How Do You Know Your Search Algorithm and Code Are Correct?
Korf, Richard Earl (University of California, Los Angeles)
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.
- Technology: