Statistical Causal Analysis For Fault Localization
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Statistical Causal Analysis For Fault Localization
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Author : George Kofi Baah
language : en
Publisher:
Release Date : 2012
Statistical Causal Analysis For Fault Localization written by George Kofi Baah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computer software categories.
The ubiquitous nature of software demands that software is released without faults. However, software developers inadvertently introduce faults into software during development. To remove the faults in software, one of the tasks developers perform is debugging. However, debugging is a difficult, tedious, and time-consuming process. Several semi-automated techniques have been developed to reduce the burden on the developer during debugging. These techniques consist of experimental, statistical, and program-structure based techniques. Most of the debugging techniques address the part of the debugging process that relates to finding the location of the fault, which is referred to as fault localization. The current fault-localization techniques have several limitations. Some of the limitations of the techniques include (1) problems with program semantics, (2) the requirement for automated oracles, which in practice are difficult if not impossible to develop, and (3) the lack of theoretical basis for addressing the fault-localization problem. \r : \r : The thesis of this dissertation is that statistical causal analysis combined with program analysis is a feasible and effective approach to finding the causes of software failures. The overall goal of this research is to significantly extend the state of the art in fault localization. To extend the state-of-the-art, a novel probabilistic model that combines program-analysis information with statistical information in a principled manner is developed. The model known as the probabilistic program dependence graph (PPDG) is applied to the fault-localization problem. The insights gained from applying the PPDG to fault localization fuels the development of a novel theoretical framework for fault localization based on established causal inference methodology. The development of the framework enables current statistical fault-localization metrics to be analyzed from a causal perspective. The analysis of the metrics show that the metrics are related to each other thereby allowing the unification of the metrics. Also, the analysis of metrics from a causal perspective reveal that the current statistical techniques do not find the causes of program failures instead the techniques find the program elements most associated with failures. However, the fault-localization problem is a causal problem and statistical association does not imply causation. Several empirical studies are conducted on several software subjects and the results (1) confirm our analytical results, (2) demonstrate the efficacy of our causal technique for fault localization. The results demonstrate the research in this dissertation significantly improves on the state-of-the-art in fault localization.
Handbook Of Software Fault Localization
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Author : W. Eric Wong
language : en
Publisher: John Wiley & Sons
Release Date : 2023-04-21
Handbook Of Software Fault Localization written by W. Eric Wong and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-21 with Computers categories.
Handbook of Software Fault Localization A comprehensive analysis of fault localization techniques and strategies In Handbook of Software Fault Localization: Foundations and Advances, distinguished computer scientists Prof. W. Eric Wong and Prof. T.H. Tse deliver a robust treatment of up-to-date techniques, tools, and essential issues in software fault localization. The authors offer collective discussions of fault localization strategies with an emphasis on the most important features of each approach. The book also explores critical aspects of software fault localization, like multiple bugs, successful and failed test cases, coincidental correctness, faults introduced by missing code, the combination of several fault localization techniques, ties within fault localization rankings, concurrency bugs, spreadsheet fault localization, and theoretical studies on fault localization. Readers will benefit from the authors’ straightforward discussions of how to apply cost-effective techniques to a variety of specific environments common in the real world. They will also enjoy the in-depth explorations of recent research directions on this topic. Handbook of Software Fault Localization also includes: A thorough introduction to the concepts of software testing and debugging, their importance, typical challenges, and the consequences of poor efforts Comprehensive explorations of traditional fault localization techniques, including program logging, assertions, and breakpoints Practical discussions of slicing-based, program spectrum-based, and statistics-based techniques In-depth examinations of machine learning-, data mining-, and model-based techniques for software fault localization Perfect for researchers, professors, and students studying and working in the field, Handbook of Software Fault Localization: Foundations and Advances is also an indispensable resource for software engineers, managers, and software project decision makers responsible for schedule and budget control.
