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Sökning: db:Swepub > Övrigt vetenskapligt > Mälardalens högskola > (2005-2009)

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2.
  • Abelli, Björn, 1961- (författare)
  • On Stage! Playwriting, Directing and Enacting the Informing Processes
  • 2007
  • Doktorsavhandling (övrigt vetenskapligt)abstract
    • Within the discipline of information systems sometimes the conception of the main object is that the information system must be computer based. An example of an information system that is non-computer based is the scenic theatre performance. Input is the message or knowledge the participants of the theatre production want to pass over to the audience; output is the information and experiences the performance in itself mediates to the audience. This has been produced through a system development process; although the developers not always have been aware about what development model has been used.The dissertation combines some of the concepts found in theatre production with traditional system development concepts, and hence introduces new perspectives into the area of information systems. Some of the main findings in the study of theatre productions were the triplicity of a theatre production as a development process, an information system and an organization at the same time; the integrated relations of context, developers and users, which leads to spontaneous changes and overlaps of development roles; and the narrative and dramaturgical approach in the practical use of methods and techniques.These aspects should be useful also in development of other types of information systems, whether computer based or using other information technologies. The triplicity gives arguments to redefine each of these concepts. The generalizability of this approach has been validated through a second study, at a folk high school, which showed that models and concepts from theatre productions are possible to generalize to other information system areas than theatre, and that the borders of the organization coincides with the borders of the information system. Especially temporary organizations must be seen as ongoing, continuous development processes.
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5.
  • Abut, Hüseyin, et al. (författare)
  • Real-World Data Collection with UYANIK
  • 2009
  • Ingår i: In-Vehicle Corpus and Signal Processing for Driver Behavior. - Springer. - 978-0-387-79581-2 - 978-0-387-79582-9 ; s. 23-44
  • Bokkapitel (övrigt vetenskapligt)
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7.
  • Adolfsson, Petra, et al. (författare)
  • Closing words!
  • 2009
  • Ingår i: Guiding and guided tours. - Göteborg : BAS Publishers. - 978-91-7246-285-4 ; s. 215-217
  • Bokkapitel (övrigt vetenskapligt)
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8.
  • Adolfsson, Petra, et al. (författare)
  • Introduction – Guiding and guided tours
  • 2009
  • Ingår i: Guiding and guided tours. - Göteborg : BAS Publishers. - 978-91-7246-285-4 ; s. 15-28
  • Bokkapitel (övrigt vetenskapligt)
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9.
  • Afzal, Wasif, et al. (författare)
  • A systematic review of search-based testing for non-functional system properties
  • 2009
  • Ingår i: Information and Software Technology. - 0950-5849. ; 51:6, s. 957-976
  • Forskningsöversikt (övrigt vetenskapligt)abstract
    • Search-based software testing is the application of metaheuristic search techniques to generate software tests. The test adequacy criterion is transformed into a fitness function and a set of solutions in the search space are evaluated with respect to the fitness function using a metaheuristic search technique. The application of metaheuristic search techniques for testing is promising due to the fact that exhaustive testing is infeasible considering the size and complexity of software under test. Search-based software testing has been applied across the spectrum of test case design methods; this includes white-box (structural), black-box (functional) and grey-box (combination of structural and functional) testing. In addition, metaheuristic search techniques have also been applied to test non-functional properties. The overall objective of undertaking this systematic review is to examine existing work into non-functional search-based software testing (NFSBST). We are interested in types of non-functional testing targeted using metaheuristic search techniques, different fitness functions used in different types of search-based non-functional testing and challenges in the application of these techniques. The systematic review is based on a comprehensive set of 35 articles obtained after a multi-stage selection process and have been published in the time span 1996–2007. The results of the review show that metaheuristic search techniques have been applied for non-functional testing of execution time, quality of service, security, usability and safety. A variety of metaheuristic search techniques are found to be applicable for non-functional testing including simulated annealing, tabu search, genetic algorithms, ant colony methods, grammatical evolution, genetic programming (and its variants including linear genetic programming) and swarm intelligence methods. The review reports on different fitness functions used to guide the search for each of the categories of execution time, safety, usability, quality of service and security; along with a discussion of possible challenges in the application of metaheuristic search techniques.
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10.
  • Afzal, Wasif, et al. (författare)
  • Genetic programming for cross-release fault count predictions in large and complex software projects
  • 2009
  • Ingår i: Evolutionary Computation and Optimization Algorithms in Software Engineering. - IGI Global. - 9781615208098
  • Bokkapitel (övrigt vetenskapligt)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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