Improving Proceeding Test Case Prioritization with Learning Software Agents

Sebastian Abele, Peter Göhner

Abstract

Test case prioritization is an important technique to improve the planning and management of a system test. The system test itself is an iterative process, which accompanies a software system during its whole life cycle. Usually, a software system is altered and extended continuously. Test case prioritization algorithms find and order the most important test cases to increase the test efficiency in the limited test time. Generally, the knowledge about a system’s characteristics grows throughout the development. With better experience and more empirical data, the test case prioritization can be optimized to rise the test efficiency. This article introduces a learning agent-based test case prioritization system, which improves the prioritization automatically by drawing conclusions from actual test results.

References

  1. Bellini, P., Bruno, I., Nesi, P., and Rogai, D. (2005). Comparing fault-proneness estimation models. In 10th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS'05), pages 205-214.
  2. Chittimalli, P. and Harrold, M.-J. (2009). Recomputing coverage information to assist regression testing. IEEE Transactions on Software Engineering, 35(4):452- 469.
  3. Engström, E., Runeson, P., and Skoglund, M. (2010). A systematic review on regression test selection techniques. Information and Software Technology, 52(1):14-30.
  4. Fenton, N. and Neil, M. (1999). A critique of software defect prediction models. IEEE Transactions on Software Engineering, 25(5):675-689.
  5. Kim, S., Zimmermann, T., Whitehead Jr., E. J., and Zeller, A. (2007). Predicting faults from cached history. In Proceedings of the 29th International Conference on Software Engineering, pages 489-498, Los Alamitos. IEEE Computer Society.
  6. Malz, C. and Göhner, P. (2011). Agent-based test case prioritization. In IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops (ICSTW), pages 149-152.
  7. Malz, C., Jazdi, N., and Göhner, P. (2012). Prioritization of test cases using software agents and fuzzy logic. In 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation (ICST), pages 483-486.
  8. Mubarak, H. (2008). Developing flexible software using agent-oriented software engineering. IEEE Software, 25(5):12-15.
  9. Pech, S. and Goehner, P. (2010). Multi-agent information retrieval in heterogeneous industrial automation environments. In Agents and Data Mining Interaction, volume 5980 of Lecture Notes in Computer Science, pages 27-39. Springer, Berlin and Heidelberg.
  10. Rauscher, M. and Göhner, P. (2013). Agent-based consistency check in early mechatronic design phase. In Proceedings of the 19th International Conference on Engineering Design (ICED13), Design for Harmonies, volume 9, pages 289-396. Design Society, Seoul.
  11. Wooldridge, M. and Jennings, N. R. (1995). Intelligent agents: theory and practice. The Knowledge Engineering Review, 10(02):115-152.
  12. Yoo, S. and Harman, M. (2012). Regression testing minimization, selection and prioritization: a survey. Software Testing, Verification and Reliability, 22(2):67- 120.
Download


Paper Citation


in Harvard Style

Abele S. and Göhner P. (2014). Improving Proceeding Test Case Prioritization with Learning Software Agents . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-016-1, pages 293-298. DOI: 10.5220/0004920002930298


in Bibtex Style

@conference{icaart14,
author={Sebastian Abele and Peter Göhner},
title={Improving Proceeding Test Case Prioritization with Learning Software Agents},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2014},
pages={293-298},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004920002930298},
isbn={978-989-758-016-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Improving Proceeding Test Case Prioritization with Learning Software Agents
SN - 978-989-758-016-1
AU - Abele S.
AU - Göhner P.
PY - 2014
SP - 293
EP - 298
DO - 10.5220/0004920002930298