| 1. |
- Abbaspour, Sara, et al.
(författare)
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Web Service Response Time Monitoring : Architecture and Validation
- 2011
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Ingår i: Communications in Computer and Information Science Volume 164 CCIS, 2011. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642249983 ; , s. 276-282
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Konferensbidrag (refereegranskat)abstract
- Web services are used in many Web applications in order to save time and cost during software development process. To peruse Web service response time, a suitable tool is needed to automate the measurement of the response time. However, not many suitable tools are available for automatic measurement of response time. This research is carried out in the context of quality of Web services in order to measure and visualize Web service response time. The method proposed in this research for accomplishing this goal is based on creating a proxy for connecting to the required Web service, and then calculating the Web services response time via the proxy. A software tool is designed based on the proposed method in order to guide the implementation that is still in progress. The tool can be validated through empirical validation using three test cases for three different Web service access situations.
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| 2. |
- Abrahamsson, Henrik, et al.
(författare)
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Simulation of IPTV caching strategies
- 2010. - 6
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Ingår i: Proceedings of the 2010 International Symposium on Performance Evaluation of Computer and Telecommunication Systems. ; , s. 187-193
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Konferensbidrag (refereegranskat)abstract
- IPTV, where television is distributed over the Internet Protocol in a single operator network, has become popular and widespread. Many telecom and broadband companies have become TV providers and distribute TV channels using multicast over their backbone networks. IPTV also means an evolution to time-shifted television where viewers now often can choose to watch the programs at any time. However, distributing individual TV streams to each viewer requires a lot of bandwidth and is a big challenge for TV operators. In this paper we present an empirical IPTV workload model, simulate IPTV distribution with time-shift, and show that local caching can limit the bandwidth requirements significantly.
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| 4. |
- Adolfsson, Margareta, 1950-, et al.
(författare)
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Exploring changes over time in habilitation professionals' perceptions and applications of the International Classification of Functioning, Disability and Health, version for Children and Youth (ICF-CY).
- 2010
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Ingår i: Journal of Rehabilitation Medicine. - : Medical Journals Sweden AB. - 1650-1977 .- 1651-2081. ; 42:7, s. 670-678
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE This study explored how professionals in inter-disciplinary teams perceived the implementation of the World Health Organization's International Classification of Functioning, Disability and Health, version for Children and Youth (ICF-CY) in Swedish habilitation services. DESIGN Descriptive longitudinal mixed-methods design. METHODS Following participation in a 2-day in-service training on the ICF-CY, 113 professionals from 14 interdisciplinary teams described their perceptions of the implementation of the ICF-CY at 3 consecutive time-points: during in-service training, after 1 year, and after 2.5 years. RESULTS Implementation of the ICF-CY in daily work focused on assessment and habilitation planning and required adaptations of routines and materials. The ICF-CY was perceived as useful in supporting analyses and in communication about children's needs. Professionals also perceived it as contributing to new perspectives on problems and a sharpened focus on participation. CONCLUSION Professionals indicated that the ICF-CY enhanced their awareness of families' views of child participation, which corresponded to organizational goals for habilitation services. An implementation finding was a lack of tools fitting the comprehensive ICF-CY perspective. The study points to the need for ICF-CY-based assessment and intervention methods focusing on child participation
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| 7. |
- 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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| 8. |
- Afzal, Wasif, et al.
(författare)
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On the application of genetic programming for software engineering predictive modeling : A systematic review
- 2011
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Ingår i: Expert Systems with Applications. - : Pergamon-Elsevier Science Ltd. - 0957-4174 .- 1873-6793. ; 38:9, s. 11984-11997
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Forskningsöversikt (refereegranskat)abstract
- The objective of this paper is to investigate the evidence for symbolic regression using genetic programming (GP) being an effective method for prediction and estimation in software engineering, when compared with regression/machine learning models and other comparison groups (including comparisons with different improvements over the standard GP algorithm). We performed a systematic review of literature that compared genetic programming models with comparative techniques based on different independent project variables. A total of 23 primary studies were obtained after searching different information sources in the time span 1995-2008. The results of the review show that symbolic regression using genetic programming has been applied in three domains within software engineering predictive modeling: (i) Software quality classification (eight primary studies). (ii) Software cost/effort/size estimation (seven primary studies). (iii) Software fault prediction/software reliability growth modeling (eight primary studies). While there is evidence in support of using genetic programming for software quality classification, software fault prediction and software reliability growth modeling: the results are inconclusive for software cost/effort/size estimation.
