| 1. |
- Afzal, Wasif, et al.
(författare)
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An experiment on the effectiveness and efficiency of exploratory testing
- 2015
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Ingår i: Empirical Software Engineering. - : Springer. - 1382-3256 .- 1573-7616. ; 20:3, s. 844-878
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Tidskriftsartikel (refereegranskat)abstract
- The exploratory testing (ET) approach is commonly applied in industry, but lacks scientific research. The scientific community needs quantitative results on the performance of ET taken from realistic experimental settings. The objective of this paper is to quantify the effectiveness and efficiency of ET vs. testing with documented test cases (test case based testing, TCT). We performed four controlled experiments where a total of 24 practitioners and 46 students performed manual functional testing using ET and TCT. We measured the number of identified defects in the 90-minute testing sessions, the detection difficulty, severity and types of the detected defects, and the number of false defect reports. The results show that ET found a significantly greater number of defects. ET also found significantly more defects of varying levels of difficulty, types and severity levels. However, the two testing approaches did not differ significantly in terms of the number of false defect reports submitted. We conclude that ET was more efficient than TCT in our experiment. ET was also more effective than TCT when detection difficulty, type of defects and severity levels are considered. The two approaches are comparable when it comes to the number of false defect reports submitted.
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| 2. |
- Nidhra, Srinivas, et al.
(författare)
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Knowledge transfer challenges and mitigation strategies in global software development : A systematic literature review and industrial validation
- 2013
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Ingår i: International Journal of Information Management. - : Elsevier. - 0268-4012 .- 1873-4707. ; 33:2, s. 333-355
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Tidskriftsartikel (refereegranskat)abstract
- In this article we considered knowledge transfer (KT) in global software development (GSD) from two perspectives, state-of-the-art and state-of-the-practice, in order to identify what are the challenges that hamper the success of KT in global software teams, as well as to find out what are the mitigation strategies that can be used to overcome such challenges. The overall aim of this work is to provide a body of knowledge for enabling successful KT in GSD settings. This is achieved by an in-depth understanding of KT challenges and mitigation strategies, both from the perspective of literature and industry. It also identifies the similarities and differences in challenges and strategies gathered from literature studies and industrial experts.
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| 3. |
- Torkar, Richard, 1971, et al.
(författare)
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Prediction of faults-slip-through in large software projects: An empirical evaluation
- 2014
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Ingår i: Software quality journal. - Netherlands : Springer Science and Business Media LLC. - 0963-9314 .- 1573-1367. ; 22:1, s. 51-86
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Tidskriftsartikel (refereegranskat)abstract
- A large percentage of the cost of rework can be avoided by finding more faults earlier in a software test process. Therefore, determination of which software test phases to focus improvement work on has considerable industrial interest. We evaluate a number of prediction techniques for predicting the number of faults slipping through to unit, function, integration, and system test phases of a large industrial project. The objective is to quantify improvement potential in different test phases by striving toward finding the faults in the right phase. The results show that a range of techniques are found to be useful in predicting the number of faults slipping through to the four test phases; however, the group of search-based techniques (genetic programming, gene expression programming, artificial immune recognition system, and particle swarm optimization–based artificial neural network) consistently give better predictions, having a representation at all of the test phases. Human predictions are consistently better at two of the four test phases. We conclude that the human predictions regarding the number of faults slipping through to various test phases can be well supported by the use of search-based techniques. A combination of human and an automated search mechanism (such as any of the search-based techniques) has the potential to provide improved prediction results.
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