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Annual International Conference on Software Analysis, Testing and Evolution (SATE)

作者： Ju, Xiaolin Chen, Xiang Jiang, Shujuan Qian, Junyan Nantong Univ Sch Comp Sci & Technol Nantong Peoples R China Nanjin Univ Sch Comp Sci & Technol Nanjing Jiangsu Peoples R China Guilin Univ Elect Technol Guanxi Key Lab Trusted Software Guilin Peoples R China China Univ Min & Technol Sch Comp Sci & Technol Xuzhou Peoples R China

ISBN: (纸本)9781538636879

Many fault localization approaches such as spectrum based fault localization(SBFL) generated a fault localization report based on which the programmer identifies the faults from corrected program entities. Unfortunately, the bug identification is quite tedious due to lack of sufficient context information. Furthermore, in the process of continuous searching for errors, the programmer's previous judgment makes no contribution for improving the efficiency of fault locating report. In this paper, we proposed an interactive debugging framework on which the programmer can iteratively identify faults with visualized heuristic graph. We first analyze the type of running information that is helpful for programmer's fault identification. The heuristic information is collected by program instrument, and modeled by program slicing techniques. We organized this information in the DOT format for visualization. In addition, we proposed an algorithm which can dynamically adjust the fault locating report using forward and backward slicing techniques based on the feedback of programmers. Furthermore, we proposed an enhanced algorithm that can adjust the fault locating report based on more than one feedback from programmers. Since the goal of fault-locating is to identify and fix faults in a program, our framework is more practical in program debugging with visualizing information.

关键词： interactive debugging fault localization heuristic information modeling software testing

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Towards Understanding interactive debugging 2

Towards Understanding Interactive Debugging

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IEEE International Conference on Software Quality, Reliability and Security (QRS)

作者： Petrillo, Fabio Soh, Zephyrin Khomh, Foutse Pimenta, Marcelo Freitas, Carla Gueheneuc, Yann-Gael Univ Fed Rio Grande do Sul Porto Alegre RS Brazil Ecole Polytech Montreal Montreal PQ Canada

ISBN: (纸本)9781509041275

debugging is a laborious activity in which developers spend lot of time navigating through code, looking for starting points, and stepping through statements. Yet, although debuggers exist for 40 years now, there have been few research studies to understand this important and laborious activity. Indeed, to perform such a study, researchers need detailed information about the different steps of the interactive debugging process. In this paper, to help research studies on debugging and, thus, help improving our understanding of how developers debug systems using debuggers, we present the Swarm Debug Infrastructure (SDI), with which practitioners and researchers can collect and share data about developers' interactive debugging activities. We assess the effectiveness of the SDI through an experiment that aims to understand how developers apply interactive debugging on five true faults found in JabRef, toggling breakpoints and stepping code. Our study involved five freelancers and two student developers performing 19 bug location sessions. We collect videos recording and data about 6 hours of effective debugging activities. The data includes 110 breakpoints and near 7,000 invocations. We process the collected videos and data to answer five research questions showing that (1) there is no correlation between the number of invocations (respectively the number of breakpoints toggled) during a debugging session and the time spent on the debugging task;rho = 0.039 (respectively 0.093). We also observed that (2) developers follow different debugging patterns and (3) there is no relation between numbers of breakpoints and expertise. However, (4) there is a strong negative correlation between time of the first breakpoint (rho = 0.637);and the time spent on the task, suggesting that when developers toggle breakpoints carefully, they complete tasks faster than developers who toggle breakpoints too quickly. We conclude that the SDI allows collecting and sharing debugging data that

关键词： Software Maintenance interactive debugging debugging Patterns

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interactive Patch Filtering as debugging Aid 37

Interactive Patch Filtering as Debugging Aid

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37th IEEE International Conference on Software Maintenance and Evolution (ICSME)

作者： Liang, Jingjing Ji, Ruyi Jiang, Jiajun Zhou, Shurui Lou, Yiling Xiong, Yingfei Huang, Gang Peking Univ Key Lab High Confidence Software Technol MoE Beijing Peoples R China Peking Univ Dept Comp Sci & Technol EECS Beijing Peoples R China Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Univ Toronto Toronto ON Canada

