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VFL: Variable-based fault localization

INFORMATION AND software TECHNOLOGY 2019年 107卷 179-191页

作者： Kim, Jeongho Kim, Jindae Lee, Eunseok Sungkyunkwan Univ Suwon South Korea HKUST Sai Kung Clear Water Bay Hong Kong Peoples R China

Context: Fault localization is one of the most important debugging tasks. Hence, many automatic fault localization techniques have been proposed to reduce the burden on developers for such tasks. Among them, Spectrum-based Fault Localization (SFL) techniques leverage coverage information and localize faults based on the coverage difference between the failed and passed test cases. Objective: However, such SFL techniques cannot localize faults effectively when coverage differences are not clear. To address this issue and improve the fault localization performance of the SFL techniques, we propose a Variable-based Fault Localization (VFL) technique. Method: The VFL technique identifies suspicious variables and uses them to generate a ranked list of suspicious source code lines. Since it only requires additional information about variables that are also available in the SFL techniques, the proposed technique is lightweight and can be used to improve the performance of existing the SFL techniques. Results: In an evaluation with 224 real Java faults and 120 C faults, the VFL technique outperforms the SFL techniques using the same similarity coefficient. The average Exam scores of the VFL techniques are reduced by more than 55% compared to the SFL techniques, and the VFL techniques localize faults at a lower rank than the SFL techniques for about 73% of the 344 faults. Conclusion: We proposed a novel variable-based fault localization technique for more effective debugging. The VFL technique has better performance than the existing techniques and the results were more useful for actual fault localization tasks. In addition, this technique is very lightweight and scalable, so it is very easy to collaborate with other fault localization techniques.

关键词： software debugging software testing Spectrum-based fault localization Variable-based fault localization Suspicious variable

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An optimal mutation execution strategy for cost reduction of mutation-based fault localization

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INFORMATION SCIENCES 2018年 422卷 572-596页

作者： Liu, Yong Li, Zheng Zhao, Ruilian Gong, Pei Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China

Identifying faulty program entities has been recognized as one of the most expensive, tedious and time-consuming processes in software debugging activity. Fault localization techniques are designed to assist developers in locating faults by giving a ranking of the probability that program entities incur failures. Mutation-based fault localization (MBFL) is a recently proposed fault localization approach via mutation analysis, which uses the location of mutants to identify the faulty statements. With improved effectiveness, the MBFL also brings huge execution cost. To reduce the execution cost of MBFL technique, this paper proposes a dynamic mutation execution strategy (DMES) to prioritize the execution on both mutants and test cases. As fewer mutants and test cases are executed with DMES, the whole process will become faster and the cost will be decreased. At the same time, it is proved that the fault localization accuracy of MBFL with DMES is the same as that of the original MBFL. Furthermore, this paper discusses the lowest mutation execution cost of MBFL in theory and gives a quick solution to compute the theoretical minimal mutation execution cost of MBFL in the case of keeping fault localization accuracy non-decreasing. The empirical studies show that MBFL with the dynamic strategy proposed in this paper can reduce mutant-test execution cost by 32.4-87% and is close to the theoretical optimal cost. Furthermore, the additional run time required by utilizing our strategy is minimum and can be ignored. (C) 2017 Elsevier Inc. All rights reserved.

关键词： software debugging Mutation-based fault localization Mutation cost reduction Dynamic mutation execution strategy

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Automated source-level error localization in hardware designs

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IEEE DESIGN & TEST OF COMPUTERS 2006年第1期23卷 8-19页

作者： Peischl, B Wotawa, F Graz Univ Technol IST Graz Austria

Recent achievements in formal verification techniques allow for fault detection even in large real-world designs. Tool support for localizing the faulty statements is critical, because it reduces development time and overall project costs. Automated source-level debugging and a new and novel debugging model allow for source-level debugging of large VHDL designs at the granularity of statements and expressions. This technique is fully automated and does not require that an engineer be familiar with formal verification techniques.

