Decomposing Composite Changes for Code Review and Regression Test Selection in Evolving Software

Guo, Bo; Kwon, Youngwoo; Song, Myoungkyu

doi:10.1007/s11390-019-1917-9

Cited by 8 publications

(12 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From the 29 offline evaluations, most (51.72%) focuses on reviewer recommenders. Approaches to support code checking are the second most common (34.48%) [109,114,117,119,138,141,142,145,148,143]. From the remaining works, two target review prioritization support [135,137], and the last two studies evaluate feedback provision assistance [21] and a variation in the MCR process [150].…”

Section: Methodsmentioning

confidence: 99%

“…Yu et al [106], Khandelwal et al [149], Müller et al [107], Balachandran [108], Yang et al [36], Barnett et al [109], Rahman et al [110], Zhang et al [111], Rahman et al [21], Thongtanunam et al [22], Tao and Kim [114], Baum et al [150], Duley et al [117], Peng et al [151], Hannebauer et al [152], Ge et al [119], Zanjani et al [120], Thongtanunam et al [5], Xia et al [128], Ouni et al [6], Menarini et al [131], Xia et al [134], Aman [135], Fejzer et al [136], Fan et al [137], Luna Freire et al [138], Mizuno and Liang [153], Runeson and Wohlin [154], Asthana et al [140], Huang et al [141], Wang et al [142], Huang et al [143], Wen et al [144], Hanam et al [145], Liao et al [146], Jiang et al [147], Guo et al [148] Foundational Study…”

Section: Evaluationsmentioning

confidence: 99%

“…Support for code checking has been focused on providing information to ease the manual work of reviewers, mainly the understanding of a change. To provide this support, the main strategies presented in the studies are (i) provide visualizations of code changes [109,138,114,119,111,117,141,142,148,143], (ii) present properties associated with them [131,121,130], and (iii) support the analysis of change impact [133,145].…”

Section: Code Checkingmentioning

confidence: 99%

“…Some proposals assume that a change can be decomposed to ease understanding. ClusterChanges [109], JClus-terChanges [138], CoRA [142], and ChgCutter [148] are techniques for decomposing changes based on static analysis. ClusterChanges and JClusterChanges, instantiated for C# and Java language, respectively, analyze composite changes to uncover definitions and their uses, clustering diff-regions into trivial and non-trivial.…”

Section: Code Checkingmentioning

confidence: 99%

“…Studies of this type are present in six (13.64%) papers. From these, four [109,111,148,142] were used to complement the results of another study detailed in the same publication. One study [107] consists of a preliminary evaluation in which the subjects interact with a prototype of the proposed approach.…”

Section: Approachmentioning

confidence: 99%

See 4 more Smart Citations

A Systematic Literature Review and Taxonomy of Modern Code Review

Davila,

Nunes

2021

Preprint

View full text Add to dashboard Cite

Context: Modern Code Review (MCR) is a widely known practice of software quality assurance. However, the existing body of knowledge of MCR is currently not understood as a whole. Objective: Our goal is to identify the state of the art on MCR, providing a structured overview and an in-depth analysis of the research done in this field. Method: We performed a systematic literature review, selecting publications from four digital libraries. Results: A total of 139 papers were selected and analyzed in three main categories. Foundational studies are those that analyze existing or collected data from the adoption of MCR. Proposals consist of techniques and tools to support MCR, while evaluations are studies to assess an approach or compare a set of them. Conclusion: The most represented category is foundational studies, mainly aiming to understand the motivations for adopting MCR, its challenges and benefits, and which influence factors lead to which MCR outcomes. The most common types of proposals are code reviewer recommender and support to code checking. Evaluations of MCR-supporting approaches have been done mostly offline, without involving human subjects. Five main research gaps have been identified, which point out directions for future work in the area.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Evaluationsmentioning

confidence: 99%

Section: Code Checkingmentioning

confidence: 99%

Section: Code Checkingmentioning

confidence: 99%

Section: Approachmentioning

confidence: 99%

See 3 more Smart Citations

A Systematic Literature Review and Taxonomy of Modern Code Review

Davila,

Nunes

2021

Preprint

View full text Add to dashboard Cite

show abstract

An exploratory study on confusion in code reviews

et al. 2021

View full text Add to dashboard Cite

Context Code review is a widely used technique of systematic examination of code changes which aims at increasing software quality. Code reviews provide several benefits for the project, including finding bugs, knowledge transfer, and assurance of adherence to project guidelines and coding style. However, code reviews have a major cost: they can delay the merge of the code change, and thus, impact the overall development process. This cost can be even higher if developers do not understand something, i.e., when developers face confusion during the code review. Objective This paper studies the phenomenon of confusion in code reviews. Understanding confusion is an important starting point to help reducing the cost of code reviews and enhance the effectiveness of this practice, and hence, improve the development process. Method We conducted two complementary studies. The first one aimed at identifying the reasons for confusion in code reviews, its impacts, and the coping strategies developers use to deal with it. Then, we surveyed developers to identify the most frequently experienced reasons for confusion, and conducted a systematic mapping study of solutions proposed for those reasons in the scientific literature. Results From the first study, we build a framework with 30 reasons for confusion, 14 impacts, and 13 coping strategies. The results of the systematic mapping study shows 38 articles addressing the most frequent reasons for confusion. From those articles, we found 13 different solutions for confusion proposed in the literature, and five impacts were established related to the most frequent reasons for confusion. Conclusions Based on the solutions identified in the mapping study, or the lack of them, we propose an actionable guideline for developers on how to cope with confusion during code reviews; we also make several suggestions how tool builders can support code reviews. Additionally, we propose a research agenda for researchers studying code reviews.

show abstract

A systematic literature review and taxonomy of modern code review

Davila

Nunes²

2021

Journal of Systems and Software

View full text Add to dashboard Cite

Decomposing Composite Changes for Code Review and Regression Test Selection in Evolving Software

Cited by 8 publications

References 41 publications

A Systematic Literature Review and Taxonomy of Modern Code Review

A Systematic Literature Review and Taxonomy of Modern Code Review

An exploratory study on confusion in code reviews

A systematic literature review and taxonomy of modern code review

Contact Info

Product

Resources

About