Abstract: Techniques for isolating software regressions are provided. In one approach, QTrace is used to generate DTrace scripts to gather timing information of one or more portions of source code during a test of particular version of a program. Based on results of one or more tests of multiple versions of a program, a regression is identified with respect to a particular portion of source code. It is determined that the particular portion of source code was changed during an intermediate version of the program (i.e., between two tests). The intermediate version and/or the particular portion of source code are identified as being a potential source of the regression.

Abstract: Techniques for efficiently isolating software regressions are provided. A system test tool determines that a particular regression is present in a particular build of a software system, but not in a baseline build. Using historical data, the tool determines, for each of a plurality of intermediate builds between these two builds, a likelihood that that intermediate build introduced the particular regression. A particular intermediate build can be identified as a build to be tested. Here, the particular intermediate build comprises a plurality of layered putbacks, each of which putbacks comprises one or more code changes in the software system. The tool determines, for each putback, a likelihood that that putback introduced the particular regression. A particular putback in the plurality of putbacks may be selected as a putback to be tested. In some embodiments, the particular putback is the putback that has the greatest likelihood of introducing the particular regression.

Abstract: Techniques for efficiently isolating software regressions are provided. In one embodiment, it is determined that a particular regression is present in a particular build of a software system. A set of candidate code components that may have caused the particular regression is identified. In accordance with an order established based on historical data for the software system, one or more intermediate builds each involving some subsets of the candidate code components may be tested to identify a set of suspect code components that caused the particular regression. For each candidate code component that is not in the set of suspect code component, a likelihood factor associated with that candidate code component is decremented.

Abstract: Techniques for efficiently isolating software regressions are provided. A system test tool determines that a particular regression is present in a particular build of a software system, but not in a baseline build. Using historical data, the tool determines, for each of a plurality of intermediate builds between these two builds, a likelihood that that intermediate build introduced the particular regression. A particular intermediate build can be identified as a build to be tested. Here, the particular intermediate build comprises a plurality of layered putbacks, each of which putbacks comprises one or more code changes in the software system. The tool determines, for each putback, a likelihood that that putback introduced the particular regression. A particular putback in the plurality of putbacks may be selected as a putback to be tested. In some embodiments, the particular putback is the putback that has the greatest likelihood of introducing the particular regression.

Abstract: Techniques for efficiently isolating software regressions are provided. In one embodiment, it is determined that a particular regression is present in a particular build of a software system. A set of candidate code components that may have caused the particular regression is identified. In accordance with an order established based on historical data for the software system, one or more intermediate builds each involving some subsets of the candidate code components may be tested to identify a set of suspect code components that caused the particular regression. For each candidate code component that is not in the set of suspect code component, a likelihood factor associated with that candidate code component is decremented.

Abstract: Techniques for isolating software regressions are provided. In one approach, QTrace is used to generate DTrace scripts to gather timing information of one or more portions of source code during a test of particular version of a program. Based on results of one or more tests of multiple versions of a program, a regression is identified with respect to a particular portion of source code. It is determined that the particular portion of source code was changed during an intermediate version of the program (i.e., between two tests). The intermediate version and/or the particular portion of source code are identified as being a potential source of the regression.