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Gap between academia and industry: a case of empirical evaluation of three software testing methods
- Source :
- International Journal of System Assurance Engineering and Management. 10:1487-1504
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- Doing the right kind of testing has always been one of main challenging and a decisive task for industry. To choose right software testing method(s), industry needs to have an exact objective knowledge of their effectiveness, efficiency, and applicability conditions. The most common way to evaluate testing methods, for such knowledge, is with empirical studies. Reliable and comprehensive evidence can be obtained by aggregating the results of different empirical studies (family of experiments) taking into account their findings and limitations. We conducted a study to investigate the current state of the art of empirical knowledge base of three testing methods. We found that although the empirical studies conducted so far to evaluate testing methods contain many important and interesting results; however, we still lack factual and generalizable knowledge about performance and applicability conditions of testing methods(s), making it unfeasible to be readily adopted by the industry. Moreover, we tried to identify the major factors responsible for limiting academia from producing significantly reliable results having an industrial impact. We believe that besides effective and long-term academia-industry collaboration, there is a need for more systematic, quantifiable and comprehensive empirical studies (which provides scope for aggregation using rigorous techniques), mainly replications so as to create an effective and applicable knowledge base about testing methods which potentially can fill the gap between academia and industry.
- Subjects :
- Scope (project management)
Computer science
business.industry
Strategy and Management
020207 software engineering
02 engineering and technology
Limiting
Family of experiments
Task (project management)
Empirical research
Risk analysis (engineering)
Knowledge base
Software testing
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Safety, Risk, Reliability and Quality
Empirical evidence
business
Subjects
Details
- ISSN :
- 09764348 and 09756809
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- International Journal of System Assurance Engineering and Management
- Accession number :
- edsair.doi...........ed4018ed749326db1193e2e488c55455
- Full Text :
- https://doi.org/10.1007/s13198-019-00899-2