This is an article from DZone’s 2022 Performance and Site Reliability Trend Report.
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Software testing is straightforward — every input => known output. However, historically, a great deal of testing has been guesswork. We create user journeys, estimate load and think time, run tests, and compare the current result with the baseline. If we don’t spot regressions, the build gets a thumbs up, and we move on. If there is a regression, back it goes. Most times, we already know the output even though it needs to be better defined — less ambiguous with clear boundaries of where a regression falls. Here is where machine learning (ML) systems and predictive analytics enter: to end ambiguity.