Ai And Deep Learning For Networks
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Author : Gopee Mukhopadhyay
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Ai And Deep Learning For Networks written by Gopee Mukhopadhyay and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
Welcome to the forefront of technological evolution with "AI and Deep Learning for Networks." Our book is your definitive guide to understanding the powerful combination of AI and deep learning, simplifying complex concepts while providing the technical depth needed for meaningful comprehension. We explore the transformative power of AI, starting from foundational principles to cutting-edge applications in computer networks. Whether you're a curious beginner or an experienced professional, this book offers a seamless blend of accessible language and technical precision. Discover the intricacies of machine learning, the nuances of supervised and unsupervised learning, and the significance of fundamental algorithms like neural networks. Each chapter caters to a wide range of readers, ensuring everyone can unravel the symbiosis between intelligent algorithms and network dynamics. Dive deeper into the synergy of Deep Learning and Software Defined Networks, exploring how convolutional neural networks optimize traffic engineering and reinforcement learning enhances network security. Real-world applications, ethical considerations, and emerging trends are interwoven to provide a holistic understanding of AI in computer networking. This book is not just a manual but a companion on your journey to a future where intelligent networks seamlessly adapt, secure, and innovate. Embrace the transformative potential of AI and deep learning, and chart your course toward a technologically enriched future.
Reliable Software Technologies Ada Europe 2013
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Author : Hubert B. Keller
language : en
Publisher: Springer
Release Date : 2013-05-27
Reliable Software Technologies Ada Europe 2013 written by Hubert B. Keller and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-27 with Computers categories.
This book constitutes the refereed proceedings of the 18th Ada-Europe International Conference on Reliable Software Technologies, Ada-Europe 2013, was held in Berlin, Germany, in June 2013. The 11 full papers presented were carefully reviewed and selected from various submissions. They are organized in topical sections on multi-core and distributed systems; Ada and Spark; dependability; and real-time systems.
Applied Algorithms
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Author : Christos Zaroliagis
language : en
Publisher: Springer Nature
Release Date : 2026-02-06
Applied Algorithms written by Christos Zaroliagis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-02-06 with Computers categories.
This book constitutes the refereed proceedings of the Third International Conference on Applied Algorithms, ICAA 2026, held in Kolkata, India, during January 7–9, 2026. The 33 full papers presented in this book were carefully reviewed and selected from 92 submissions. They focus on the design, analysis, implementation, and experimental evaluation of efficient algorithms and data structures aimed at solving practical, real-world problems.
Nasa Formal Methods
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Author : Alwyn Goodloe
language : en
Publisher: Springer
Release Date : 2012-03-30
Nasa Formal Methods written by Alwyn Goodloe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-30 with Computers categories.
This book constitutes the refereed proceedings of the Fourth International Symposium on NASA Formal Methods, NFM 2012, held in Norfolk, VA, USA, in April 2012. The 36 revised regular papers presented together with 10 short papers, 3 invited talks were carefully reviewed and selected from 93 submissions. The topics are organized in topical sections on theorem proving, symbolic execution, model-based engineering, real-time and stochastic systems, model checking, abstraction and abstraction refinement, compositional verification techniques, static and dynamic analysis techniques, fault protection, cyber security, specification formalisms, requirements analysis and applications of formal techniques.
Statistical Fault Localization And Causal Interactions
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Author : Shih-Feng Sun
language : en
Publisher:
Release Date : 2017
Statistical Fault Localization And Causal Interactions written by Shih-Feng Sun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Computer science categories.
Coverage-based statistical fault-localization (CBSFL) techniques have been proposed for characterizing the "suspiciousness" of program statements based on code-coverage profiles and PASS/FAIL labels for a set of test or operational executions. The resulting suspiciousness scores are typically intended to be used to rank statements for inspection by developers, on the assumption that statements which cause labeled failures will tend to receive high ranks. Many CBSFL metrics have been proposed. This dissertation examines two issues related to proposed CBSFL metrics. First, it examines the structure of some of the most effective of the proposed metrics, when they are expressed as expressions involving relatively simple probabilities. It is shown that these metrics have a common structure that makes it easier to understand their strengths and weaknesses. The second issue examined here is the impact, on the occurrence of observable program failures, of dynamic interactions between the execution of one program statement and the execution of another. To clarify this issue, event-based definitions of fault-revealing and fault-concealing interactions (FRIs and FCIs) in programs are presented and they are then related to both the theory of causal interactions developed by causal inference researchers and to characterizations of fault-interactions and failed error propagation developed by software researchers. It is shown that statistical tests developed to detect causal interactions are applicable to detecting FRIs and FCIs. A preliminary approach, based on causal interaction tests, is proposed for locating statements involved in both FRIs and FCIs.
