| 1. |
- Afzal, Wasif, et al.
(författare)
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Genetic programming for cross-release fault count predictions in large and complex software projects
- 2010
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Ingår i: Evolutionary Computation and Optimization Algorithms in Software Engineering. - : IGI Global, Hershey, USA. - 9781615208098
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Bokkapitel (refereegranskat)abstract
- Software fault prediction can play an important role in ensuring software quality through efficient resource allocation. This could, in turn, reduce the potentially high consequential costs due to faults. Predicting faults might be even more important with the emergence of short-timed and multiple software releases aimed at quick delivery of functionality. Previous research in software fault prediction has indicated that there is a need i) to improve the validity of results by having comparisons among number of data sets from a variety of software, ii) to use appropriate model evaluation measures and iii) to use statistical testing procedures. Moreover, cross-release prediction of faults has not yet achieved sufficient attention in the literature. In an attempt to address these concerns, this paper compares the quantitative and qualitative attributes of 7 traditional and machine-learning techniques for modeling the cross-release prediction of fault count data. The comparison is done using extensive data sets gathered from a total of 7 multi-release open-source and industrial software projects. These software projects together have several years of development and are from diverse application areas, ranging from a web browser to a robotic controller software. Our quantitative analysis suggests that genetic programming (GP) tends to have better consistency in terms of goodness of fit and accuracy across majority of data sets. It also has comparatively less model bias. Qualitatively, ease of configuration and complexity are less strong points for GP even though it shows generality and gives transparent models. Artificial neural networks did not perform as well as expected while linear regression gave average predictions in terms of goodness of fit and accuracy. Support vector machine regression and traditional software reliability growth models performed below average on most of the quantitative evaluation criteria while remained on average for most of the qualitative measures.
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| 2. |
- Afzal, Wasif, et al.
(författare)
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Towards benchmarking feature subset selection methods for software fault prediction
- 2016
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Ingår i: Computational Intelligence and Quantitative Software Engineering. - Berlin, Heidelberg : Springer. - 9783319259642 - 9783319259628 ; , s. 33-58
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Bokkapitel (refereegranskat)abstract
- Despite the general acceptance that software engineering datasets often contain noisy, irrele- vant or redundant variables, very few benchmark studies of feature subset selection (FSS) methods on real-life data from software projects have been conducted. This paper provides an empirical comparison of state-of-the-art FSS methods: information gain attribute ranking (IG); Relief (RLF); principal com- ponent analysis (PCA); correlation-based feature selection (CFS); consistency-based subset evaluation (CNS); wrapper subset evaluation (WRP); and an evolutionary computation method, genetic programming (GP), on five fault prediction datasets from the PROMISE data repository. For all the datasets, the area under the receiver operating characteristic curve—the AUC value averaged over 10-fold cross- validation runs—was calculated for each FSS method-dataset combination before and after FSS. Two diverse learning algorithms, C4.5 and na ̈ıve Bayes (NB) are used to test the attribute sets given by each FSS method. The results show that although there are no statistically significant differences between the AUC values for the different FSS methods for both C4.5 and NB, a smaller set of FSS methods (IG, RLF, GP) consistently select fewer attributes without degrading classification accuracy. We conclude that in general, FSS is beneficial as it helps improve classification accuracy of NB and C4.5. There is no single best FSS method for all datasets but IG, RLF and GP consistently select fewer attributes without degrading classification accuracy within statistically significant boundaries.
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| 3. |
- Ahnström, Eva-Lisa, et al.
(författare)
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The profession of research management and administration in Sweden
- 2023
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Ingår i: The Emerald Handbook of Research Management and Administration Around the World. - : Emerald Group Publishing Ltd.. - 9781803827018 - 9781803827025 ; , s. 751-757
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter outlines the development of the Swedish Higher Education System that led to the evolution of the profession of research management and administration (RMA) in Sweden. Evolution from an informal network towards more formalised and structured work within the Swedish RMA community is highlighted. Discussion on the level of salaries development depending on the education level, gender, experience and roles are elaborated too. The majority of the Swedish RMA community are women, which does not differ from most other RMA communities around the world. Swedish Association of Research Managers and Administrators (SWARMA) is the bridge between national research and innovation funding agencies and researchers. SWARMA selected members actively participate in the reference groups for EU R&I programmes. The future for RMAs in Sweden looks bright!.
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| 4. |
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| 5. |
- Alves, Gustavo R., et al.
(författare)
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International Cooperation for Remote Laboratory Use
- 2018
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Ingår i: Contributions to Higher Engineering Education. - Singapore : Springer. - 9789811089176 ; , s. 1-31
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Bokkapitel (refereegranskat)abstract
- Experimenting is fundamental to the training process of all scientists and engineers. While experiments have been traditionally done inside laboratories, the emergence of Information and Communication Technologies added two alternatives accessible anytime, anywhere. These two alternatives are known as virtual and remote laboratories and are sometimes indistinguishably referred as online laboratories. Similarly to other instructional technologies, virtual and remote laboratories require some effort from teachers in integrating them into curricula, taking into consideration several factors that affect their adoption (i.e., cost) and their educational effectiveness (i.e., benefit). This chapter analyzes these two dimensions and sustains the case where only through international cooperation it is possible to serve the large number of teachers and students involved in engineering education. It presents an example in the area of electrical and electronics engineering, based on a remote laboratory named Virtual Instruments System in Reality, and it then describes how a number of European and Latin American institutions have been cooperating under the scope of an Erasmus+ project, for spreading its use in Brazil and Argentina.
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| 6. |
- Andersson, Martin, et al.
(författare)
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Entreprenörskapets envisa geografi
- 2019
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Ingår i: Entreprenörskap för en levande landsbygd. - Växjö : Familjen Kamprads stiftelse. - 9789151919775 ; , s. 31-43
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Andersson, Martin, et al.
(författare)
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Geography and Entrepreneurship
- 2020
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Ingår i: Handbook of Regional Science. - Berlin, Heidelberg : Springer. - 9783642362033
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Bokkapitel (refereegranskat)abstract
- We take selective stock of the literature on the geography of entrepreneurship. This literature has been focused on rates of new firm formation, whereas studies of the geography of “high-impact” entrepreneurship are still scant. Entrepreneurship may be described as a “regional event” by the fact that entrepreneurs derive necessary resources from local markets, but also from regional spillovers, social networks, and engrained factors of the local industrial geography. We point to a few fields of analysis where causal or more detailed analyses are warranted.
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| 8. |
- Andersson, Martin, et al.
(författare)
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Imports and regional development
- 2014
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Ingår i: Knowledge, Innovation and Space. - : Edward Elgar Publishing. - 9781848449015 - 9781783475988 ; , s. 80-102
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 9. |
- Andersson, Martin, et al.
(författare)
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Introduction
- 2017
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Ingår i: Geographies of Growth. - : Edward Elgar Publishing Ltd.. - 9781785360602 - 9781785360596 ; , s. 1-27
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 10. |
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