortage, such as using a specific neighborhood definition which employs a block of jobs notion [6], employing a flexible memory system to avoid the entrapment in a local minimum and developing the ideal of "distance" to the fitness to accelerate optimization [7], processing a new parallel model for TS algorithm based on the crossover operator of genetic algorithms [8], and using three continuous stages in process like stage continuous tabu search (SCTS) algorithm [9].…”

Estimating Software Development Effort Using Tabu Search

“…There exist other searchbased techniques that have been found to be very effective and robust in solving numerous optimization problems. In particular, Tabu Search has been successfully applied for software testing (Diaz et al, 2008), for object replication in distributed web server (Mahmood and Homeed, 2005) and for Software-Hardware Partitioning (Lanying and Shi, 2008). In this paper, we report on an empirical study carried out to analyze the effectiveness of Tabu Search for effort estimation.…”