Towards Product Lining Model-Driven Development Code Generators

A code generator systematically transforms compact models to detailed code. Today, code generation is regarded as an integral part of model-driven development (MDD). Despite its relevance, the development of code generators is an inherently complex task and common methodologies and architectures are lacking. Additionally, reuse and extension of existing code generators only exist on individual parts. A systematic development and reuse based on a code generator product line is still in its infancy. Thus, the aim of this paper is to identify the mechanism necessary for a code generator product line by (a) analyzing the common product line development approach and (b) mapping those to a code generator specific infrastructure. As a first step towards realizing a code generator product line infrastructure, we present a component-based implementation approach based on ideas of variability-aware module systems and point out further research challenges.Comment: 6 pages, 1 figure, Proceedings of the 3rd International Conference on Model-Driven Engineering and Software Development, pp. 539-545, Angers, France, SciTePress, 201

Model driven product line engineering : core asset and process implications

Reuse is at the heart of major improvements in productivity and quality in Software Engineering. Both Model Driven Engineering (MDE) and Software Product Line Engineering (SPLE) are software development paradigms that promote reuse. Specifically, they promote systematic reuse and a departure from craftsmanship towards an industrialization of the software development process. MDE and SPLE have established their benefits separately. Their combination, here called Model Driven Product Line Engineering (MDPLE), gathers together the advantages of both. Nevertheless, this blending requires MDE to be recasted in SPLE terms. This has implications on both the core assets and the software development process. The challenges are twofold: (i) models become central core assets from which products are obtained and (ii) the software development process needs to cater for the changes that SPLE and MDE introduce. This dissertation proposes a solution to the first challenge following a feature oriented approach, with an emphasis on reuse and early detection of inconsistencies. The second part is dedicated to assembly processes, a clear example of the complexity MDPLE introduces in software development processes. This work advocates for a new discipline inside the general software development process, i.e., the Assembly Plan Management, which raises the abstraction level and increases reuse in such processes. Different case studies illustrate the presented ideas.This work was hosted by the University of the Basque Country (Faculty of Computer Sciences). The author enjoyed a doctoral grant from the Basque Goverment under the “Researchers Training Program” during the years 2005 to 2009. The work was was co-supported by the Spanish Ministry of Education, and the European Social Fund under contracts WAPO (TIN2005-05610) and MODELINE (TIN2008-06507-C02-01)

Towards a flexible service integration through separation of business rules

Driven by dynamic market demands, enterprises are continuously exploring collaborations with others to add value to their services and seize new market opportunities. Achieving enterprise collaboration is facilitated by Enterprise Application Integration and Business-to-Business approaches that employ architectural paradigms like Service Oriented Architecture and incorporate technological advancements in networking and computing. However, flexibility remains a major challenge related to enterprise collaboration. How can changes in demands and opportunities be reflected in collaboration solutions with minimum time and effort and with maximum reuse of existing applications? This paper proposes an approach towards a more flexible integration of enterprise applications in the context of service mediation. We achieve this by combining goal-based, model-driven and serviceoriented approaches. In particular, we pay special attention to the separation of business rules from the business process of the integration solution. Specifying the requirements as goal models, we separate those parts which are more likely to evolve over time in terms of business rules. These business rules are then made executable by exposing them as Web services and incorporating them into the design of the business process.\ud Thus, should the business rules change, the business process remains unaffected. Finally, this paper also provides an evaluation of the flexibility of our solution in relation to the current work in business process flexibility research

Model-Driven Engineering for Trusted Embedded Systems based on Security and Dependability Patterns

National audienceNowadays, many practitioners express their worries about current software engineering practices. New recommendations should be considered to ground software engineering on two pillars: solid theory and proven principles. We took the second pillar towards software engineering for embedded system applications, focusing on the problem of integrating Security and Dependability (S&D) by design to foster reuse. The framework and the methodology we propose associate the model-driven paradigm and a model-based repository of S&D patterns to support the design of trusted Resource Constrained Embedded System (RCES) applications for multiple domains (e.g., railway, metrology, automotive). The approach has been successfully evaluated by the TERESA project external reviewers as well as internally by the Ikerlan Research Center for the railway domain

