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  • Aceijas, Carmen, et al. (författare)
  • Teaching Ethics in Schools of Public Health in the European Region
  • 2012
  • Ingår i: Public Health Reviews. - Public Health Reviews. - 0301-0422. ; 34:1
  • Tidskriftsartikel (refereegranskat)abstract
    • A survey targeting ASPHER members was launched in 2010/11, being a first initiative in improving ethics education in European Schools of Public Health. An 8-items questionnaire collected information on teaching of ethics in public health. A 52% response rate (43/82) revealed that almost all of the schools (95% out of 40 respondents with valid data) included the teaching of ethics in at least one of its programmes. They also expressed the need of support, (e.g.: a model curriculum (n=25), case studies (n=24)), which indicates further work to be met by the ASPHER Working Group on Ethics and Values in Public Health.
  • Adolfsson, Stefan (författare)
  • Quility Monitoring in Robotised Short Circuiting GMA Welding
  • 1997
  • Rapport (övrigt vetenskapligt)abstract
    • This paper addresses the problem of automatic monitoring the weld quality produced by robotised short arc welding. A simple statistical change detection algorithm for the weld quality, recursive Sequential Probability Ratio Test (SPRT), is used. The algorithm may equivalently be viewed as a cumulative sum (CUSUM) - type test. The test statistics is based upon the variance of the amplitude of the weld voltage. The performance of the algorithm is evaluated using experimental data. The results obtained from the algorithm indicate that it is possible to detect changes in the weld quality automatically and on-line.
  • Afzal, Wasif, et al. (författare)
  • An experiment on the effectiveness and efficiency of exploratory testing
  • 2015
  • Ingår i: Empirical Software Engineering. - Springer. - 1382-3256. ; 20:3, s. 844-878
  • 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.
  • Afzal, Wasif, et al. (författare)
  • Incorporating Metrics in an Organizational Test Strategy
  • 2008
  • Konferensbidrag (refereegranskat)abstract
    • An organizational level test strategy needs to incorporate metrics to make the testing activities visible and available to process improvements. The majority of testing measurements that are done are based on faults found in the test execution phase. In contrast, this paper investigates metrics to support software test planning and test design processes. We have assembled metrics in these two process types to support management in carrying out evidence-based test process improvements and to incorporate suitable metrics as part of an organization level test strategy. The study is composed of two steps. The first step creates a relevant context by analyzing key phases in the software testing lifecycle, while the second step identifies the attributes of software test planning and test design processes along with metric(s) support for each of the identified attributes.
  • Afzal, Wasif (författare)
  • Lessons from applying experimentation in software engineering prediction systems
  • 2008
  • Konferensbidrag (refereegranskat)abstract
    • Within software engineering prediction systems, experiments are undertaken primarliy to investigate relationships and to measure/compare models' accuracy. This paper discusses our experience and presents useful lessons/guidelines in experimenting with software engineering prediction systems. For this purpose, we use a typical software engineering experimentation process as a baseline. We found that the typical software engineering experimentation process in software engineering is supportive in developing prediction systems and have highlighted issues more central to the domain of software engineering prediction systems.
  • Afzal, Wasif, et al. (författare)
  • Prediction of faults-slip-through in large software projects:
  • 2014
  • Ingår i: Software quality journal. - 0963-9314. ; 22:1, s. 51-86
  • 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.
  • Afzal, Wasif (författare)
  • Search-based approaches to software fault prediction and software testing
  • 2009
  • Licentiatavhandling (övrigt vetenskapligt)abstract
    • Software verification and validation activities are essential for software quality but also constitute a large part of software development costs. Therefore efficient and cost-effective software verification and validation activities are both a priority and a necessity considering the pressure to decrease time-to-market and intense competition faced by many, if not all, companies today. It is then perhaps not unexpected that decisions related to software quality, when to stop testing, testing schedule and testing resource allocation needs to be as accurate as possible. This thesis investigates the application of search-based techniques within two activities of software verification and validation: Software fault prediction and software testing for non-functional system properties. Software fault prediction modeling can provide support for making important decisions as outlined above. In this thesis we empirically evaluate symbolic regression using genetic programming (a search-based technique) as a potential method for software fault predictions. Using data sets from both industrial and open-source software, the strengths and weaknesses of applying symbolic regression in genetic programming are evaluated against competitive techniques. In addition to software fault prediction this thesis also consolidates available research into predictive modeling of other attributes by applying symbolic regression in genetic programming, thus presenting a broader perspective. As an extension to the application of search-based techniques within software verification and validation this thesis further investigates the extent of application of search-based techniques for testing non-functional system properties. Based on the research findings in this thesis it can be concluded that applying symbolic regression in genetic programming may be a viable technique for software fault prediction. We additionally seek literature evidence where other search-based techniques are applied for testing of non-functional system properties, hence contributing towards the growing application of search-based techniques in diverse activities within software verification and validation.
  • Afzal, Wasif, et al. (författare)
  • Search-based prediction of fault count data
  • 2009
  • Konferensbidrag (refereegranskat)abstract
    • Symbolic regression, an application domain of genetic programming (GP), aims to find a function whose output has some desired property, like matching target values of a particular data set. While typical regression involves finding the coefficients of a pre-defined function, symbolic regression finds a general function, with coefficients, fitting the given set of data points. The concepts of symbolic regression using genetic programming can be used to evolve a model for fault count predictions. Such a model has the advantages that the evolution is not dependent on a particular structure of the model and is also independent of any assumptions, which are common in traditional time-domain parametric software reliability growth models. This research aims at applying experiments targeting fault predictions using genetic programming and comparing the results with traditional approaches to compare efficiency gains.
  • Afzal, Wasif (författare)
  • Search-Based Prediction of Software Quality
  • 2011
  • Doktorsavhandling (övrigt vetenskapligt)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.
  • Afzal, Wasif (författare)
  • Using faults-slip-through metric as a predictor of fault-proneness
  • 2010
  • Konferensbidrag (refereegranskat)abstract
    • The majority of software faults are present in small number of modules, therefore accurate prediction of fault-prone modules helps improve software quality by focusing testing efforts on a subset of modules. This paper evaluates the use of the faults-slip-through (FST) metric as a potential predictor of fault-prone modules. Rather than predicting the fault-prone modules for the complete test phase, the prediction is done at the specific test levels of integration and system test. We applied eight classification techniques to the task of identifying fault-prone modules, representing a variety of approaches, including a standard statistical technique for classification (logistic regression), tree-structured classifiers (C4.5 and random forests), a Bayesian technique (Na\"{i}ve Bayes), machine-learning techniques (support vector machines and back-propagation artificial neural networks) and search-based techniques (genetic programming and artificial immune recognition systems) on FST data collected from two large industrial projects from the telecommunication domain. \emph{Results:} Using area under the receiver operating characteristic (ROC) curve and the location of (PF, PD) pairs in the ROC space, GP showed impressive results in comparison with other techniques for predicting fault-prone modules at both integration and system test levels. The use of faults-slip-through metric in general provided good prediction results at the two test levels. The accuracy of GP is statistically significant in comparison with majority of the techniques for predicting fault-prone modules at integration and system test levels. (ii) Faults-slip-through metric has the potential to be a generally useful predictor of fault-proneness at integration and system test levels.
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