Skip to main content
SpringerLink
Log in

Model-Based Regression Testing of Autonomous Robots

  • Conference paper
  • First Online:
SDL 2017: Model-Driven Engineering for Future Internet (SDL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10567))

Included in the following conference series:

Abstract

Testing is a common technique to assess quality of systems. Regression testing comes into view, when changes are introduced to the system under test and re-running all tests is not practical. Numerous techniques have been introduced to select tests only relevant to a given set of changes. These are typically based on source code, however, model-based development projects use models as primary artifacts described in various domain-specific languages. Thus, regression test selection should be performed directly on these models. We present a method and a case study on how model-based regression testing can be achieved in the context of autonomous robots. The method uses information from several domain-specific languages for modeling the robot’s context and configuration. Our approach is implemented in a prototype tool, and its scalability is evaluated on models from the case study.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.r5-cop.eu.

References

  1. Aggrawal, K., Singh, Y., Kaur, A.: Code coverage based technique for prioritizing test cases for regression testing. ACM Softw. Eng. Notes 29(5), 1–4 (2004)

    Article  Google Scholar 

  2. Agrawal, H., Horgan, J.R., Krauser, E.W., London, S.: Incremental regression testing. Int. Conf. Softw. Maintenance 93, 348–357 (1993)

    Google Scholar 

  3. Almasri, N., Tahat, L., Korel, B.: Toward automatically quantifying the impact of a change in systems. Softw. Qual. J., 1–40 (2016)

    Google Scholar 

  4. Altmanninger, K., Seidl, M., Wimmer, M.: A survey on model versioning approaches. Int. J. Web Inform. Syst. 5(3), 271–304 (2009)

    Article  Google Scholar 

  5. ASTM International: Standard Terminology for Evaluating Response Robot Capabilities E2521–16 (2016)

    Google Scholar 

  6. Bergmann, G., Dávid, I., Hegedüs, Á., Horváth, Á., Ráth, I., Ujhelyi, Z., Varró, D.: Viatra 3: a reactive model transformation platform. In: Kolovos, D., Wimmer, M. (eds.) ICMT 2015. LNCS, vol. 9152, pp. 101–110. Springer, Cham (2015). doi:10.1007/978-3-319-21155-8_8

    Chapter  Google Scholar 

  7. Brambilla, M., Cabot, J., Wimmer, M.: Model-Driven Software Engineering in Practice, 1st edn. Morgan & Claypool Publishers, Williston (2012)

    Google Scholar 

  8. Briand, L., Labiche, Y., He, S.: Automating regression test selection based on UML designs. Inf. Softw. Technol. 51(1), 16–30 (2009)

    Article  Google Scholar 

  9. Briand, L., Labiche, Y., Soccar, G.: Automating impact analysis and regression test selection based on UML designs. In: International Conference on Software Maintenance, pp. 252–261 (2002)

    Google Scholar 

  10. Chen, Y., Probert, R.L., Sims, D.P.: Specification-based regression test selection with risk analysis. In: Conference of the Centre for Advanced Studies on Collaborative Research, pp. 1–14 (2002)

    Google Scholar 

  11. Chen, Y., Probert, R.L., Ural, H.: Regression test suite reduction using extended dependence analysis. In: 4th International Workshop on Software Quality Assurance, SOQUA 2007, pp. 62–69. ACM (2007)

    Google Scholar 

  12. Connelly, J., Hong, W., Mahoney, R., Sparrow, D.: Challenges in autonomous system development. In: Proceedings of Performance Metrics for Intelligent Systems Workshop (PerMIS 2006) (2006)

    Google Scholar 

  13. Engström, E., Runeson, P., Skoglund, M.: A systematic review on regression test selection techniques. Inf. Softw. Technol. 52(1), 14–30 (2010)

    Article  Google Scholar 

  14. Farooq, Q., Iqbal, M., Malik, Z., Riebisch, M.: A model-based regression testing approach for evolving software systems with flexible tool support. In: IEEE International Conference on Engineering of Computer Based Systems, pp. 41–49 (2010)

