Abstract: Sampled profile data provides information about processor activity during a test. Processor activity can be analyzed to determine an amount of processor resources used to execute the various functions, modules, and processes associated with a tested software activity. Statistical methods can be applied to the resource data from multiple test runs to determine whether a significant regression has occurred between a baseline test pass and a daily test pass. By collecting data at the function, module and process levels, significant regressions may be uncovered at any of the levels. Regressions may also be ranked according to their importance, which allows for identification and notification of development teams responsible for significant regressions.

Abstract: In testing hardware and/or software, processor events can be logged during a test. Using the events, we can determine an amount of processor activity not used to execute software considered to be involved in the test. Such noise may then be accounted for in determining and prioritizing regressions, as well as to improve test results generally.