A Benchmark for Conflict Detection Components of Model Versioning Systems

Langer, Philip; Wimmer, Manuel

doi:10.1007/s40568-013-0060-y

Cited by 5 publications

(4 citation statements)

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“…[22] measures precision and recall), we propose a new scalability benchmark for model merge by adapting of the Train Benchmark [29], which is an existing performance benchmark for model queries and well-formedness constraints (and also a case of the TTC 2015 contest [28]). The benchmark uses a domain-specic model of a railway system originating from the MOGENTES project [4].…”

Section: Discussionmentioning

confidence: 99%

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Automated Model Merge by Design Space Exploration

Debreceni

Ráth

Varró

et al. 2016

Fundamental Approaches to Software Engineering

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Abstract. Industrial applications of model-driven engineering to develop large and complex systems resulted in an increasing demand for collaboration features. However, use cases such as model dierencing and merging have turned out to be a dicult challenge, due to (i) the graphlike nature of models, and (ii) the complexity of certain operations (e.g. hierarchy refactoring) that are common today. In the paper, we present a novel search-based automated model merge approach where rule-based design space exploration is used to search the space of solution candidates that represent conict-free merged models. Our method also allows engineers to easily incorporate domain-specic knowledge into the merge process to provide better solutions. The merge process automatically calculates multiple merge candidates to be presented to domain experts for nal selection. Furthermore, we propose to adopt a generic synthetic benchmark to carry out an initial scalability assessment for model merge with large models and large change sets.

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Section: Discussionmentioning

confidence: 99%

“…[25] and [26] show a preliminary evaluation which show the relevance of the approach on very small models and change set. [13] evaluated by [22], but scalability is not discussed. For comparing models, [1] has a scalability test presented in [7].…”

Section: Related Workmentioning

confidence: 99%

Automated Model Merge by Design Space Exploration

Debreceni

Ráth

Varró

et al. 2016

Fundamental Approaches to Software Engineering

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show abstract

“…Similar to Langer et al [28], we are going to implement a generic API for the workflow and implement adapters for each transformation engine. Similar to the Train Benchmark framework [43], we will design models and transformations with growing size and complexity to exercise the model transformation engines.…”

Section: Multi-tenant Reactive Model Transformation Benchmarkmentioning

confidence: 99%

Towards the next generation of reactive model transformations on low-code platforms

Horváth

Horváth²,

Wimmer

2020

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedi

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Low-Code Development Platforms have emerged as the next-generation, cloud-enabled collaborative platforms. These platforms adopt the principles of Model-Driven Engineering, where models are used as first-class citizens to build complex systems, and model transformations are employed to keep a consistent view between the different aspects of them. Due to the online nature of low-code platforms, users expect them to be responsive, to complete complex operations in a short time. To support such complex collaboration scenarios, the next-generation of low-code platforms must (𝑖) offer a multi-tenant environment to manage the collaborative work of engineers, (𝑖𝑖) provide a model processing paradigm scaling up to hundreds of millions of elements, and (𝑖𝑖𝑖) provide engineers a set of selection criteria to choose the right model transformation engine in multi-tenant execution environments.In this paper, we outline three research lines to improve the performance of reactive model transformations on low-code platforms, by motivating our research with a case study from a systems engineering domain. CCS CONCEPTS• Software and its engineering → Model-driven software engineering.

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“…In this case study, we have used the "benchmark for conflict detection of model versioning systems" 5 and more specifically the "class diagram versioning" test case described in [47]. It lists a series of common operations that may cause troubles during concurrent modifications.…”

Section: Experimental Designmentioning

confidence: 99%