Incremental Model Transformation with Epsilon in Model-Driven Engineering

Ghorbani, Marzieh; Sharbaf, Mohammadreza; Zamani, Bahman

doi:10.18267/j.aip.179

Cited by 4 publications

(1 citation statement)

References 33 publications

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“…System needs are divided into different separate development cycle components using the incremental method [43]. Each module goes through the stages of requirements, design, implementation, and testing [44].…”

Section: 4the Incremental Methodsmentioning

confidence: 99%

Enhancing peatland fire prevention: an incremental LoRa and mobile-based early warning system

2023

IJATEE

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Peatland is a unique and sensitive ecosystem that brings significant economic functions to the local community. As an essential natural resource, peatland provides vital environmental services such as flood control, water filtration, and carbon sequestration. At the same time, peatland supports the livelihoods of local communities through the cultivation of crops like sago, coconut, and fruit, as well as fishing and extraction of forest products. However, peatland is also highly vulnerable to degradation from deforestation, drainage, fire, and unsustainable agricultural practices [1].*Author for correspondence However, recent reports reveal a concerning trend of forest fires in Indonesia, particularly on Sumatra island, predominantly caused by human errors and unsustainable practices. Sumatra has experienced widespread annual forest fires, with over 311,000 hectares burned in 2021 alone. The leading causes stem from slash-and-burn clearing of land for agriculture, negligence during land preparation, and drainage of peatland areas [2]. Prohibited farming practices aimed at converting peatland into palm oil areas have been identified as a significant catalyst for these fires. Draining peat swamps and using fire for land clearing are techniques illegally employed to convert forested peatlands into plantations for the lucrative palm oil industry [3]. This detrimental setting leads to frequent fire occurrences, especially during dry periods, resulting in haze and

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Section: 4the Incremental Methodsmentioning

confidence: 99%

Enhancing peatland fire prevention: an incremental LoRa and mobile-based early warning system

2023

IJATEE

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Using reactive links to propagate changes across engineering models

Raţiu,

Assunção,

Herac

et al. 2024

Softw Syst Model

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Collaborative model-driven development is a de facto practice to create software-intensive systems in several domains (e.g., aerospace, automotive, and robotics). However, when multiple engineers work concurrently, keeping all model artifacts synchronized and consistent is difficult. This is even harder when the engineering process relies on a myriad of tools and domains (e.g., mechanic, electronic, and software). Existing work tries to solve this issue from different perspectives, such as using trace links between different artifacts or computing change propagation paths. However, these solutions mainly provide additional information to engineers, still requiring manual work for propagating changes. Yet, most modeling tools are limited regarding the traceability between different domains, while also lacking the efficiency and granularity required during the development of software-intensive systems. Motivated by these limitations, in this work, we present a solution based on what we call “reactive links”, which are highly granular trace links that propagate change between property values across models in different domains, managed in different tools. Differently from traditional “passive links”, reactive links automatically propagate changes when engineers modify models, assuring the synchronization and consistency of the artifacts. The feasibility, performance, and flexibility of our solution were evaluated in three practical scenarios, from two partner organizations. Our solution is able to resolve all cases in which change propagation among models were required. We observed a great improvement of efficiency when compared to the same propagation if done manually. The contribution of this work is to enhance the engineering of software-intensive systems by reducing the burden of manually keeping models synchronized and avoiding inconsistencies that potentially can originate from collaborative engineering in a variety of tool from different domains.

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