Earticle

초록

영어

One of the most important and effort intensive activity of the entire software development process is software testing. The effort involved chiefly increases because of the need to obtain optimal test data out of the entire search space of the problem under testing. Software test data generation is one area that has seen tremendous research in terms of automation and optimization. Generating or identifying an optimal test set that satisfies a more robust adequacy criteria, like data flow testing, is still a challenging task. A number of heuristic and meta-heuristics like genetic algorithm (GA), Particle Swarm Optimization (PSO) have been applied to optimize the test data generation problem. GA, although more popular, has its own difficulties such as complex to implement and slow convergence rate. In this paper an Adaptive Particle Swarm Optimization (APSO) algorithm is applied to generate test data for data-flow dependencies of a program guided by a novel fitness function. Adaptive PSO is used because of its capability of balancing in exploration and exploitation. A new fitness function is designed based on the concepts of dominance relations, weighted branch distance for APSO to guide the search direction. A set of benchmark programs and four modules of Krishna Institute of Engineering and Technology (KIET), Enterprise resource planning (ERP) system were taken for the experimental analysis. The experimental results show that the proposed adaptive PSO based approach performed significantly better than random search, Genetic Algorithm and PSO in enhancing the convergence speed.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Background
  3.1. Data Flow Analysis
  3.2. Dominator Tree
  3.3. Particle Swarm Optimization
 4. Adaptive Particle Swarm Optimization
 5. Proposed Approach
  5.1. Adaptive PSO based Test Data Generation
  5.2. Fitness Function
  5.3. Branch Distance Computation
  5.4. Branch Weight Computation
 6. Result and Discussion
  6.1. Experimental Setup
  6.2. Performance Evaluation Parameter
  6.3. Research Questions
  6.4. Results
  6.5. Experiment on ERP Module
  6.6. Discussion
  6.7. Statistical Analysis of Proposed Approach
 7. Threats to Validity and Limitations
 8. Conclusion
 References

키워드

저자

• Sumit Kumar [ KIET, Ghaziabad, India ]
• D K Yadav [ NIT Jamshedpur, Jharkhand, India ]
• D A Khan [ NIT Jamshedpur, Jharkhand, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605