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We formally define the notion of an explanation together with three metrics, relevance, precision, and generality, that measure explanation quality. We present the explanation-generation algorithm based on techniques related to decision-tree building. We evaluate the approach on a log of past executions on Amazon EC2, and show that our approach can generate quality explanations, outperforming two na\u00efve explanation-generation methods.<\/jats:p>","DOI":"10.14778\/2180912.2180913","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"598-609","source":"Crossref","is-referenced-by-count":46,"title":["PerfXplain"],"prefix":"10.14778","volume":"5","author":[{"given":"Nodira","family":"Khoussainova","sequence":"first","affiliation":[{"name":"University of Washington, Seattle, WA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Magdalena","family":"Balazinska","sequence":"additional","affiliation":[{"name":"University of Washington, Seattle, WA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Suciu","sequence":"additional","affiliation":[{"name":"University of Washington, Seattle, WA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2012,3]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Amazon EC2. http:\/\/aws.amazon.com\/ec2\/.  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