Matches in SemOpenAlex for { <https://semopenalex.org/work/W3207316101> ?p ?o ?g. }
- W3207316101 endingPage "1043" @default.
- W3207316101 startingPage "1027" @default.
- W3207316101 abstract "Software testing is still a manual process in many industries, despite the recent improvements in automated testing techniques. As a result, test cases (which consist of one or more test steps that need to be executed manually by the tester) are often specified in natural language by different employees and many redundant test cases might exist in the test suite. This increases the (already high) cost of test execution. Manually identifying similar test cases is a time-consuming and error-prone task. Therefore, in this paper, we propose an unsupervised approach to identify similar test cases. Our approach uses a combination of text embedding, text similarity and clustering techniques to identify similar test cases. We evaluate five different text embedding techniques, two text similarity metrics, and two clustering techniques to cluster similar test steps and three techniques to identify similar test cases from the test step clusters. Through an evaluation in an industrial setting, we showed that our approach achieves a high performance to cluster test steps (an F-score of 87.39%) and identify similar test cases (an F-score of 86.13%). Furthermore, a validation with developers indicates several different practical usages of our approach (such as identifying redundant test cases), which help to reduce the testing manual effort and time." @default.
- W3207316101 created "2021-10-25" @default.
- W3207316101 creator A5026684568 @default.
- W3207316101 creator A5060673676 @default.
- W3207316101 creator A5066198862 @default.
- W3207316101 creator A5066994589 @default.
- W3207316101 date "2023-03-01" @default.
- W3207316101 modified "2023-10-09" @default.
- W3207316101 title "Identifying Similar Test Cases That Are Specified in Natural Language" @default.
- W3207316101 cites W1504779339 @default.
- W3207316101 cites W1538791262 @default.
- W3207316101 cites W1820505434 @default.
- W3207316101 cites W1846261984 @default.
- W3207316101 cites W1867551913 @default.
- W3207316101 cites W1915139526 @default.
- W3207316101 cites W1972375918 @default.
- W3207316101 cites W1978394996 @default.
- W3207316101 cites W1985690171 @default.
- W3207316101 cites W1990710124 @default.
- W3207316101 cites W1992987499 @default.
- W3207316101 cites W1996073624 @default.
- W3207316101 cites W1999793044 @default.
- W3207316101 cites W2038869480 @default.
- W3207316101 cites W2053154970 @default.
- W3207316101 cites W2071106922 @default.
- W3207316101 cites W2071332064 @default.
- W3207316101 cites W2080395944 @default.
- W3207316101 cites W2143470595 @default.
- W3207316101 cites W2145734471 @default.
- W3207316101 cites W2153418968 @default.
- W3207316101 cites W2164777277 @default.
- W3207316101 cites W2165663378 @default.
- W3207316101 cites W2239306219 @default.
- W3207316101 cites W2461407631 @default.
- W3207316101 cites W2465098971 @default.
- W3207316101 cites W2491258296 @default.
- W3207316101 cites W2546674645 @default.
- W3207316101 cites W2583788916 @default.
- W3207316101 cites W2805144384 @default.
- W3207316101 cites W2884854827 @default.
- W3207316101 cites W2890521506 @default.
- W3207316101 cites W2893667345 @default.
- W3207316101 cites W2970641574 @default.
- W3207316101 cites W3032170634 @default.
- W3207316101 cites W3034238904 @default.
- W3207316101 cites W3042750271 @default.
- W3207316101 cites W3047487993 @default.
- W3207316101 cites W3090921344 @default.
- W3207316101 cites W3094765685 @default.
- W3207316101 cites W3104859925 @default.
- W3207316101 cites W3175507369 @default.
- W3207316101 cites W4250042253 @default.
- W3207316101 doi "https://doi.org/10.1109/tse.2022.3170272" @default.
- W3207316101 hasPublicationYear "2023" @default.
- W3207316101 type Work @default.
- W3207316101 sameAs 3207316101 @default.
- W3207316101 citedByCount "1" @default.
- W3207316101 countsByYear W32073161012022 @default.
- W3207316101 crossrefType "journal-article" @default.
- W3207316101 hasAuthorship W3207316101A5026684568 @default.
- W3207316101 hasAuthorship W3207316101A5060673676 @default.
- W3207316101 hasAuthorship W3207316101A5066198862 @default.
- W3207316101 hasAuthorship W3207316101A5066994589 @default.
- W3207316101 hasBestOaLocation W32073161012 @default.
- W3207316101 hasConcept C103278499 @default.
- W3207316101 hasConcept C115961682 @default.
- W3207316101 hasConcept C119857082 @default.
- W3207316101 hasConcept C124101348 @default.
- W3207316101 hasConcept C128942645 @default.
- W3207316101 hasConcept C149091818 @default.
- W3207316101 hasConcept C151552104 @default.
- W3207316101 hasConcept C151730666 @default.
- W3207316101 hasConcept C152877465 @default.
- W3207316101 hasConcept C154945302 @default.
- W3207316101 hasConcept C186846655 @default.
- W3207316101 hasConcept C195324797 @default.
- W3207316101 hasConcept C199360897 @default.
- W3207316101 hasConcept C204321447 @default.
- W3207316101 hasConcept C2777267654 @default.
- W3207316101 hasConcept C2777904410 @default.
- W3207316101 hasConcept C41008148 @default.
- W3207316101 hasConcept C73555534 @default.
- W3207316101 hasConcept C7435765 @default.
- W3207316101 hasConcept C86803240 @default.
- W3207316101 hasConceptScore W3207316101C103278499 @default.
- W3207316101 hasConceptScore W3207316101C115961682 @default.
- W3207316101 hasConceptScore W3207316101C119857082 @default.
- W3207316101 hasConceptScore W3207316101C124101348 @default.
- W3207316101 hasConceptScore W3207316101C128942645 @default.
- W3207316101 hasConceptScore W3207316101C149091818 @default.
- W3207316101 hasConceptScore W3207316101C151552104 @default.
- W3207316101 hasConceptScore W3207316101C151730666 @default.
- W3207316101 hasConceptScore W3207316101C152877465 @default.
- W3207316101 hasConceptScore W3207316101C154945302 @default.
- W3207316101 hasConceptScore W3207316101C186846655 @default.
- W3207316101 hasConceptScore W3207316101C195324797 @default.
- W3207316101 hasConceptScore W3207316101C199360897 @default.
- W3207316101 hasConceptScore W3207316101C204321447 @default.