Sap Se

Jingun Hong

Dong Won Hwang

Won Joon Lee

Sumi Yun

Database instances can be clustered using various attributes, such as attributes reflecting resources assigned to a database instance, attributes reflecting configuration or software version information, or attributes that reflect users or usage of a database instance. As it can be resource intensive to capture database workloads, one or more database instances can be selected from one or more of the clusters and workloads can be captured from such instances. In a similar manner, various attributes can be used to cluster database instances, and one or more instances can be selected from one or more of the clusters, and a captured workload can be replayed on such instances.

Database instance clustering

Machine learning is used for pre-submit test selection. A commit including a new code change is obtained and a feature vector is generated based on the code change and historical test information. A ranking pre-submit tests is determined by providing the feature vector to a learning algorithm. One or more pre-submit tests are selected based on the ranking and the new code change is tested using selected tests. An assessment of the new code change is determined based on the test results, which indicate whether the new code change is accepted or rejected for submission to the source code repository. Later, new submitted source code stored in the repository is tested using a set of post-submit tests to obtain post-submit test results. Then the learning algorithm is updated based on the assessment of the new code change and the post-submit test results to obtain an updated learning algorithm.

Machine learning based pre-submit test selection

Various examples are directed to systems and methods for testing software. A testing system may use test case data describing a first test case failed by a first build of the software application, the first build generated by a first commit operation of the plurality of commit operations to execute a fault localization operation, the fault localization operation to identify a first suspect program element of a first build. The testing system may use the first suspect program element and commit data to select a second commit operation from the plurality of commit operations. The testing system may determine an error-inducing commit operation from the plurality of commit operations and executing a corrective action.

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Seoul, South Korea

Jingun Hong