The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Goiuria Sagardui - One of the best experts on this subject based on the ideXlab platform.
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test case selection using structural coverage in software product lines for Time Budget constrained scenarios
ACM Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
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SAC - Test case selection using structural coverage in software product lines for Time-Budget constrained scenarios
Proceedings of the 34th ACM SIGAPP Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
Urtzi Markiegi - One of the best experts on this subject based on the ideXlab platform.
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test case selection using structural coverage in software product lines for Time Budget constrained scenarios
ACM Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
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SAC - Test case selection using structural coverage in software product lines for Time-Budget constrained scenarios
Proceedings of the 34th ACM SIGAPP Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
Leire Etxeberria - One of the best experts on this subject based on the ideXlab platform.
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test case selection using structural coverage in software product lines for Time Budget constrained scenarios
ACM Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
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SAC - Test case selection using structural coverage in software product lines for Time-Budget constrained scenarios
Proceedings of the 34th ACM SIGAPP Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
Aitor Arrieta - One of the best experts on this subject based on the ideXlab platform.
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test case selection using structural coverage in software product lines for Time Budget constrained scenarios
ACM Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
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SAC - Test case selection using structural coverage in software product lines for Time-Budget constrained scenarios
Proceedings of the 34th ACM SIGAPP Symposium on Applied Computing, 2019Co-Authors: Urtzi Markiegi, Aitor Arrieta, Leire Etxeberria, Goiuria SagarduiAbstract:Testing product lines is a challenging activity due to the large number of products to be tested. Many approaches focus on reducing the Time for testing a product line by reducing the number of products to be tested, by employing, for instance, combinatorial approaches. However, even if the number of derived products by a combinatorial approach is limited, testing can still be Time consuming. In this paper, we propose three different test case selection methods that consider a given Time Budget to test product lines in an efficient manner using structural coverage information. We analyze the three methods with three white-box coverage criteria (i.e., Decision Coverage, Condition Coverage and Modified Condition/Decision Coverage). We evaluate the different approaches with a case study from the automotive domain and mutation testing. The results suggest that considering coverage information at the domain engineering level helps on detecting more faults, particularly when Time Budgets are low.
Frank M. Weerman - One of the best experts on this subject based on the ideXlab platform.
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The space-Time Budget method in criminological research
Crime Science, 2014Co-Authors: Evelien M. Hoeben, Wim Bernasco, Frank M. Weerman, Lieven Pauwels, Sjoerd Van HalemAbstract:This article reviews the Space-Time Budget method developed by Wikstrom and colleagues and particularly discusses its relevance for criminological research. The Space-Time Budget method is a data collection instrument aimed at recording, retrospectively, on an hour-by-hour basis, the whereabouts and activities of respondents during four days in the week before the interview. The method includes items about criminologically relevant events, such as offending and victimization. We demonstrate that the method can be very useful in criminology, because it enables the study of situational causes of crime and victimization, because it enables detailed measurement of theoretical concepts such as individual lifestyles and individual routine activities, and because it enables the study of adolescents’ whereabouts, which extends the traditional focus on residential neighborhoods. The present article provides the historical background of the method, explains how the method can be applied, presents validation results based on data from 843 secondary school students in the Netherlands and describes the methods’ strengths and weaknesses. Two case studies are summarized to illustrate the usefulness of the method in criminological research. The article concludes with some anticipated future developments and recommendations on further readings.
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situational causes of offending a fixed effects analysis of space Time Budget data
Criminology, 2013Co-Authors: Wim Bernasco, Lieven Pauwels, Stijn Ruiter, Gerben J N Bruinsma, Frank M. WeermanAbstract:Situational theories of crime assert that the situations that people participate in contain the proximal causes of crime. Prior research has not tested situational hypotheses rigorously, either for lack of detailed situational data or for lack of analytical rigor. The present research combines detailed situational data with analytical methods that eliminate all stable between-individual factors as potential confounds. We test seven potential situational causes: 1) presence of peers, 2) absence of adult handlers, 3) public space, 4) unstructured activities, 5) use of alcohol, 6) use of cannabis, and 7) carrying weapons. In a two-wave panel study, a general sample of adolescents completed a space-Time Budget interview that recorded, hour by hour over the course of 4 complete days, the activities and whereabouts of the subjects, including any self-reported offenses. In total, 76 individuals reported having committed 104 offenses during the 4 days covered in the space-Time Budget interview. Using data on the 4,949 hours that these 76 offenders spent awake during these 4 days, within-individual, fixed-effects multivariate logit analyses were used to establish situational causes of offending. The findings demonstrate that offending is strongly and positively related to all hypothesized situational causes except using cannabis and carrying weapons. © 2013 American Society of Criminology.