    Google Scholar 

  15. Farooq, Q.u.a., Iqbal, M.Z.Z., Malik, Z.I., Nadeem, A.: An approach for selective state machine based regression testing. In: Proceeding of the 3rd International Workshop on Advances in Model-based Testing, A-MOST, pp. 44–52. ACM (2007)

    Google Scholar 

  16. Fourneret, E., Cantenot, J., Bouquet, F., Legeard, B., Botella, J.: SeTGaM: generalized technique for regression testing based on UML/OCL models. In: International Conference on Software Security and Reliability, pp. 147–156. IEEE, US (2014)

    Google Scholar 

  17. Graves, T.L., Harrold, M.J., Kim, J.M., Porter, A., Rothermel, G.: An empirical study of regression test selection techniques. ACM TOSEM 10(2), 184–208 (2001)

    Article  MATH  Google Scholar 

  18. Guiochet, J., Machin, M., Waeselynck, H.: Safety-critical advanced robots: a survey. Robot. Auton. Syst. 94, 43–52 (2017)

    Article  Google Scholar 

  19. Harman, M.: Making the case for MORTO: multi objective regression test optimization. In: ICST Workshops, pp. 111–114 (2011)

    Google Scholar 

  20. Harrold, M.J., Gupta, R., Soffa, M.L.: A methodology for controlling the size of a test suite. ACM TOSEM 2(3), 270–285 (1993)

    Article  Google Scholar 

  21. Harrold, M.J., Jones, J.A., Li, T., Liang, D., Orso, A., Pennings, M., Sinha, S., Spoon, S.A., Gujarathi, A.: Regression test selection for Java software. ACM SIGPLAN Not. 36(11), 312–326 (2001)

    Article  Google Scholar 

  22. IEEE: Systems and software engineering - Vocabulary, standard 24765:2010 (2010)

    Google Scholar 

  23. Jacoff, A., Huang, H.M., Messina, E., Virts, A., Downs, A.: Comprehensive standard test suites for the performance evaluation of mobile robots. In: Proc of the 10th Performance Metrics for Intelligent Systems Workshop, PerMIS 2010, pp. 161–168. ACM (2010)

    Google Scholar 

  24. Korel, B., Tahat, L., Vaysburg, B.: Model based regression test reduction using dependence analysis. In: International Conference on Software Maintenance, pp. 214–223 (2002)

    Google Scholar 

  25. Le Traon, Y., Jeron, T., Jezequel, J., Morel, P.: Efficient object-oriented integration and regression testing. IEEE Tran. Reliab. 49(1), 12–25 (2000)

    Article  Google Scholar 

  26. Leung, H., White, L.: Insights into regression testing. In: International Conference on Software Maintenance, pp. 60–69, October 1989

    Google Scholar 

  27. Malishevsky, A.G., Ruthruff, J.R., Rothermel, G., Elbaum, S.: Cost-cognizant test case prioritization. Technical report, Department of Computer Science and Engineering, University of Nebraska-Lincoln (2006)

    Google Scholar 

  28. Micskei, Z., Szatmári, Z., Oláh, J., Majzik, I.: A concept for testing robustness and safety of the context-aware behaviour of autonomous systems. In: Jezic, G., Kusek, M., Nguyen, N.-T., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2012. LNCS, vol. 7327, pp. 504–513. Springer, Heidelberg (2012). doi:10.1007/978-3-642-30947-2_55

    Chapter  Google Scholar 

  29. NIST: Guide for Evaluating, Purchasing, and Training with Response Robots using DHS-NIST-ASTM International Standard Test Methods (2014). https://www.nist.gov/el/intelligent-systems-division-73500/response-robots

  30. Orso, A., Do, H., Rothermel, G., Harrold, M.J., Rosenblum, D.S.: Using component metadata to regression test component-based software. Softw. Testing Verification Reliab. 17(2), 61–94 (2007)

    Article  Google Scholar 

  31. Pilskalns, O., Uyan, G., Andrews, A.: Regression testing UML designs. In: International Conference on Software Maintenance, pp. 254–264 (2006)

    Google Scholar 

  32. R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing (2013). http://www.R-project.org/

  33. R5-COP: Incremental testing of behaviour (2016). http://www.r5-cop.eu/media/cms_page_media/35/R5-COP_D34.20_v1.0_BME.pdf, d34.20 deliverable

