The Experts below are selected from a list of 2379 Experts worldwide ranked by ideXlab platform
Vidroha Debroy - One of the best experts on this subject based on the ideXlab platform.
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towards better fault localization a crosstab based statistical approach
2012Co-Authors: W E Wong, Vidroha DebroyAbstract:It is becoming prohibitively expensive and time consuming, as well as tedious and error-prone, to perform debugging manually. Among the debugging activities, fault localization has been one of the most expensive, and therefore, a large number of fault-localization techniques have been proposed over the recent years. This paper presents a crosstab-based statistical technique that makes use of the coverage information of each executable statement and the execution result (success or failure) with respect to each test case to localize faults in an effective and efficient manner. A crosstab is constructed for each executable statement, and a statistic is computed to determine the Suspiciousness of the corresponding statement. Statements with a higher Suspiciousness are more likely to contain bugs and should be examined before those with a lower Suspiciousness. Case studies are performed on both small- (the Siemens and Unix suites) and large-sized programs (space, grep, gzip, and make), and results suggest that the crosstab-based technique (CBT) is more effective (in terms of a smaller percentage of executable statements that have to be examined until the first statement containing the fault is reached) than other techniques, such as Tarantula. Further studies using the Siemens suite reveal that the proposed technique is also more effective at locating faults than other statistically oriented techniques, such as SOBER and Liblit05. Additional experiments evaluate the CBT from other perspectives, such as its efficiency in terms of time taken, its applicability to object-oriented languages (on a very large Java program: Ant), and its sensitivity to test suite size, and demonstrate its superior performance.
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effective software fault localization using an rbf neural network
2012Co-Authors: W E Wong, Vidroha Debroy, Richard M Golden, Bhavani ThuraisinghamAbstract:We propose the application of a modified radial basis function neural network in the context of software fault localization, to assist programmers in locating bugs effectively. This neural network is trained to learn the relationship between the statement coverage information of a test case and its corresponding execution result, success or failure. The trained network is then given as input a set of virtual test cases, each covering a single statement. The output of the network, for each virtual test case, is considered to be the Suspiciousness of the corresponding covered statement. A statement with a higher Suspiciousness has a higher likelihood of containing a bug, and thus statements can be ranked in descending order of their Suspiciousness. The ranking can then be examined one by one, starting from the top, until a bug is located. Case studies on 15 different programs were conducted, and the results clearly show that our proposed technique is more effective than several other popular, state of the art fault localization techniques. Further studies investigate the robustness of the proposed technique, and illustrate how it can easily be applied to programs with multiple bugs as well.
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ties within fault localization rankings exposing and addressing the problem
2011Co-Authors: Vidroha Debroy, Xiaofeng Xu, Eric W WongAbstract:Software fault localization techniques typically rank program components, such as statements or predicates, in descending order of their Suspiciousness (likelihood of being faulty). During debugging, programmers may examine these components, starting from the top of the ranking, in order to locate faults. However, the assigned Suspiciousness to each component may not always be unique, and thus some of them may be tied for the same position in the ranking. In such a scenario, the total number of components that a programmer needs to examine in order to find the faults may vary considerably. The greater the variability, the harder it is for a programmer to decide which component to examine first, and the harder it is to accurately compute the expected effectiveness of a fault localization technique. In this paper, we first conduct a case study, based on three fault localization techniques across four sets of programs, which reveals that the phenomenon of assigning the same Suspiciousness to multiple components is not limited to any technique or program in particular. Thus, to reduce variability and alleviate this problem, four tie-breaking strategies are discussed and evaluated empirically in our second case study. Results indicate that the strategies can not only reduce the number of ties in the rankings, but also maintain the effectiveness of the fault localization techniques. We also propose a new metric for evaluating fault localization techniques called CScore, which takes the notion of ties into account. Finally, an additional slicing-based approach to breaking ties is discussed briefly, which aims to provide further insights into tie-breaking and stimulate further research in the area.
