Interactive Code Review for Systematic Changes

Zhang, Tianyi; Song, Myoungkyu; Pinedo, Joseph; Kim, Miryung

doi:10.1109/icse.2015.33

Cited by 46 publications

(40 citation statements)

References 37 publications

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“…However, they do not lift a code template to summarize the commonalities and variations between similar code. Several techniques construct code templates for the purpose of code search [66] or code transformation [67]. Glassman et al design an interactive visualization called EXAMPLORE to help developers comprehend hundreds of similar but different API usages in GitHub [68].…”

Section: Related Workmentioning

confidence: 99%

Analyzing and Supporting Adaptation of Online Code Examples

Zhang

Yang

Lopes

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)

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Developers often resort to online Q&A forums such as Stack Overflow (SO) for filling their programming needs.Although code examples on those forums are good starting points, they are often incomplete and inadequate for developers' local program contexts; adaptation of those examples is necessary to integrate them to production code. As a consequence, the process of adapting online code examples is done over and over again, by multiple developers independently. Our work extensively studies these adaptations and variations, serving as the basis for a tool that helps integrate these online code examples in a target context in an interactive manner.We perform a large-scale empirical study about the nature and extent of adaptations and variations of SO snippets. We construct a comprehensive dataset linking SO posts to GitHub counterparts based on clone detection, time stamp analysis, and explicit URL references. We then qualitatively inspect 400 SO examples and their GitHub counterparts and develop a taxonomy of 24 adaptation types. Using this taxonomy, we build an automated adaptation analysis technique on top of GumTree to classify the entire dataset into these types. We build a Chrome extension called EXAMPLESTACK that automatically lifts an adaptation-aware template from each SO example and its GitHub counterparts to identify hot spots where most changes happen. A user study with sixteen programmers shows that seeing the commonalities and variations in similar GitHub counterparts increases their confidence about the given SO example, and helps them grasp a more comprehensive view about how to reuse the example differently and avoid common pitfalls.

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Section: Related Workmentioning

confidence: 99%

Analyzing and Supporting Adaptation of Online Code Examples

Zhang

Yang

Lopes

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)

Self Cite

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“…When comparing

M_{i}

and

M_{j}

, our approach generalizes the names of identifiers with abstract variables (eg, variables, qualifier values, fields, and method parameters) to create a generalized program comparison that does not depend on concrete identifiers. This generalization technique was used in previous works and achieved a high performance in distinguishing if 2 code fragments are relevant. We define the similarity

scriptS

between

M_{i}

and

M_{j}

as follows:

scriptS = 1 - \frac{italicLevenshteinDistance false(M_{i}, M_{j} false)}{\max false(false| M_{i} false|, false| M_{j} false| false)} .

…”

Section: Pattern‐based Clone Refactoring Inspectionmentioning

confidence: 99%

Clone refactoring inspection by summarizing clone refactorings and detecting inconsistent changes during software evolution

Chen

Kwon

Song

2018

J Software Evolu Process

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It has been broadly assumed that removing code clones by refactorings would solve the problems of code duplication. Despite recent empirical studies on the benefit of refactorings, contradicting evidence shows that it is often difficult or impossible to remove clones by using standard refactoring techniques. Developers cannot easily determine which clones can be refactored or how they should be maintained scattered throughout a large code base in evolving systems. We propose pattern‐based clone refactoring inspection (PRI), a technique for managing clone refactorings. PRI summarizes refactorings of clones and detects clones that are not consistently refactored. To help developers refactor these anomalies, PRI also visualizes clone evolution and refactorings and fixes refactoring anomalies to prevent the clone group from being left in an inconsistent state. We evaluated PRI on 6 open‐source projects and showed that it identifies clone refactorings with 94.1% accuracy and detects inconsistent refactorings with 98.4% accuracy, tracking clone change histories. In a study with 10 student developers, the participants reported that flexible PRI's summarization and detection features can be valuable for novice developers to learn about refactorings to clones. These results show that PRI should improve developer productivity in inspecting clone refactorings distributed across multiple files in evolving systems.

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“…Zhang et al [20] developed a patch inspection tool to help reviewers more easily understand the impact of a code change.…”

Section: Helping Reviewersmentioning

confidence: 99%

Will it pass? Predicting the outcome of a source code review

2018

Turk J Elec Eng & Comp Sci

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It has been observed that allowing source code changes to be made only after source code reviews has a positive impact on the quality and lifetime of the resulting software. In some cases, code review processes take quite a long time and this negatively affects software development costs and employee job satisfaction. Establishing mechanisms that predict what kind of feedback reviewers will provide and what revisions they will ask for can reduce the number of times this problem occurs. Thanks to such mechanisms, developers can improve the maturity of their code change requests before the review process starts. In this way, when they start the review, the process may advance quickly and more smoothly. In this study, as a first step towards this goal, we developed a mechanism to identify whether a change proposal would require any revisions or not for approval.

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Interactive Code Review for Systematic Changes

Cited by 46 publications

References 37 publications

Analyzing and Supporting Adaptation of Online Code Examples

Analyzing and Supporting Adaptation of Online Code Examples

Clone refactoring inspection by summarizing clone refactorings and detecting inconsistent changes during software evolution

Will it pass? Predicting the outcome of a source code review

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