MoDSEL

2012 ◽  
pp. 572-594
Author(s):  
Ersin Er ◽  
Bedir Tekinerdogan
Keyword(s):  
Software Development ◽  
Impact Analysis ◽  
Software Evolution ◽  
Academic Research ◽  
Model Driven ◽  
Model Driven Software Development ◽  
Basic Concepts ◽  
The Impact ◽  
Development And Evolution

Model-Driven Software Development (MDSD) aims to support the development and evolution of software intensive systems using the basic concepts of model, metamodel, and model transformation. In parallel with the ongoing academic research, MDSD is more and more applied in industrial practices. Like conventional non-MDSD practices, MDSD systems are also subject to changing requirements and have to cope with evolution. In this chapter, the authors provide a scenario-based approach for documenting and analyzing the impact of changes that apply to model-driven development systems. To model the composition and evolution of an MDSD system, they developed the so-called Model-Driven Software Evolution Language (MoDSEL) which is based on a megamodel for MDSD. MoDSEL includes explicit language abstractions to specify both the model elements of an MDSD system and the evolution scenarios that might apply to model elements. Based on MoDSEL specifications, an impact analysis is performed to assess the impact of evolution scenarios and the sensitivity of model elements. A case study is provided to show different kind of evolution scenarios and the required adaptations to model elements.

scholarly journals MoDSEL

2014 ◽  
pp. 528-550
Author(s):  
Ersin Er ◽  
Bedir Tekinerdogan
Keyword(s):  
Software Development ◽  
Impact Analysis ◽  
Software Evolution ◽  
Academic Research ◽  
Model Driven ◽  
Model Driven Software Development ◽  
Basic Concepts ◽  
The Impact ◽  
Development And Evolution

Model-Driven Software Development (MDSD) aims to support the development and evolution of software intensive systems using the basic concepts of model, metamodel, and model transformation. In parallel with the ongoing academic research, MDSD is more and more applied in industrial practices. Like conventional non-MDSD practices, MDSD systems are also subject to changing requirements and have to cope with evolution. In this chapter, the authors provide a scenario-based approach for documenting and analyzing the impact of changes that apply to model-driven development systems. To model the composition and evolution of an MDSD system, they developed the so-called Model-Driven Software Evolution Language (MoDSEL) which is based on a megamodel for MDSD. MoDSEL includes explicit language abstractions to specify both the model elements of an MDSD system and the evolution scenarios that might apply to model elements. Based on MoDSEL specifications, an impact analysis is performed to assess the impact of evolution scenarios and the sensitivity of model elements. A case study is provided to show different kind of evolution scenarios and the required adaptations to model elements.

Towards Measuring the Change Impact in ATL Model Transformations

2016 ◽  
Vol 26 (02) ◽  
pp. 153-181 ◽  
Author(s):  
Andreza Vieira ◽  
Franklin Ramalho
Keyword(s):  
Software Development ◽  
Static Analysis ◽  
Development Time ◽  
Development Process ◽  
Model Transformations ◽  
Software Development Process ◽  
Model Driven ◽  
Change Impact ◽  
The Impact

The Model-Driven Development (MDD) approach shifts the focus on code to models in the software development process. In MDD, model transformations are elements that play an important role. MDD-based projects evolve along their lifecycle in a way that changes in their transformations are frequent. Before applying changes it is important to measure their impacts within the transformation. However, currently no technique helps practitioners in this direction. We propose an approach to measure the change impact in ATL model transformations. Based on static analysis, it detects the elements impacted by a change and calculates the change impact value through three metrics we defined. By using our approach, practitioners can (i) save effort and development time since the elements impacted with the change are automatically detected and (ii) better schedule and prioritize changes according to the impact value. To empirically evaluate our approach we conducted a case study.

scholarly journals Teaching pragmatic model-driven software development

2015 ◽  
Vol 12 (2) ◽  
pp. 683-705 ◽  
Author(s):  
Jaroslav Porubän ◽  
Michaela Bacíková ◽  
Sergej Chodarev ◽  
Milan Nosál’
Keyword(s):  
Software Development ◽  
Development Process ◽  
Model Driven Development ◽  
Model Driven ◽  
Visualisation Tool ◽  
Big Picture ◽  
Model Driven Software Development ◽  
Positive Results

Model-driven software development is surrounded by numerous myths and misunderstandings that hamper its adoption. For long, our students were victims of these myths and considered MDSD impractical and only applied in academy. In this paper we discuss these myths and present our experience with devising an MDSD course that challenges them and motivates students to understand MDSD principles. The main contribution of this work is a set of MDSD teaching guidelines that can make the course pragmatic in the eyes of students - programmers. These guidelines introduce MDSD from the viewpoint of a programmer as a pragmatic tool for solving concrete problems in the development process. In our MDSD course we implemented the presented guidelines. The course shows several techniques and principles of model-driven development in multiple incremental iterations instead of concentrating on a single tool. At the same time we unite these techniques by using a dynamic visualisation tool that shows to the students the whole infrastructure in the big picture. The course is implemented as an iterative incremental MDSD case study. The paper concludes with a survey performed with our students that indicates positive results of the approach.

scholarly journals ‘I’m not being paid for this conversation’: Uncovering the challenges of artist–academic collaborations in the neoliberal institution

2019 ◽  
Vol 23 (3) ◽  
pp. 317-333
Author(s):  
Alena Pfoser ◽  
Sara de Jong
Keyword(s):  
Collaborative Work ◽  
Knowledge Exchange ◽  
Academic Research ◽  
The Political ◽  
Institutional Pressures ◽  
Negative Effects ◽  
Collective Response ◽  
And Shifts ◽  
The Impact

Artist–academic collaborations are fuelled by increasing institutional pressures to show the impact of academic research. This article departs from the celebratory accounts of collaborative work and pragmatic toolkits for successful partnerships, which are dominant in existing scholarship, arguing for the need to critically interrogate the structural conditions under which collaborations take place. Based on a reflexive case study of a project developed in the context of Tate Exchange, one of the UK’s highest-profile platforms for knowledge exchange, we reveal three sets of (unequal) pressures, which mark artist–academic collaborations in the contemporary neoliberal academy: asymmetric funding and remuneration structures; uneven pressures of audit cultures; acceleration and temporal asymmetries. Innovations at the level of individual projects or partners can only mitigate the negative effects to a limited extent. Instead this article offers a systemic critique of the political economy of artist–academic collaborations and shifts the research agenda to developing a collective response.

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