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| 9. |
- Afzal, Wasif, et al.
(författare)
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Search-based prediction of fault-slip-through in large software projects
- 2010
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Ingår i: Proceedings - 2nd International Symposium on Search Based Software Engineering, SSBSE 2010. - : IEEE. - 9780769541952 ; , s. 79-88
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Konferensbidrag (refereegranskat)abstract
- A large percentage of the cost of rework can be avoided by finding more faults earlier in a software testing process. Therefore, determination of which software testing phases to focus improvements work on, has considerable industrial interest. This paper evaluates the use of five different techniques, namely particle swarm optimization based artificial neural networks (PSO-ANN), artificial immune recognition systems (AIRS), gene expression programming (GEP), genetic programming (GP) and multiple regression (MR), for predicting the number of faults slipping through unit, function, integration and system testing phases. The objective is to quantify improvement potential in different testing phases by striving towards finding the right faults in the right phase. We have conducted an empirical study of two large projects from a telecommunication company developing mobile platforms and wireless semiconductors. The results are compared using simple residuals, goodness of fit and absolute relative error measures. They indicate that the four search-based techniques (PSO-ANN, AIRS, GEP, GP) perform better than multiple regression for predicting the fault-slip-through for each of the four testing phases. At the unit and function testing phases, AIRS and PSO-ANN performed better while GP performed better at integration and system testing phases. The study concludes that a variety of search-based techniques are applicable for predicting the improvement potential in different testing phases with GP showing more consistent performance across two of the four test phases.
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| 10. |
- Afzal, Wasif
(författare)
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Search-Based Prediction of Software Quality : Evaluations and Comparisons
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Software verification and validation (V&V) activities are critical for achieving software quality; however, these activities also constitute a large part of the costs when developing software. Therefore efficient and effective software V&V activities are both a priority and a necessity considering the pressure to decrease time-to-market and the intense competition faced by many, if not all, companies today. It is then perhaps not unexpected that decisions that affects software quality, e.g., how to allocate testing resources, develop testing schedules and to decide when to stop testing, needs to be as stable and accurate as possible. The objective of this thesis is to investigate how search-based techniques can support decision-making and help control variation in software V&V activities, thereby indirectly improving software quality. Several themes in providing this support are investigated: predicting reliability of future software versions based on fault history; fault prediction to improve test phase efficiency; assignment of resources to fixing faults; and distinguishing fault-prone software modules from non-faulty ones. A common element in these investigations is the use of search-based techniques, often also called metaheuristic techniques, for supporting the V&V decision-making processes. Search-based techniques are promising since, as many problems in real world, software V&V can be formulated as optimization problems where near optimal solutions are often good enough. Moreover, these techniques are general optimization solutions that can potentially be applied across a larger variety of decision-making situations than other existing alternatives. Apart from presenting the current state of the art, in the form of a systematic literature review, and doing comparative evaluations of a variety of metaheuristic techniques on large-scale projects (both industrial and open-source), this thesis also presents methodological investigations using search-based techniques that are relevant to the task of software quality measurement and prediction. The results of applying search-based techniques in large-scale projects, while investigating a variety of research themes, show that they consistently give competitive results in comparison with existing techniques. Based on the research findings, we conclude that search-based techniques are viable techniques to use in supporting the decision-making processes within software V&V activities. The accuracy and consistency of these techniques make them important tools when developing future decision-support for effective management of software V&V activities.
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