Particle Swarm Optimization Based Parallel Input Time Test Suite Construction

  • Yunlong Sheng
  • Chang’an WeiEmail author
  • Shouda Jiang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)


Testing of Real-Time Embedded Systems (RTESs) under input timing constraints is a critical issue, especially for parallel input factors. Test suites which can cover more possibilities of input time and discover more defects under input timing constraints are worthy of study. In this paper, Parallel Input Time Test Suites (PITTSs) are proposed to improve the coverage of input time combinations. PITTSs not only cover all the neighbor input time point combinations of each factor, but also cover all the input time point combinations between each two factors of the same input. Particle swarm optimization based the PITTS construction algorithm is presented and benchmarks with different configurations are conducted to evaluate the algorithm’ performance. A real world RTES is tested with a PITTS as application and we have reason to believe that PITTSs are effective and efficient for testing RTESs under input timing constraints of parallel input factors.


Real-time embedded systems Parallel input Time test suite construction Particle swarm optimization 



The research work presented in this paper is supported by National Defense Basic Scientific Research Project of China (xx2016xxxxx). The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.


  1. 1.
    Arcuri, A., Iqbal, M.Z., Briand, L.: Black-box system testing of real-time embedded systems using random and search-based testing. In: 22nd IFIP WG 6.1 International Conference on Testing Software and Systems, pp. 95–110. Springer, Berlin (2010)CrossRefGoogle Scholar
  2. 2.
    Bell, R.: Introduction and Revision of IEC 61508. Adv. Syst. Saf. 42, 273–291 (2011)CrossRefGoogle Scholar
  3. 3.
    Ferrer, J., Kruse, P.M., Peter, M., Chicano, F., Alba, E.: Search based algorithms for test sequence generation in functional testing. Inf. Soft. Technol. 58, 419–432 (2015)CrossRefGoogle Scholar
  4. 4.
    En-Nouaary, A., Hamou-Lhadj A.: A boundary checking technique for testing real-time systems modeled as timed input output automata. In: Eighth International Conference on Quality Software, pp. 209–215. IEEE Computer Society, Washington DC (2008)Google Scholar
  5. 5.
    Krichen, M.: A formal framework for black-box conformance testing of distributed real-time systems. Int. J. Crit. Comput. Based Syst. 3, 26–43 (2012)CrossRefGoogle Scholar
  6. 6.
    Nie, C., Wu, H., Niu, X., Kuo, F., Leung, H., Colbourn, C.: Combinatorial testing, random testing, and adaptive random testing for detecting interaction triggered failures. Inf. Softw. Technol. 62, 198–213 (2015)CrossRefGoogle Scholar
  7. 7.
    Wei, C.A., Sheng, Y.L., Jiang, S.D.: Combinatorial test suites generation method based on fuzzy genetic algorithm. J. Inf. Hiding Multimed. Signal Process. 6, 968–976 (2015)Google Scholar
  8. 8.
    Lei Y., Tai K.C.: In-parameter-order: a test generation strategy for pairwise testing. In: Proceedings of 3rd IEEE International Symposium on High-Assurance Systems Engineering, pp. 254–261. IEEE Computer Society, Washington DC (1998)Google Scholar
  9. 9.
    Kennedy, J., Eberhart, R.: Particle swarm optimization. In: ICNN’95—International Conference on Neural Networks, pp. 1942–1948. IEEE, Washington DC (1995)Google Scholar
  10. 10.
    Ahmed, B.S., Zamli, K.Z., Lim, C.P.: Application of particle swarm optimization to uniform and variable strength covering array construction. Appl. Soft Comput. 12, 1330–1347 (2012)CrossRefGoogle Scholar
  11. 11.
    Sheng, Y.L., Sun, C., Jiang, S.D., Wei, C.A.: Extended covering arrays for sequence coverage. Symmetry 10 146–1–146–26 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Automatic Test and Control InstituteHarbin Institute of TechnologyHarbinChina

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