  34. R5-COP: Assessment of the On-line Verification and Incremental Testing (2017). http://www.r5-cop.eu/media/cms_page_media/35/R5-COP_D34.50_v1.1_BME.pdf, d34.50 deliverable

  35. Rothermel, G., Harrold, M.J.: Selecting regression tests for object-oriented software. In: International Conference on Software Maintenance, pp. 14–25. IEEE (1994)

    Google Scholar 

  36. Rothermel, G., Harrold, M.J.: Analyzing regression test selection techniques. IEEE Tran. Softw. Eng. 22(8), 529–551 (1996)

    Article  Google Scholar 

  37. Rothermel, G., Untch, R.H., Chu, C., Harrold, M.J.: Prioritizing test cases for regression testing. IEEE Tran. Softw. Eng. 27(10), 929–948 (2001)

    Article  Google Scholar 

  38. Soetens, Q.D., Demeyer, S.: ChEOPSJ: change-based test optimization. In: European Conference on Software Maintenance and Reengineering, pp. 535–538 (2012)

    Google Scholar 

  39. de Sousa Santos, I., de Castro Andrade, R.M., Rocha, L.S., Matalonga, S., de Oliveira, K.M., Travassos, G.H.: Test case design for context-aware applications: are we there yet? Inf. Softw. Technol. 88, 1–16 (2017)

    Article  Google Scholar 

  40. Tengeri, D., Beszedes, A., Havas, D., Gyimothy, T.: Toolset and program repository for code coverage-based test suite analysis and manipulation. In: 14th IEEE International Working Conference on Source Code Analysis and Manipulation, pp. 47–52 (2014)

    Google Scholar 

  41. Vaysburg, B., Tahat, L.H., Korel, B.: Dependence analysis in reduction of requirement based test suites. In: Proceeding of the International Symposium on Software Testing and Analysis, pp. 107–111 (2002)

    Google Scholar 

  42. Wu, Y., Offutt, J.: Maintaining evolving component-based software with UML. In: European Conference on Software Maintenance and Reengineering, pp. 133–142 (2003)

    Google Scholar 

  43. Yoo, S., Harman, M.: Regression testing minimization, selection and prioritization: a survey. Softw. Testing Verification Reliab. 22(2), 67–120 (2012)

    Article  Google Scholar 

  44. Zech, P., Felderer, M., Kalb, P., Breu, R.: A generic platform for model-based regression testing. In: Margaria, T., Steffen, B. (eds.) ISoLA 2012. LNCS, vol. 7609, pp. 112–126. Springer, Heidelberg (2012). doi:10.1007/978-3-642-34026-0_9

    Chapter  Google Scholar 

  45. Zech, P., Kalb, P., Felderer, M., Atkinson, C., Breu, R.: Model-based regression testing by OCL. Int. J. STTT 19, 115–131 (2015)

    Article  Google Scholar 

Download references

Acknowledgment

This work was partially supported by the ARTEMIS JU and the Hungarian National Research, Development and Innovation Fund in the frame of the R5-COP project.

Author information

Authors and Affiliations

  1. Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary

    Dávid Honfi, Gábor Molnár, Zoltán Micskei & István Majzik

Authors
  1. Dávid Honfi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gábor Molnár
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zoltán Micskei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. István Majzik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zoltán Micskei .

Editor information

Editors and Affiliations

  1. Ericsson Hungary, Budapest, Hungary

    Tibor Csöndes

  2. Budapest University of Technology and Economics, Budapest, Hungary

    Gábor Kovács

  3. Ericsson Hungary, Budapest, Hungary

    György Réthy

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Honfi, D., Molnár, G., Micskei, Z., Majzik, I. (2017). Model-Based Regression Testing of Autonomous Robots. In: Csöndes, T., Kovács, G., Réthy, G. (eds) SDL 2017: Model-Driven Engineering for Future Internet. SDL 2017. Lecture Notes in Computer Science(), vol 10567. Springer, Cham. https://doi.org/10.1007/978-3-319-68015-6_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-68015-6_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68014-9

  • Online ISBN: 978-3-319-68015-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation