A Survey of Algorithmic Debugging

Caballero, Rafael; Riesco, Adrián; Silva, Josep

doi:10.1145/3106740

Cited by 24 publications

(9 citation statements)

References 77 publications

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“…Our system uses the principles of a technique called Algorithmic Debugging [10] to identify the methods that should be assessed (and corrected) first.…”

Section: Methodsmentioning

confidence: 99%

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Semiautomatic generation and assessment of Java exercises in engineering education

Insa

Pérez

Silva

et al. 2020

Comp Applic In Engineering

Self Cite

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Continuous assessment is essential in education. It should be an integral part of education that provides immediate feedback to students. Unfortunately, the assessment of programming source code is still a hand‐operated and error‐prone task, and can take weeks before the student gets feedback. This study presents a semiautomatic code assessment method able to automatically apply black‐box assessment (which relies on the comparison of input‐output pairs) and white‐box assessment (which relies on checking different source code properties). The method proposed is a general‐purpose assessment system that was originally designated to be used in engineering education, but that can be used in other educational contexts to assist the assessment of any Java programming assignments or exams. The main advantage of this system is that the assessment made is quicker, exhaustive, and objective; and it does not produce false positives. After the application of this method over two years in several real university courses, we have released a public and free implementation. An empirical evaluation of this system estimates that the amount of assessment work automatically done by the tool is over 48%. Additionally, the system has been used to measure the average subjective influence (i.e., assessment errors) introduced by teachers when they assess exams manually.

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“…Our system uses the principles of a technique called Algorithmic Debugging [10] to identify the methods that should be assessed (and corrected) first.…”

Section: Methodsmentioning

confidence: 99%

“…">Automatic detection of the assessment order. The system uses Algorithmic Debugging [10] to detect the order of assessment. Collaborative assessment.…”

Section: Introductionmentioning

confidence: 99%

Semiautomatic generation and assessment of Java exercises in engineering education

Insa

Pérez

Silva

et al. 2020

Comp Applic In Engineering

Self Cite

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“…Many interactive debugging techniques [43], [47]- [49], [53]- [56] leveraged user feedback to localize faults. Algorithmic debugging [53] built a tree of method invocations for a failed test, and then repeatedly asked developers questions to prune the tree for fault localization.…”

Section: Interactive Debuggingmentioning

confidence: 99%

Interactive Patch Filtering as Debugging Aid

Liang¹,

Ji²,

Jiang³

et al. 2021

Preprint

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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 mixedmethod 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.

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“…However, this debugger is often very difficult to use and to understand. Another approach to the debugging problem is the use of algorithmic debugging [42] and declarative debuggers (see [43][44][45]) like Freja [46,47] or Buddha [48,49]. Both of them try to find the faulty code by asking some automatic questions to the programmers and by analyzing their answers.…”

Section: Introductionmentioning

confidence: 99%

A Semantic Framework to Debug Parallel Lazy Functional Languages

et al. 2020

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It is not easy to debug lazy functional programs. The reason is that laziness and higher-order complicates basic debugging strategies. Although there exist several debuggers for sequential lazy languages, dealing with parallel languages is much harder. In this case, it is important to implement debugging platforms for parallel extensions, but it is also important to provide theoretical foundations to simplify the task of understanding the debugging process. In this work, we deal with the debugging process in two parallel languages that extend the lazy language Haskell. In particular, we provide an operational semantics that allows us to reason about our parallel extension of the sequential debugger Hood. In addition, we show how we can use it to analyze the amount of speculative work done by the processes, so that it can be used to optimize their use of resources.

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A Survey of Algorithmic Debugging

Cited by 24 publications

References 77 publications

Semiautomatic generation and assessment of Java exercises in engineering education

Semiautomatic generation and assessment of Java exercises in engineering education

Interactive Patch Filtering as Debugging Aid

A Semantic Framework to Debug Parallel Lazy Functional Languages

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