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1,142
A survey of outlier detection methodologies
- Artificial Intelligence Review
, 2004
"... Abstract. Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human error, instrument error or simply through natural deviations in populat ..."
Abstract
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Cited by 312 (3 self)
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but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a
A Critique of Software Defect Prediction Models
- IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 1999
"... Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large literatur ..."
Abstract
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Cited by 292 (21 self)
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Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large
Self-determination and persistence in a real-life setting: Toward a motivational model of high school dropout.
- Journal of Personality and Social Psychology,
, 1997
"... The purpose of this study was to propose and test a motivational model of high school dropout. The model posits that teachers, parents, and the school administration's behaviors toward students influence students' perceptions of competence and autonomy. The less autonomy supportive the so ..."
Abstract
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Cited by 183 (19 self)
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Sciences and Humanities Research Council of Canada and grants from le Fonds pour la Formation des Chercheurs et l'Aide a la Recherche and the University du Quebec a Montreal. We would like to thank Ed Deci, Andrew Elliott, Marc Blais, Stephane Perreault, and Luc Pelletier for their feedback
Non-Parametric Statistical Fault Localization
- JOURNAL OF SYSTEMS AND SOFTWARE
, 2011
"... Fault localization is a major activity in program debugging. To automate this time-consuming task, many existing fault-localization techniques compare passed executions and failed executions, and suggest suspicious program elements, such as predicates or statements, to facilitate the identification ..."
Abstract
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Cited by 9 (4 self)
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Fault localization is a major activity in program debugging. To automate this time-consuming task, many existing fault-localization techniques compare passed executions and failed executions, and suggest suspicious program elements, such as predicates or statements, to facilitate the identification
On-Board Component Fault Detection and Isolation Using the Statistical Local Approach
, 1997
"... We describe both the key principles and real application examples of a unified theory which allows us to perform the on-board incipient fault detection and isolation tasks involved in monitoring for condition-based maintenance. We stress that, when designing detection algorithms, the main conceptual ..."
Abstract
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Cited by 41 (6 self)
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We describe both the key principles and real application examples of a unified theory which allows us to perform the on-board incipient fault detection and isolation tasks involved in monitoring for condition-based maintenance. We stress that, when designing detection algorithms, the main
Failure proximity: A fault localization-based approach
- In Proceedings of the International Symposium on the Foundations of Software Engineering
, 2006
"... Recent software systems usually feature an automated failure reporting system, with which a huge number of failing traces are collected every day. In order to prioritize fault diagnosis, failing traces due to the same fault are expected to be grouped together. Previous methods, by hypothesizing that ..."
Abstract
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Cited by 39 (2 self)
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failing case suggests is automatically obtained with Sober, an existing statistical debugging tool. We show that with R-Proximity, failing traces due to the same fault can be grouped together. In addition, we find that R-Proximity is helpful for statistical debugging: It can help developers interpret
Search-based fault localization
- in ASE, 2011
"... Abstract—Many spectrum-based fault localization measures have been proposed in the literature. However, no single fault localization measure completely outperforms others: a measure which is more accurate in localizing some bugs in some programs is less accurate in localizing other bugs in other pro ..."
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Cited by 7 (5 self)
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Abstract—Many spectrum-based fault localization measures have been proposed in the literature. However, no single fault localization measure completely outperforms others: a measure which is more accurate in localizing some bugs in some programs is less accurate in localizing other bugs in other
Directed test generation for effective fault localization
- In Proceedings of the 19th international symposium on Software testing and analysis, ISSTA ’10
"... ABSTRACT Fault-localization techniques that apply statistical analyses to execution data gathered from multiple tests are quite effective when a large test suite is available. However, if no test suite is available, what is the best approach to generate one? This paper investigates the fault-locali ..."
Abstract
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Cited by 35 (0 self)
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ABSTRACT Fault-localization techniques that apply statistical analyses to execution data gathered from multiple tests are quite effective when a large test suite is available. However, if no test suite is available, what is the best approach to generate one? This paper investigates the fault-localization
Statistical Fault Localization with Reduced Program Runs
"... Abstract. A typical approach to software fault location is to pinpoint buggy statements by comparing the failing program runs with some successful runs. Most of the research works in this line require a large amount of failing runs and successful runs. Those required execution data inevitably conta ..."
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contain a large number of redundant or noisy execution paths, and thus leads to a lower efficiency and accuracy of pinpointing. In this paper, we present an improved fault localization method by statistical analysis of difference between reduced program runs. To do so, we first use a clustering method
Results 1 - 10
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1,142
