Name
Abstract | ||
|---|---|---|
Developers of performance sensitive production software are in a dilemma: performance regression tests are too costly to run at each commit, but skipping the tests delays and complicates performance regression detection. Ideally, developers would have a system that predicts whether a given commit is likely to impact performance and suggests which tests to run to detect a potential performance regression. Prior approaches towards this problem require static or dynamic analyses that limit their generality and applicability. This paper presents an approach that is simple and general, and that works surprisingly well for real applications. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICST.2017.17 | 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST) |
Keywords | Field | DocType |
perphecy,performance regression test selection,performance sensitive production software,dynamic analysis,static analysis | Regression,Commit,Computer science,Software bug,Regression testing,Real-time computing,Software,Generality,Software regression,Benchmark (computing),Reliability engineering | Conference |
ISSN | ISBN | Citations |
2381-2834 | 978-1-5090-6032-0 | 4 |
PageRank | References | Authors |
0.40 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Augusto Born De Oliveira | 1 | 37 | 4.17 |
| Sebastian Fischmeister | 2 | 409 | 52.75 |
| Amer Diwan | 3 | 941 | 76.40 |
| Matthias Hauswirth | 4 | 317 | 34.96 |
| Peter F. Sweeney | 5 | 742 | 69.82 |