Building a Classification System for Failed Test Reports: Industrial Experience
| Autor: | Sergey Pavlov, Anna Gromova, Evgenii Tsymbalov, Murad Mamedov, Iosif Itkin, Alexander Libkov, Andrey Novikov |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
business.industry Computer science 02 engineering and technology Machine learning computer.software_genre Test (assessment) Task (project management) 020901 industrial engineering & automation System under test Financial transaction 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Cluster analysis computer |
| Zdroj: | AITest |
| Popis: | Running complex test suites against a financial transaction system produces huge amounts of responses, both expected and unexpected. In this article, we outline our experience of using ML for reliable automatic extraction of "that" unexpected response from a big number of same type messages produced a by system under test. We describe classification approaches and data manipulations we have tried, and explain the final choices. Also we outline business constraints and final design decisions for the resultant tool.We also address the task of classifying difference patterns between expected and actual responses in attempt to provide automated pre-judgement on a reason for test failure. We outline clustering considerations and results achieved. |
| Databáze: | OpenAIRE |
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