关键词： Design Error Diagnosis software debugging Model Based Diagnosis Fault Localization

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Optimizing Mutation-Based Fault Localization Through Contribution-Based Test Case Reduction

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INTERNATIONAL JOURNAL OF software ENGINEERING AND KNOWLEDGE ENGINEERING 2024年第10期34卷 1537-1564页

作者： Wang, Haifeng Yang, Kun Wu, Tong Ctr Adv Metering Infrastruct Natl Inst Metrol Beijing 100029 Peoples R China

Fault localization is an expensive phase of software debugging processes. Although Mutation-based Fault Localization (MBFL) is a promising technique, its computational cost remains high due to the extensive mutation executions involved in mutation analysis. Previous studies have primarily focused on reducing costs by decreasing the mutant numbers and optimizing the execution, yielding promising results. However, test case reduction has also proven to be effective in reducing costs in MBFL. In this paper, we propose an approach called Contribution-Based Test Case Reduction (CBTCR) aimed at enhancing MBFL efficiency. CBTCR assesses the contribution value of each test case and selects them accordingly. The reduced test suite is then used for mutant execution. We evaluate CBTCR on 543 real software faults from Defects4J benchmark. Results show that CBTCR outperforms other MBFL test case reduction strategies (e.g. FTMES, IETCR), in terms of the Top-N and MAP metrics. Moreover, CBTCR achieves an average cost reduction of 87.06%, while maintaining accuracy comparable to those of the original MBFL techniques. This research paper presents an innovative and effective solution for optimizing MBFL, which can significantly reduce the cost and time required for software debugging.

关键词： software debugging fault localization mutation-based fault localization test case reduction

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Locating faults with program slicing: an empirical analysis

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EMPIRICAL software ENGINEERING 2021年第3期26卷 1-45页

作者： Soremekun, Ezekiel Kirschner, Lukas Bohme, Marcel Zeller, Andreas Univ Luxembourg SnT Luxembourg Luxembourg CISPA Helmholtz Ctr Informat Secur Saarbrucken Germany Monash Univ Melbourne Vic Australia

Statistical fault localization is an easily deployed technique for quickly determining candidates for faulty code locations. If a human programmer has to search the fault beyond the top candidate locations, though, more traditional techniques of following dependencies along dynamic slices may be better suited. In a large study of 457 bugs (369 single faults and 88 multiple faults) in 46 open source C programs, we compare the effectiveness of statistical fault localization against dynamic slicing. For single faults, we find that dynamic slicing was eight percentage points more effective than the best performing statistical debugging formula;for 66% of the bugs, dynamic slicing finds the fault earlier than the best performing statistical debugging formula. In our evaluation, dynamic slicing is more effective for programs with single fault, but statistical debugging performs better on multiple faults. Best results, however, are obtained by a hybrid approach: If programmers first examine at most the top five most suspicious locations from statistical debugging, and then switch to dynamic slices, on average, they will need to examine 15% (30 lines) of the code. These findings hold for 18 most effective statistical debugging formulas and our results are independent of the number of faults (i.e. single or multiple faults) and error type (i.e. artificial or real errors).

关键词： software engineering software debugging software testing Automated fault localization Program slicing Statistical debugging

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Maintaining component-based systems

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IEEE software 1998年第4期15卷 22-+页

作者： Voas, J RST Corp Sterling VA 20165 USA

As we continue to move toward component-based software engineering, software development will become more like traditional manufacturing: developers will code less and design and integrate more. Voas argues that to reap the benefits of component-based development-reduced time to market, more user choice, and lower costs-we must rethink our software maintenance strategies. He gives a wide-ranging overview of the maintenance challenges raised by component-based development.

关键词： software maintenance Application software software debugging Costs Documentation software engineering Programming Manufacturing Time to market software systems

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An Analysis on the Negative Effect of Multiple-Faults for Spectrum-Based Fault Localization

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IEEE ACCESS 2019年 7卷 2327-2347页

作者： Yan Xiaobo Bin Liu Wang Shihai Beihang Univ Sci & Technol Reliabil & Environm Engn Lab Beijing 100191 Peoples R China

This paper aims to investigate the negative effects of multiple-faults on spectrum-based fault localization (SBFL). Previously, researchers validated the fact that the occurrence of multiple-faults could have a significant negative impact on fault localization. However, a very little current research addresses the degree of these impacts through a systemic analysis. Furthermore, the fundamental causes underlying that negative impact have not been investigated and are not fully understood. We conducted experiments on fourteen real-life open source programs to explore and possibly solve these problems. Our results indicate that: 1) although multiple-faults generally do have a negative impact on fault localization, different fault localizations displayed various levels of robustness against that negative impact;2) restoring pass/fail fault interactions only has a modest effect on that negative impact;3) our investigation of twelve Fault Localization Interactions (FLI) shows that there is a dominant FLI-1 interaction in multiple-fault programs which should be responsible for that negative impact;4) restoring FLI-1 can significantly improve the performance of both SBFL and parallel debugging techniques;and 5) furthermore, this paper practically validated the revised Kendall Tau distance as an efficient measure to help locate test cases, which have triggered FLI-1. Based on the revised Kendall Tau distance, a fast search algorithm has been suggested to locate FLI-1 test cases. It is expected that this paper can provide some insight into the fundamental causes of multiple-faults' negative impact on fault localization and drive the development of more efficient fault localization techniques to improve the identification and handling of multiple-faults.