W E Wong - One of the best experts on this subject based on the ideXlab platform.
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towards better fault localization a crosstab based statistical approach
2012Co-Authors: W E Wong, Vidroha DebroyAbstract:It is becoming prohibitively expensive and time consuming, as well as tedious and error-prone, to perform debugging manually. Among the debugging activities, fault localization has been one of the most expensive, and therefore, a large number of fault-localization techniques have been proposed over the recent years. This paper presents a crosstab-based statistical technique that makes use of the coverage information of each executable statement and the execution result (success or failure) with respect to each test case to localize faults in an effective and efficient manner. A crosstab is constructed for each executable statement, and a statistic is computed to determine the Suspiciousness of the corresponding statement. Statements with a higher Suspiciousness are more likely to contain bugs and should be examined before those with a lower Suspiciousness. Case studies are performed on both small- (the Siemens and Unix suites) and large-sized programs (space, grep, gzip, and make), and results suggest that the crosstab-based technique (CBT) is more effective (in terms of a smaller percentage of executable statements that have to be examined until the first statement containing the fault is reached) than other techniques, such as Tarantula. Further studies using the Siemens suite reveal that the proposed technique is also more effective at locating faults than other statistically oriented techniques, such as SOBER and Liblit05. Additional experiments evaluate the CBT from other perspectives, such as its efficiency in terms of time taken, its applicability to object-oriented languages (on a very large Java program: Ant), and its sensitivity to test suite size, and demonstrate its superior performance.
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effective software fault localization using an rbf neural network
2012Co-Authors: W E Wong, Vidroha Debroy, Richard M Golden, Bhavani ThuraisinghamAbstract:We propose the application of a modified radial basis function neural network in the context of software fault localization, to assist programmers in locating bugs effectively. This neural network is trained to learn the relationship between the statement coverage information of a test case and its corresponding execution result, success or failure. The trained network is then given as input a set of virtual test cases, each covering a single statement. The output of the network, for each virtual test case, is considered to be the Suspiciousness of the corresponding covered statement. A statement with a higher Suspiciousness has a higher likelihood of containing a bug, and thus statements can be ranked in descending order of their Suspiciousness. The ranking can then be examined one by one, starting from the top, until a bug is located. Case studies on 15 different programs were conducted, and the results clearly show that our proposed technique is more effective than several other popular, state of the art fault localization techniques. Further studies investigate the robustness of the proposed technique, and illustrate how it can easily be applied to programs with multiple bugs as well.
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a crosstab based statistical method for effective fault localization
2008Co-Authors: W E Wong, Tingting Wei, Lei ZhaoAbstract:Fault localization is the most expensive activity in program debugging. Traditional ad-hoc methods can be time-consuming and ineffective because they rely on programmers' intuitive guesswork, which may neither be accurate nor reliable. A better solution is to utilize a systematic and statistically well-defined method to automatically identify suspicious code that should be examined for possible fault locations. We present a crosstab-based statistical method using the coverage information of each executable statement and the execution result (success or failure) with respect to each test case. A crosstab is constructed for each executable statement and a statistic is computed to determine the Suspiciousness of the corresponding statement. Statements with a higher Suspiciousness are more likely to contain bugs and should be examined before those with a lower Suspiciousness. Three case studies using the Siemens suite, the Space program, and the Unix suite, respectively, are conducted. Our results suggest that the crosstab-based method is effective in fault localization and performs better (in terms of a smaller percentage of executable statements that have to be examined until the first statement containing the fault is reached) than other methods such as Tarantula. The difference in efficiency (computational time) between these two methods is very small.
Nico Karssemeijer - One of the best experts on this subject based on the ideXlab platform.