Using Statistical Monitoring To Detect Failures In Internet Services
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Author : Emre Kiciman
language : en
Publisher:
Release Date : 2005
Using Statistical Monitoring To Detect Failures In Internet Services written by Emre Kiciman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Proceedings Of The Ieee International Symposium On Industrial Electronics
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Author :
language : en
Publisher:
Release Date : 2005
Proceedings Of The Ieee International Symposium On Industrial Electronics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Industrial electronics categories.
Localizing Faults In Numerical Software Using A Value Based Causal Model
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Author : Zhuofu Bai
language : en
Publisher:
Release Date : 2016
Localizing Faults In Numerical Software Using A Value Based Causal Model written by Zhuofu Bai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Computer science categories.
Abstract: Causal statistical fault localization (CSFL) techniques, which applies causal inference techniques to test-execution profiles and test outcomes, estimates the causal effect of individual program elements on the occurrence of failures, and have been found to be effective in localizing software faults. In most research on CSFL, execution dynamics have been characterized by code-coverage profiles that indicate which statements, branches, or paths were covered by an execution. This coverage-based CSFL has two potential problems: (1) causal effect estimation can be biased when an important precondition for causal inference, called positivity, is violated (2) it is poorly suited for localizing faults in numerical programs and subprograms having relatively few conditional branches. To solve the aforementioned problems, we first investigate the performance of Baah et al's causal regression model for fault localization when the positivity condition, for all t, x Pr[T=t|X=x]>0 is violated, where T is a coverage indicator for the target statement and X is the set of covariates used for confounding adjustment. Two kinds of positivity violations are considered: structural and random ones. We prove that random, but not structural nonpositivity may harm the performance of Baah et al's causal estimator. To address the problem of random nonpositivity, we propose a modification to the way suspiciousness scores are assigned. Empirical results are presented that indicate it improves the performance of Baah et al's technique. We also present a probabilistic characterization of Baah et al's estimator, which provides a more efficient way to compute it. Then we present two value-based causal inference models for localizing faults in numerical software. The first model is denoted NUMFL. NUMFL combines causal and statistical analyses to characterize the causal effects of individual numerical expressions on output errors. Given value-profiles for an expression's variables, NUMFL uses generalized propensity scores (GPSs) or covariate balancing propensity scores (CBPSs) to reduce confounding bias caused by confounding variables, which are the evaluation of other, faulty expressions. It estimates the average failure-causing effect (AFCE) of an expression using quadratic regression models fit within GPS or CBPS subclasses. We report on an empirical evaluation of NUMFL involving components from four Java numerical libraries, in which it was compared to five alternative statistical fault localization metrics. The results indicate that NUMFL is more effective than baseline techniques. We also found that NUMFL works fairly well with data from failing runs alone. The second model is based on Bayesian Additive Regression Trees (BART), which are due to Chipman et al. Instead of controlling confounding bias with propensity scores, we use a BART model to approximate the dose-response function (DRF) relating the treatment variable to the output errors, where treatment variable is the result of evaluating a numerical expression. Given a unit in the observational data set, we input it into the fitted BART model, and then increase the value of the treatment variable, but keep the confounding variables unchanged. The causal effect of treatment for that unit is estimated by the change in the output of the BART model. The average value of the estimated causal effect of each unit in the data set is the estimated AFCE of the expression. We compare the performance of BART model with that of NUMFL and five baseline techniques in an empirical evaluation. The result shows BART model is the most effect techniques overall.