Software testing is a key phase in software development lifecycle. Testing objectives corresponds to the discovery and detection of faults, which can be attained by utilizing manual or automated testing approaches. In this thesis, we are mainly concerned with the manual test approaches. The most commonly used manual testing approaches in the software industry are the Exploratory Testing (ET) approach and the Test Case Based Testing (TCBT) approach. TCBT is primarily used by software testers to formulize and guide their testing tasks and set the theoretical principles for testing. On the other hand ET is simultaneous learning, test design, and test execution. Software testing might benefit from an intelligent combination of these approaches of testing however there is no proof of any formal process that accommodates the usage of both test approaches in a combination. This thesis presents a process for Mix Testing (MT) based on the strengths and weaknesses of both test approaches, identified through a systematic literature review and interviews with testers in a software organization. The new process is defined through the mapping of weaknesses of one approach to the strengths of other. Static validation of the MT process through interviews in the software organization suggested that MT has ability to resolve the problems of both test approaches to some extent. Furthermore, MT was validated by conducting an experiment in an industrial setting. The analysis of the experimentation results indicated that MT has better defect detection than TCBT and less than ET. In addition, the results of the experiments also indicate that MT provides equal functionality coverage as compared to ET and TCBT.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-3083 |
| Date | January 2010 |
| Creators | Shah, Syed Muhammad Ali, Alvi, Usman Sattar |
| Publisher | Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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