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Influence of local contrast optimisation on perceived case Suspiciousness in digital screening mammography
2012Co-Authors: Wouter J. H. Veldkamp, Roelant Visser, Gerard J. Den Heeten, Nico Karssemeijer, M.j.m. BroedersAbstract:Poster: "ECR 2012 / C-0851 / Influence of local contrast optimisation on perceived case Suspiciousness in digital screening mammography" by: "W. Veldkamp1, R. Visser2, G. J. den Heeten2, N. Karssemeijer2, M. Broeders2; 1Leiden/NL, 2Nijmegen/NL"
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Increase in perceived case Suspiciousness due to local contrast optimisation in digital screening mammography
2011Co-Authors: Roelant Visser, Wouter J. H. Veldkamp, David Beijerinck, Petra A. M. Bun, Jan J. M. Deurenberg, Mechli W. Imhof-tas, Klaas H. Schuur, Miranda M. Snoeren, Gerard J. Den Heeten, Nico KarssemeijerAbstract:Objectives To determine the influence of local contrast optimisation on diagnostic accuracy and perceived Suspiciousness of digital screening mammograms.
Adrian Raine - One of the best experts on this subject based on the ideXlab platform.
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developmental aspects of schizotypy and Suspiciousness a review
2018Co-Authors: Keri Kayee Wong, Adrian RaineAbstract:This review identifies the early developmental processes that contribute to schizotypy and Suspiciousness in adolescence and adulthood. It includes the most recent literature on these phenomena in childhood. The early developmental processes that affect schizotypy and paranoia in later life are complex. In contrast to existing studies of psychiatric patients and clinical/nonclinical adult populations, the study of schizotypy and Suspiciousness in young children and adolescents is possible due to new child-appropriate dimensional assessments. New assessments and the advancement of technology (e.g., virtual reality in mental health) as well as statistical modeling (e.g., mediation and latent-class analyses) in large data have helped identified the developmental aspects (e.g., psychosocial, neurocognitive and brain factors, nutrition, and childhood correlates) that predict schizotypy and Suspiciousness in later life. Prospective longitudinal designs in community youths can enhance our understanding of the etiology of schizophrenia-spectrum disorders and, in the future, the development of preventive interventions by extending adult theories and interventions to younger populations.
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developmental aspects of schizotypy and Suspiciousness a review
2018Co-Authors: Keri Kayee Wong, Adrian RaineAbstract:PURPOSE OF THE REVIEW: This review identifies the early developmental processes that contribute to schizotypy and Suspiciousness in adolescence and adulthood. It includes the most recent literature on these phenomena in childhood. RECENT FINDINGS: The early developmental processes that affect schizotypy and paranoia in later life are complex. In contrast to existing studies of psychiatric patients and clinical/nonclinical adult populations, the study of schizotypy and Suspiciousness in young children and adolescents is possible due to new child-appropriate dimensional assessments. New assessments and the advancement of technology (e.g., virtual reality in mental health) as well as statistical modeling (e.g., mediation and latent-class analyses) in large data have helped identified the developmental aspects (e.g., psychosocial, neurocognitive and brain factors, nutrition, and childhood correlates) that predict schizotypy and Suspiciousness in later life. SUMMARY: Prospective longitudinal designs in community youths can enhance our understanding of the etiology of schizophrenia-spectrum disorders and, in the future, the development of preventive interventions by extending adult theories and interventions to younger populations.
Chen Daoxu - One of the best experts on this subject based on the ideXlab platform.
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research on software fault localization based on execution trace
2009Co-Authors: Chen DaoxuAbstract:Software reliability is directly relevant to the count of faults in software.Fault localization is the key to detect and eliminate the faults.Execution trace-based fault localization is of great significance because it can be integrated well with automatic software testing.Proposed the framework of execution trace-based fault localization FLOC,which can be divided into four components:organization of execution trace,selection of execution trace,computation of Suspiciousness,and evaluation of the output.The typical current execution trace-based approaches were described and compared in FLOC.Finally some improvements were proposed according to FLOC.The purpose of this paper is to compare the advantages and disadvantages of those localization approaches in a unified framework,and provide some improvements on those approaches.