ISBN: (纸本)9781665428828

It is widely recognized that patches generated by program repair tools have to be correct to be useful. However, it is fundamentally difficult to ensure the correctness of the patches. Many tools generate only the patches that are highly likely to be correct by taking conservative strategies which inevitably limit the recall of APR approaches. While the recall of APR can potentially be improved by relaxing the requirement on precision, more incorrect patches may also be generated. In this paper, we conjecture that reviewing incorrect patches also helps developers to understand the bug, and with proper tool support, reviewing incorrect patches would at least not reduce the repair performance. To evaluate this, we propose an interactive patch filtering approach to facilitate developers in the patch review process via effectively filtering out groups of incorrect patches. We implemented the approach as an Eclipse plugin, InPaFer, and evaluated the effectiveness and usefulness with a mixed-method evaluation. The results show that our approach improves the repair performance of developers, with 62.5% more successfully repaired bugs and 25.3% less debugging time. In particular, even if all generated patches are incorrect, the performance of developers would not be significantly reduced, and could still be improved. Our work provides a new way of thinking for the APR research.

关键词： interactive debugging Patch filtering User study Program repair

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Interacting with interactive Fault Localization Tools 13

Interacting with Interactive Fault Localization Tools

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13th International Workshop on Automating Test Case Design, Selection and Evaluation (A-TEST)

作者： Horvath, Ferenc Balogh, Gergo Szatmari, Attila Sarhan, Qusay Idrees Vancsics, Bela Beszedes, Arpad Univ Szeged Dept Software Engn Szeged Hungary Univ Duhok Dept Comp Sci Duhok Iraq

ISBN: (纸本)9781450394529

Spectrum-Based Fault Localization (SBFL) is one of the most popular genres of Fault Localization (FL) methods among researchers. One possibility to increase the practical usefulness of related tools is to involve interactivity between the user and the core FL algorithm. In this setting, the developer provides feedback to the fault localization algorithm while iterating through the elements suggested by the algorithm. This way, the proposed elements can be influenced in the hope to reach the faulty element earlier (we call the proposed approach interactive Fault Localization, or iFL). With this work, we would like to propose a presentation of our recent achievements in this topic. In particular, we overview the basic approach, and the supporting tools that we implemented for the actual usage of the method in different contexts: iFL4Eclipse for Java developers using the Eclipse IDE, and CharmFL for Python developers using the PyCharm IDE. Our aim is to provide an insight into the practicalities and effectiveness of the iFL approach, while acquiring valuable feedback. In addition, with the demonstration we would like to catalyse the discussion with researchers on the topic.

关键词： spectrum-based fault localization interactive fault localization interactive debugging testing user feedback

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One step at a time: An efficient approach to query-based ontology debugging

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KNOWLEDGE-BASED SYSTEMS 2022年 251卷

作者： Rodler, Patrick Univ Klagenfurt Univ Str 65-67 Klagenfurt Austria

When ontologies reach a certain size and complexity, faults such as inconsistencies, unsatisfiable classes or wrong entailments are hardly avoidable. Locating the incorrect axioms that cause these faults is a hard and time-consuming task. Addressing this issue, several techniques for a semi-automatic fault localization in ontologies have been proposed and extensively studied. One class of these approaches involve a human expert who provides answers to system-generated queries about the intended (correct) ontology in order to reduce the possible fault locations. To suggest as informative questions as possible, existing methods draw on various algorithmic optimizations as well as heuristics. However, these computations are often based on certain assumptions about the interacting expert. In this work, we demonstrate that these assumptions might not always be adequate and discuss consequences of their violations. In particular, we characterize a range of expert types with different query answering behavior and show that existing approaches are far from achieving optimal efficiency for all of them. In addition, we find that the cost metric adopted by state-of-the-art techniques might not always be realistic and that a change of metric has a decisive impact on the best choice of query answering strategy. As a remedy, we suggest a new - and simpler - type of expert question that leads to a stable fault localization performance for all analyzed expert types and effort metrics, and has numerous further advantages over existing techniques. Moreover, we present an algorithm which computes and optimizes this new query type in worst-case polynomial time and which is fully compatible with existing concepts (e.g., query selection heuristics) and infrastructure (e.g., debugging user interfaces) in the field. Comprehensive experiments on faulty real-world ontologies attest that the new querying method is substantially and statistically significantly superior to existing techniques b

关键词： Ontology debugging Query -based ontology debugging interactive debugging Fault localization Sequential diagnosis Expert questions Ontology quality assurance Ontology repair Test-driven debugging Singleton query Model -based diagnosis Semantic Web User interaction Effort minimization Performance optimization Entailment Test cases Query computation Query selection One-step lookahead debugging cost criteria Query quality assessment Expert types Heuristics Knowledge -base debugging OntoDebug Protege

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Sequential model-based diagnosis by systematic search

