Abstract

Many problems cloud operators solve are computationally expensive and they often use heuristic algorithms (that are faster and scale better than the optimal) to solve them more efficiently. Heuristic analyzers enable operators to find when and by how much their heuristics underperform. However, the outputs they provide are not actionable because they lack sufficient detail about why the heuristic underperforms.

We propose XPlain, a tool that extends these analyzers and helps operators understand when and why their heuristics underperform. We present promising initial results that show such an extension is viable.

BibTeX Citation

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