http://www.dagstuhl.de/08351

August 24 – 29 , 2008, Dagstuhl Seminar 08351

Evolutionary Test Generation

Organizers

Holger Schlingloff (HU Berlin, DE)
Tanja Vos (Univ. Politèc. de Valencia, ES)
Joachim Wegener (Berner & Mattner Systemtechnik – Berlin, DE)

For support, please contact

Dagstuhl Service Team

Documents

Dagstuhl Seminar Proceedings DROPS
List of Participants

Summary

The ``Evolutionary Test Generation'' Dagstuhl seminar that was held from September 24th to September 29th 2008. The organisation of the seminar was initiated by the EvoTest project, a project funded by the European Commission under the contract number IST-33472. The goal of our seminar was to bring together researchers from the software testing and evolutionary algorithms communities for the discussion of problems and challenges in evolutionary test generation. This goal has been satisfactorily met and has led to a comprehensive list of open problems and challenges identified and discussed during the seminar. The seminar has been attended by 33 people: 30 were researchers from all over the world working on evolutionary testing, test generation and/or evolutionary computing; 3 were industrial participants with experience and feedback from real-life challenges were present: Microsoft, IBM and Berner & Mattner. The abstract collection indicates the talks that were given by the participants.

Systematic testing is the most widely used method to ensure that a program meets its specification. The effectiveness of testing for quality assurance largely depends on the chosen test suite. Currently, test suites are constructed either manually or semi-automatically from the program code or program specification. For large systems, however, manual test case construction is tedious and error-prone, whereas semi-automatic procedures often achieve only insufficient coverage. Therefore, new methods for the automated generation of "good" test suites are necessary.

Evolutionary adaptive search techniques offer a promising perspective for this problem. Genetic algorithms have been investigated for complex search problems in various fields. Their basic principles are selection, mutation, and recombination. These principles can be beneficially applied to the automated generation and optimisation of test suites, both from code (white-box testing) and specification (black-box testing). However, to make this approach successful in practice, a lot of problems remain to be solved: the question of adequate testing objectives, coverage and reliability measures, representation issues for test cases and test suites, seeding, recombination and mutation strategies, and others.

Results of the discussions: Open problems and future challenges

The future challenges identified at the Dagstuhl seminar have been categorized as follows:

  • Theoretical foundations
  • Search Technique improvements
  • New testing objectives
  • Tool environment/testing infrastructure
  • New application areas

Classification

  • Modelling / Simulation
  • Sw-engineering
  • Semantics / Specification / Formal Methods
  • Verification / Logic
  • Soft Computing / Evol. Algorithms

Keywords

  • Test generation
  • Evolutionary algorithms
  • Model Based Development
  • Genetic algorithms

Book exhibition

Books from the participants of the current Seminar 

Book exhibition in the library, ground floor, during the seminar week.

Documentation

In the series Dagstuhl Reports each Dagstuhl Seminar and Dagstuhl Perspectives Workshop is documented. The seminar organizers, in cooperation with the collector, prepare a report that includes contributions from the participants' talks together with a summary of the seminar.

 

Download overview leaflet (PDF).

Publications

Furthermore, a comprehensive peer-reviewed collection of research papers can be published in the series Dagstuhl Follow-Ups.

Dagstuhl's Impact

Please inform us when a publication was published as a result from your seminar. These publications are listed in the category Dagstuhl's Impact and are presented on a special shelf on the ground floor of the library.

NSF young researcher support