Enhancing version control with domain-specific semantics

Foucault, Matthieu; Barbier, Sebastien; Lugato, David

doi:10.1109/mise.2013.6595293

Cited by 2 publications

(3 citation statements)

References 19 publications

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“…Foucault et al [59] aimed to enhance traditional text-based version control (more specifically, git [54]) with domainspecific semantics. The textual representations are described by a textual domain-specific modeling language using EBNF, and the matching is done based on static identifiers.…”

Section: Text-based Model Matching (Rq11)mentioning

confidence: 99%

“…We have seen examples of this configuration cost in two out of three algorithms that aimed to be both accurate and general at the same time [127,136,137]. Foucault et al [59] is the exception to this, as their algorithm aims to be general by using static identifiers, which limits its practical applicability in the case of more complex modeling languages. We did not find a text-based algorithm which focuses only on generality.…”

Section: Text-based Model Matching (Rq11)mentioning

confidence: 99%

“…-Lack of text-based algorithms There is a lack of textbased model matching algorithms, and an even greater lack of general text-based algorithms. -Motivations behind using text-based algorithms The main motivations we found behind text-based model matching are (i) using the simplicity of raw text differencing and enhancing it to be suitable for models [16,59,157], (ii) aiming for better accuracy at a higher configuration cost [127,136], and (iii) supporting the textual notation of the models by solving a related, specific problem [19,157]. -Generality comes with configuration cost Text-based model matching algorithms tend to focus either on accuracy, or on both accuracy and generality.…”

Section: Text-based Model Matching (Rq11)mentioning

confidence: 99%

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Systematic review of matching techniques used in model-driven methodologies

Somogyi

Asztalos

2019

Softw Syst Model

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In model-driven methodologies, model matching is the process of finding a matching pair for every model element between two or more software models. Model matching is an important task as it is often used while differencing and merging models, which are key processes in version control systems. There are a number of different approaches to model matching, with most of them focusing on different goals, i.e., the accuracy of the matching process, or the generality of the algorithm. Moreover, there exist algorithms that use the textual representations of the models during the matching process. We present a systematic literature review that was carried out to obtain the state-of-the-art of model matching techniques. The search process was conducted based on a well-defined methodology. We have identified a total of 3274 non-duplicate studies, out of which 119 have been included as primary studies for this survey. We present the state-of-the-art of model matching, highlighting the differences between different matching techniques, mainly focusing on text-based and graph-based algorithms. Finally, the main open questions, challenges, and possible future directions in the field of model matching are discussed, also including topics like benchmarking, performance and scalability, and conflict handling. Keywords Model matching • Model comparison • Model differencing • Version control • Text-based modeling • Systematic literature review Communicated by Professor Jon Whittle.

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Section: Text-based Model Matching (Rq11)mentioning

confidence: 99%

Section: Text-based Model Matching (Rq11)mentioning

confidence: 99%

Section: Text-based Model Matching (Rq11)mentioning

confidence: 99%

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Systematic review of matching techniques used in model-driven methodologies

Somogyi

Asztalos

2019

Softw Syst Model

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Conflict management techniques for model merging: a systematic mapping review

2022

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Model merging conflicts occur when different stakeholders aim to integrate their contradicting changes that are applied concurrently to update software models. We conduct an extensive systematic mapping study on conflict management techniques and relevant collaboration attributes to the versioning and merging models from 2001 to the middle of 2021. This study follows the standard guidelines within the software engineering domain. We analyzed a total of 105 articles extracted from an initial pool of more than 1800 articles to infer a taxonomy for conflict management techniques. We use this taxonomy to classify existing approaches to understand characteristics, shortcomings, and challenges on conflict management techniques in merging models. It also provides a solid foundation for future work in this area. We show that syntactic conflicts are the most studied type and that the top three popular conflict detection techniques are constraint violation, change overlapping, and pattern matching. We observe the lack of a comprehensive state-of-theart comparison between academic or industrial tools, as well as the need for real-world case studies. Finally, we show that recent trends have focused on online collaboration, where teams of stakeholders work on large-scale models.

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Enhancing version control with domain-specific semantics

Cited by 2 publications

References 19 publications

Systematic review of matching techniques used in model-driven methodologies

Systematic review of matching techniques used in model-driven methodologies

Conflict management techniques for model merging: a systematic mapping review

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