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SoCS 2014

How Do You Know Your Search Algorithm and Code Are Correct?

Conference Paper Research Abstracts Algorithms and Complexity · Artificial Intelligence · Automated Planning and Scheduling

Abstract

Algorithm design and implementation are notoriously error-prone. As researchers, it is incumbent upon us to maximize the probability that our algorithms, their implementations, and the results we report are correct. In this position paper, I argue that the main technique for doing this is confirmation of results from multiple independent sources, and provide a number of concrete suggestions for how to achieve this in the context of combinatorial search algorithms.

Authors

Keywords

  • correctness
  • testing
  • debugging

Context

Venue
International Symposium on Combinatorial Search
Archive span
2010-2024
Indexed papers
598
Paper id
931064491823807426
v2026.09.13