Reference : Evaluating Search-Based Techniques With Statistical Tests
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Evaluating Search-Based Techniques With Statistical Tests
Arcuri, Andrea mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
The Search-Based Software Testing (SBST) Workshop
The Search-Based Software Testing (SBST) Workshop
[en] This tutorial covers the basics of how to use statistical tests to
evaluate and compare search-algorithms, in particular when applied
on software engineering problems. Search-algorithms like
Hill Climbing and Genetic Algorithms are randomised. Running
such randomised algorithms twice on the same problem can give
different results. It is hence important to run such algorithms multiple
times to collect average results, and avoid so publishing wrong
conclusions that were based on just luck. However, there is the
question of how often such runs should be repeated. Given a set
of n repeated experiments, is such n large enough to draw sound
conclusions? Or should had more experiments been run? Statistical
tests like the Wilcoxon-Mann-Whitney U-test can be used to
answer these important questions.
FnR ; FNR3949772 > Lionel Briand > VVLAB > Validation and Verification Laboratory > 01/01/2012 > 31/07/2018 > 2010

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