Statistical analysis of sampled profile data in the identification of significant software test performance regressions
US7577875B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 14, 2005 |
| Grant date | Aug 18, 2009 |
| Priority date | — |
| Expiry date | Nov 29, 2026 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2201/88
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.