关键词： Fault localization software debugging multiple-faults

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CONTROLLER REDUCTION - CONCEPTS AND APPROACHES

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1989年第8期34卷 802-812页

作者： ANDERSON, BDO LIU, Y Department of Systems Engineering Research School of Physical Sciences Australian National University Canberra ACT Australia

The problem of passing from a linear time-invariant high-order controller designed for a linear time-invariant plant (of presumably high order) to a low-order approximation of the controller is discussed. The approximation problem is often best posed as a frequency-weighted L/sub infinity / approximation problem. Many different controller representations are possible, giving different performances of the various reduction algorithms.< >

关键词： Performance analysis Equations Hardware Computer bugs software debugging Design methodology Optimization methods Displays Control design Packaging

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DDImage: an image reduction based approach for automatically explaining black-box classifiers

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EMPIRICAL software ENGINEERING 2024年第5期29卷 129-129页

作者： Jiang, Mingyue Tang, Chengjian Zhang, Xiao-Yi Zhao, Yangyang Ding, Zuohua Zhejiang Sci Tech Univ Hangzhou Peoples R China Univ Sci & Technol Beijing Beijing Peoples R China

Due to the prevalent application of machine learning (ML) techniques and the intrinsic black-box nature of ML models, the need for good explanations that are sufficient and necessary towards locally interpreting a model's prediction has been well recognized and emphasized. Existing explanation approaches, however, favor either the sufficiency or necessity. To fill this gap, in this paper, we propose an approach for generating local explanations that are both sufficient and necessary. Our approach, DDImage, automatically produces local explanations for ML-based image classifiers in a post-hoc way. The core idea behind DDImage is to discover an appropriate explanation by debugging the given input image via a series of image reductions, with respect to the sufficiency and necessity properties. Evaluation of DDImage using publicly available datasets and popular classification models reveals its effectiveness and efficiency. Compared with three state-of-the-art approaches, DDImage demonstrates a superior performance in producing small-sized explanations preserving both sufficiency and necessity, and it also shows promising stability and efficiency. We also identify the impact of segmentation granularity, reveal the performance variance for different target models, and further show that our approach is applicable across different problem domains.

关键词： Machine learning Explainability software debugging

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Using Process and Motivation Data to Predict the Quality With Which Preservice Teachers Debugged Higher and Lower Complexity Programs

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IEEE TRANSACTIONS ON EDUCATION 2021年第4期64卷 374-382页

作者： Belland, Brian R. Kim, ChanMin Zhang, Anna Y. Baabdullah, Afaf A. Lee, Eunseo Penn State Univ Dept Educ Psychol Counseling & Special Educ University Pk PA 16802 USA Penn State Univ Dept Learning & Performance Syst University Pk PA 16802 USA King Saud Univ Dept Curriculum & Instruct Riyadh 11451 Saudi Arabia

Contribution: This study indicates that supporting debugging processes is a strong method to improve debugging outcome quality among preservice, early childhood education (ECE) teachers. Background: Central to preparing ECE teachers to teach computer science is helping them learn to debug. Little is known about how ECE teachers' motivation and debugging process quality contributes to debugging outcome quality. Research Questions: How do debugging process and motivation variables predict the quality with which participants debug lower and higher complexity programs? Method: A Bayesian multiple linear regression model with debugging process and motivation variables as predictors was used to predict debugging outcome quality. An inverse gamma prior distribution for sigma(2) and uniform prior distribution for Betas was used. Findings: The strongest positive predictor of debugging outcome quality for both the lower complexity and higher complexity debugging task was debugging process quality.

关键词： debugging Computer bugs Task analysis Complexity theory Programming profession Education Encoding Computing education regression analysis software debugging teacher learning

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