Running Experiments with Confidence and Sanity

Martin Aumüller, Matteo Ceccarello

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


Analyzing data from large experimental suites is a daily task for anyone doing experimental algorithmics. In this paper we report on several approaches we tried for this seemingly mundane task in a similarity search setting, reflecting on the challenges it poses.

We conclude by proposing a workflow, which can be implemented using several tools, that allows to analyze experimental data with confidence.

The extended version of this paper and the support code are provided at
Original languageEnglish
Title of host publicationInternational Conference on Similarity Search and Applications
Publication date2020
Publication statusPublished - 2020


  • Experimental algorithmics
  • Data analysis
  • Similarity search
  • Workflow development
  • Support code


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