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Semantic Annotation and Retrieval Approach for Historical Testcases
- Source :
- ICEBE
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- Reusing Historical testcases play a crucial role in ensuring software testing quality. However, the diversity of historical testcases limits their potential uses. As a result, large amounts of human effort is required to write testcases for complex functional testings. In this paper, an effective framework is proposed to integrate and retrieve historical testcase bases with semantic analysis technologies. Firstly, semantic similarity is calculated to integrate the metadata of the inputted semi-structured testcases. Then, testcases are clustered by using similarity measures to eliminate heterogeneity existed in the contents of the testcases. The clustering results are added to the testcases as semantic annotations for the later semantic query. Using the semantic query interface, testers can easily obtain useful testcases without ambiguity. Finally, a case study demonstrates the effectiveness and scalability of this method for testcases retrieval for bank information systems testing.
- Subjects :
- Semantic query
Information retrieval
Computer science
Semantic analysis (machine learning)
02 engineering and technology
Semantics
Software quality
Metadata
03 medical and health sciences
0302 clinical medicine
Semantic similarity
Hardware_INTEGRATEDCIRCUITS
030221 ophthalmology & optometry
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Cluster analysis
Image retrieval
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)
- Accession number :
- edsair.doi...........0f08599ff7e3428775115c5ed3181a7c
- Full Text :
- https://doi.org/10.1109/icebe.2017.18