Peter Spragins, Google Software Engineer and Teaching Assistant at UCSD Math Department, is summarizing almost four years of experience in running software tests at scale, with several colleagues in Mountain View (California).
"The two key numbers for the system's performance are sensitivity, the percentage of failing tests we actually execute, and specificity, the percentage of passing tests we actually skip. The two numbers go hand in hand."
Discover how Machine Learning is now part of the Google process of committing code. Read his article about Efficacy Presubmit Service
