Toward introducing automated program repair techniques to industrial software development

Naitou, Keigo; Tanikado, Akito; Matsumoto, Shinsuke; Higo, Yoshiki; Kusumoto, Shoichi; Kirinuki, Hiroyuki; Kurabayashi, Toshiyuki; Tanno, Haruto

doi:10.1145/3196321.3196358

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…"present" industrial practices. However, it is widely accepted that, just like any research field, many SE researchers conduct "discovery" (ground-breaking) type of research activities, i.e., research which is not motivated by the "current" challenges in the software industry, but rather presenting ground-breaking new approaches to SE which could or would possibly improve SE practices in future, e.g., research on automated program repair which took many years to be gradually used by industry (Naitou et al 2018). In such cases, the research work and the paper would be considered of practical relevance, with the notion of "future" focus, i.e., research with potential practical relevance in future.…”

Section: Our Definition Of Practical Relevance For Se Researchmentioning

confidence: 99%

Practical relevance of software engineering research: synthesizing the community’s voice

2020

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Software engineering (SE) research should be relevant to industrial practice. There have been regular discussions in the SE community on this issue since the 1980's, led by pioneers such as Robert Glass. As we recently passed the milestone of "50 years of software engineering", some recent positive efforts have been made in this direction, e.g., establishing "industrial" tracks in several SE conferences. However, many researchers and practitioners believe that we, as a community, are still struggling with research relevance and utility. The goal of this paper is to synthesize the evidence and experience-based opinions shared on this topic so far in the SE community, and to encourage the community to further reflect and act on the research relevance. For this purpose, we have conducted a Multi-vocal Literature Review (MLR) of 54 systematically-selected sources (papers and non peer-reviewed articles). Instead of relying on and considering the individual opinions on research relevance, mentioned in each of the sources, the MLR aims to synthesize and provide the "holistic" view on the topic. The highlights of our MLR findings are as follows. The top three root causes of low relevance, discussed in the community, are: (1) Researchers having simplistic views (or wrong assumptions) about SE in practice; (2) Lack of connection with industry; and (3) Wrong identification of research problems. The top three suggestions for improving research relevance are: (1) Using appropriate research approaches such as action-research; (2) Choosing relevant (practical) research problems; and (3) Collaborating with industry. By synthesizing all the discussions on this important topic so far, this paper aims to encourage further discussions and actions in the community to increase our collective efforts to improve the research relevance. Furthermore, we raise the need for empirically-grounded and rigorous studies on the relevance problem in SE research, as carried out in other fields such as management science.

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Section: Our Definition Of Practical Relevance For Se Researchmentioning

confidence: 99%

Practical relevance of software engineering research: synthesizing the community’s voice

2020

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“…Martinez et al and Barr et al both verified its validity by analyzing thousands of past commits [11,12]: between 3% and 17% of commits are only composed of existing code. Recently, it has been reported that a redundancy-based approach successfully scales to an industrial project [17].…”

Section: B Overview Of Redundancy-based Program Repairmentioning

confidence: 99%

The Remarkable Role of Similarity in Redundancy-based Program Repair

Chen¹,

Monperrus²

2018

Preprint

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Recently, there have been original attempts to use the concept of "code similarity" in program repair, suggesting that similarity analysis has an important role in the repair process. However, there is no dedicated work to characterize and quantify the role of similarity in redundancy-based program repair, where the patch is composed from source code taken from somewhere else. This is where our paper makes a major contribution: we perform a deep and systematic analysis of the role of code similarity during the exploration of the repair search space. We define and set up a large-scale experiment based on four code similarity metrics that capture different similarities: character, token, semantic and structure similarity. Overall, we have computed 56 million similarity score over 15 million source code components. We show that with similarity analysis, at least 90% of search space can be ignored to find the correct patch. Code similarity is capable of ranking the correct repair ingredient first in 4 -33 % of the considered cases.

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Experience Report: How Effective is Automated Program Repair for Industrial Software?

Noda

Nemoto

Tanida

et al. 2020

2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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Toward introducing automated program repair techniques to industrial software development

Cited by 5 publications

References 18 publications

Practical relevance of software engineering research: synthesizing the community’s voice

Practical relevance of software engineering research: synthesizing the community’s voice

The Remarkable Role of Similarity in Redundancy-based Program Repair

Experience Report: How Effective is Automated Program Repair for Industrial Software?

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