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ARTIFICIAL INTELLIGENCE 2023年第1期323卷

作者： Rodler, Patrick Univ Klagenfurt Univ Str 65-67 Klagenfurt Austria

Model-based diagnosis aims at identifying the real cause of a system's malfunction based on a formal system model and observations of the system behavior. To discriminate between multiple fault hypotheses (diagnoses), sequential diagnosis approaches iteratively pose queries to an oracle to acquire additional knowledge about the diagnosed system. Depending on the system type, queries can capture, e.g., system tests, probes, measurements, or expert questions. As the determination of optimal queries is NP-hard, state-of-the-art sequential diagnosis methods rely on a myopic one-step-lookahead analysis which has proven to constitute a particularly favorable trade-off between computational efficiency and diagnostic effectivity. Yet, this solves only a part of the problem, as various sources of complexity, such as the reliance on costly reasoning services and large numbers of or not explicitly given query candidates, remain. To deal with such issues, existing approaches often make assumptions about the (i) type of diagnosed system, (ii) formalism to describe the system, (iii) inference engine, (iv) type of query to be of interest, (v) query quality criterion to be adopted, or (vi) diagnosis computation algorithm to be employed. Moreover, they (vii) often cannot deal with large or implicit query spaces or with expressive logics, or (viii) require inputs that cannot always be provided. As a remedy, we propose a novel one-step lookahead query computation technique for sequential diagnosis that overcomes the said issues of existing methods. Our approach (1) is based on a solid theory, (2) involves a systematic search for optimal queries, (3) can operate on implicit and huge query spaces, (4) allows for a two-stage optimization of queries (wrt. their number and cost), (5) is designed to reduce expensive logical inferences to a minimum, and (6) is generally applicable. The latter means that it can deal with any type of diagnosis problem as per Reiter's theory, is applicable with

关键词： Model-based diagnosis Sequential diagnosis Query-based debugging interactive debugging Combinatorial search Diagnostic decision-making Fault localization Measurement selection Knowledge-base debugging Ontologies Query computation Active learning Heuristics

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interactive Program debugging and Optimization for Directive-Based, Efficient GPU Computing

Interactive Program Debugging and Optimization for Directive...

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IEEE 28th International Parallel & Distributed Processing Symposium (IPDPS)

作者： Lee, Seyong Li, Dong Vetter, Jeffrey S. Oak Ridge Natl Lab Oak Ridge TN 37831 USA

ISBN: (纸本)9780769552071

Directive-based GPU programming models are gaining momentum, since they transparently relieve programmers from dealing with complexity of low-level GPU programming, which often reflects the underlying architecture. However, too much abstraction in directive models puts a significant burden on programmers for debugging applications and tuning performance. In this paper, we propose a directive-based, interactive program debugging and optimization system. This system enables intuitive and synergistic interaction among programmers, compilers, and runtimes for more productive and efficient GPU computing. We have designed and implemented a series of prototype tools within our new open source compiler framework, called Open Accelerator Research Compiler (OpenARC);OpenARC supports the full feature set of OpenACC V1.0. Our evaluation on twelve OpenACC benchmarks demonstrates that our prototype debugging and optimization system can detect a variety of translation errors. Additionally, the optimization provided by our prototype minimizes memory transfers, when compared to a fully manual memory management scheme.

关键词： interactive debugging performance optimization directive programming GPU OpenACC OpenARC

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Memory-limited model-based diagnosis ?

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ARTIFICIAL INTELLIGENCE 2022年 305卷 103681-103681页

作者： Rodler, Patrick Univ Klagenfurt A-9020 Klagenfurt Austria

Various model-based diagnosis scenarios require the computation of the most preferred fault explanations. Existing algorithms that are sound (i.e., output only actual fault explanations) and complete (i.e., can return all explanations), however, require exponential space to achieve this task. As a remedy, and to enable successful diagnosis both on memory-restricted devices and for memory-intensive problem cases, we propose two novel diagnostic search algorithms which build upon tried and tested techniques from the heuristic search domain. The first method, dubbed Recursive Best-First Hitting Set Search (RBF-HS), is based on Korf's well-known Recursive Best-First Search (RBFS) algorithm. We show that RBF-HS can enumerate an arbitrary predefined finite number of fault explanations in best-first order within linear space bounds, without sacrificing the desirable soundness or completeness properties. The second algorithm, called Hybrid Best-First Hitting Set Search (HBF-HS), is a hybrid between RBF-HS and Reiter's seminal HS-Tree. The idea is to find a trade-off between runtime optimization and a restricted space consumption that does not exceed the available memory. Notably, both suggested algorithms are generally applicable to any model-based diagnosis problem, regardless of the used (monotonic) logical language to describe the diagnosed system and of the used reasoning *** conducted extensive experiments on real-world benchmarks from the knowledge-based systems field, a domain where the features soundness, completeness, the best -first property as well as a general applicability are pivotal and where Reiter's HS-Tree is the predominantly used diagnostic search. The evaluation reveals that, when computing fault explanations minimal-cardinality-first, RBF-HS compared to HS-Tree reduces memory requirements substantially in most cases by up to several orders of magnitude, while also saving runtime in more than a third of the cases. When computing fault explanati

