VarFix: balancing edit expressiveness and search effectiveness in automated program repair

Wong, Chu-Pan; Santiesteban, Priscila; Kästner, Christian; Goues, Claire Le

doi:10.1145/3468264.3468600

Cited by 30 publications

(7 citation statements)

References 54 publications

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“…In this paper, we will assume an APR approach that includes a patch ranking step where valid patches collected are ranked before being presented to the user. This approach is in line with recent works [10,11,15,16,26,43,60,62,70]. In the first part of this paper, we will describe in more detail the relationship between fuzzing and APR.…”

Section: Introductionsupporting

confidence: 71%

Automated Program Repair from Fuzzing Perspective

Kim,

Han,

Khamit

et al. 2023

Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis

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In this work, we present a novel approach that connects two closelyrelated topics: fuzzing and automated program repair (APR). The paper is divided into two parts. In the first part, we describe the similarities between fuzzing and APR both of which can be viewed as a search problem. In the second part, we introduce a new patchscheduling algorithm called Casino, which is designed from a fuzzing perspective to enhance search efficiency. Our experiments demonstrate that Casino outperforms existing algorithms. We also promote open science by sharing SimAPR, a simulation tool that can be used to evaluate new patch-scheduling algorithms. CCS CONCEPTS• Software and its engineering → Software testing and debugging; Automatic programming.

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Section: Introductionsupporting

confidence: 71%

Automated Program Repair from Fuzzing Perspective

Kim,

Han,

Khamit

et al. 2023

Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis

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“…APR research should consider the benefits of providing multiple fixes to a single bug: Our survey respondents had a strong preference for choosing between multiple fixes. There is some APR research that takes this approach (for example, [57], [58], [59]) -our results suggest that this may be a promising future direction, although more work is needed to identify what the ideal number of fixes for developers to choose from is.…”

Section: E Recommendations For Apr Tool Designmentioning

confidence: 97%

How do Developers Really Feel About Bug Fixing? Directions for Automatic Program Repair

Winter

Bowes

Counsell

et al. 2023

IIEEE Trans. Software Eng.

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Automatic program repair (APR) is a rapidly advancing field of software engineering that aims to supplement or replace manual bug fixing with an automated tool. For APR to be successfully adopted in industry, it is vital that APR tools respond to developer needs and preferences. However, very little research has considered developers' general attitudes to APR or developers' current bug fixing practices (the activity APR aims to replace). This paper responds to this gap by reporting on a survey of 386 software developers about their bug finding and fixing practices and experiences, and their instinctive attitudes towards APR. We find that bug finding and fixing is not necessarily as onerous for developers as has often been suggested, being rated as more satisfying than developers' general work. The fact that developers derive satisfaction and benefit from bug fixing indicates that APR adoption is not as simple as APR replacing an unwanted activity. When it comes to potential APR approaches, we find a strong preference for developers being kept in the loop (for example, choosing between different fixes or validating fixes) as opposed to a fully automated process. This suggests that advances in APR should be careful to consider the agency of the developer, as well as what information is presented to developers alongside fixes. It also indicates that there are key barriers related to trust that would need to be overcome for full scale APR adoption, supported by the fact that even those developers who stated that they were positive about APR listed several caveats and concerns. We find very few statistically significant relationships between particular demographic variables (for example, developer experience, age, education) and key attitudinal variables, suggesting that developers' instinctive attitudes towards APR are little influenced by experience level but are held widely across the developer community.

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“…ACS 9 uses the heuristic guidance of the frequently used predicates to sort the ingredients. VarFix 48 generalizes plausible patches to meta‐programs and employs variational execution to speed up the patch search process.…”

Section: Related Workmentioning

confidence: 99%

Enhanced evolutionary automated program repair by finer‐granularity ingredients and better search algorithms

Wang,

Liu,

Lin

et al. 2023

J Software Evolu Process

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SummaryBug repair is time consuming and tedious, which hampers software maintenance. To alleviate the burden, automated program repair (APR) is proposed and has been fruitful in the last decade. Evolutionary repair is the seminal work of this field and proliferated a family of approaches. The performance of evolutionary repair approaches is affected by two main factors: (1) search space, which defines all possible patches, and (2) search algorithms, which navigate the space. Although recent approaches have achieved remarkable progress, the main challenges of the two factors still remain. On one hand, the different kinds of search space are very coarse for containing correct patches. On the other hand, the search process guided by genetic algorithms is inefficient in finding the correct patches in an appropriate time budget. In this paper, we propose MicroRepair, a new evolutionary repair approach to address the two challenges. Rather than finding statement‐level patches like existing genetic repair approaches, MicroRepair enlarges the search space by breaking the statements into finer‐granularity ingredients that consist of AST leaves. As the search space grows exponentially, the former search algorithms may become inefficient in navigating the larger space. We utilize the best multiobjective search algorithm selected from our empirical comparison of a set of search algorithms. At last, we find redundancies search in the existing genetic process, and we further design a history‐aware search strategy to accelerate the process.We evaluated MicroRepair on 224 bugs of real‐world from the benchmark Defects4J and compared it with several state‐of‐the‐art repair approaches. The evaluation results show that MicroRepair correctly repaired 26 bugs with a precision of 62%, which significantly outperforms the state‐of‐the‐art evolutionary APR approaches in terms of precision. Moreover, the history‐aware search boosts the repair execution speed by 4% on average.

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VarFix: balancing edit expressiveness and search effectiveness in automated program repair

Cited by 30 publications

References 54 publications

Automated Program Repair from Fuzzing Perspective

Automated Program Repair from Fuzzing Perspective

How do Developers Really Feel About Bug Fixing? Directions for Automatic Program Repair

Enhanced evolutionary automated program repair by finer‐granularity ingredients and better search algorithms

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