关键词： Hitting set computation Diagnosis Sound complete best-first diagnosis & nbsp computation Linear best-first search Linear best-first hitting set search Model-based diagnosis Fault localization Fault isolation Recursive best first search RBFS Heuristic search Memory-limited diagnosis search Reiters hitting set tree HS-tree Sequential diagnosis Combinatorial search Ontology debugging Ontology quality assurance Knowledge base debugging interactive debugging OntoDebug

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Using contextual knowledge in interactive fault localization

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EMPIRICAL SOFTWARE ENGINEERING 2022年第6期27卷 150-150页

作者： Horvath, Ferenc Beszedes, Arpad Vancsics, Bela Balogh, Gergo Vidacs, Laszlo Gyimothy, Tibor Univ Szeged Dept Software Engn Szeged Hungary Univ Szeged MTA SZTE Res Grp Artificial Intelligence Szeged Hungary

Tool support for automated fault localization in program debugging is limited because state-of-the-art algorithms often fail to provide efficient help to the user. They usually offer a ranked list of suspicious code elements, but the fault is not guaranteed to be found among the highest ranks. In Spectrum-Based Fault Localization (SBFL) - which uses code coverage information of test cases and their execution outcomes to calculate the ranks -, the developer has to investigate several locations before finding the faulty code element. Yet, all the knowledge she a priori has or acquires during this process is not reused by the SBFL tool. There are existing approaches in which the developer interacts with the SBFL algorithm by giving feedback on the elements of the prioritized list. We propose a new approach called iFL which extends interactive approaches by exploiting contextual knowledge of the user about the next item in the ranked list (e. g., a statement), with which larger code entities (e. g., a whole function) can be repositioned in their suspiciousness. We implemented a closely related algorithm proposed by Gong et al., called Talk. First, we evaluated iFL using simulated users, and compared the results to SBFL and Talk. Next, we introduced two types of imperfections in the simulation: user's knowledge and confidence levels. On SIR and Defects4J, results showed notable improvements in fault localization efficiency, even with strong user imperfections. We then empirically evaluated the effectiveness of the approach with real users in two sets of experiments: a quantitative evaluation of the successfulness of using iFL, and a qualitative evaluation of practical uses of the approach with experienced developers in think-aloud sessions.

关键词： Spectrum-based fault localization Automated debugging interactive debugging User simulation User study Think-aloud sessions

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Experiments with interactive Fault Localization Using Simulated and Real Users 36

Experiments with Interactive Fault Localization Using Simula...

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36th IEEE International Conference on Software Maintenance and Evolution (ICSME)

ISBN: (纸本)9781728156194

Fault localization is considered a difficult and time consuming activity. However, tool support for automated fault localization is still limited because state-of-the-art algorithms often fail to provide efficient help to the user. They usually offer a ranked list of suspicious code elements, but the fault is not guaranteed to be found among the highest ranks. In Spectrum-Based Fault Localization (SBFL) - which uses code coverage information of test cases and their execution outcomes to calculate the ranks -, the developer has to investigate several locations before finding the faulty code element. Yet, all the knowledge she a priori has or acquires during this process is not reused by the SBFL tool. We propose an approach in which the developer interacts with the SBFL algorithm by giving feedback on the elements of the prioritized list. We exploit contextual knowledge of the user about the next item in the ranked list (e.g., a statement), with which larger code entities (e.g., a whole function) can be repositioned in their suspiciousness. First, we evaluated the approach using simulated users incorporating two types of imperfections, their knowledge and confidence levels. On SIR and Defects4J, results showed notable improvements in fault localization efficiency, even with strong user imperfections. We then empirically evaluated the effectiveness of the approach with real users, which also showed promising results.

关键词： Spectrum-Based Fault Localization automated debugging interactive debugging user feedback user simulation user imperfection user study

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