Supporting Model-to-Model Transformations: The VMT Approach

The model-driven architecture approach (MDA) promotes software development as driven by a thorough modeling phase where application code is automatically generated from a platform specific UML model (PSM). The idea is that the PSM is itself derived from a platform independent UML model (PIM). Such code generation and model derivation are examples of model-to-model transformations. This paper presents the Visual Model Transformation (VMT) approach, which includes a transformation language and a tool to support UML model transformations. The transformation language is a visual declarative language that supports the specification, composition and reuse of model transformation rules. These rules make use of the OCL language and a visual notation to indicate the selection, creation, modification and removal of model elements. An abstract denotational semantics based on graph transformation is sketched for the VMT language. We also present the MEDAL tool, which is a prototype build on top of IBM/Rational XDE development environment, and is a first step towards tool support for the VMT approach

Beyond “Data Thrifting”: An Investigation of Factors Influencing Research Data Reuse In the Social Sciences

The development of e-Research infrastructure has enabled data to be shared and accessed more openly. Policy mandates for data sharing have contributed to the increasing availability of research data through data repositories, which create favorable conditions for the reuse of data for purposes not always anticipated by original collectors. Despite the current efforts to promote transparency and reproducibility in science, data reuse cannot be assumed, nor merely considered a “thrifting” activity where scientists shop around in data repositories considering only the ease of access to data. This research was driven by three main questions: 1) What are the factors that influence scientists’ research data reuse? 2) To what degree do these factors influence scientists’ research data reuse? and 3) To what extent do scientists reuse research data? Following a sequential mixed-method approach, this study sought to provide a more nuanced view of the underlying factors that affect social scientists’ intentions to reuse data, as well as the impact of these factors on the actual reuse of data. Findings from a preliminary small-scale exploratory study with 13 social scientists produced 25 factors that were found to influence their perceptions and experiences, including both their unsuccessful and successful attempts to reuse data. These factors were grouped into six theoretical variables: perceived benefits, perceived risks, perceived effort, social influence, facilitating conditions, and perceived reusability. The variables were articulated in a conceptual model drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT) in order to examining social scientists’ intentions and behaviors towards the reuse of research data. The proposed hierarchical component model and the research hypotheses were validated through a survey, which was distributed to 4,500 social scientists randomly selected from the Pivot/Community of Science (CoS) database. A total of 743 social scientists participated in the survey, of which 564 cases were included in the analysis. The survey data were analyzed using the Partial Least Square Structural Equation Modeling (PLS-SEM) technique, and supplemented by ad-hoc group comparison analyses. Survey results demonstrated that social scientists’ data reuse intention and reuse behavior were indeed influenced by different factors beyond frugality. More specifically, the more practical and social benefits social scientists perceive from reusing research data, the more likely they intended to reuse data. Similarly, peer and disciplinary influence had a positive effect on social scientists’ intention to reuse data collected/produced by others. On the contrary, the construct perceived risks was found to negatively influence social scientists’ intention to reuse existing research data collected by others. Facilitating conditions and intention to reuse were found to positively correlate to actual data reuse behavior. Perceived effort was found not statistically significant, indicating that reusing data from others did not involve as much effort as collecting/producing primary data. Perceived reusability failed to be measured, due to the lack of convergent validity. Ad-hoc group comparison tests found that intention and data reuse behavior depended on sub-disciplines’ traditions and the methodological approach social scientists followed. The findings of this research provide an in-depth understanding about the reuse of research data in the context of open science, and provide a collection of factors that influence social scientists’ decisions to reuse research data collected by others. Additionally, they update our knowledge of data reuse behavior and contribute to the body of data reuse literature by establishing a conceptual model that can be validated by future research. In terms of practice, it offers recommendations for policy makers, data scientists, and stakeholders from data repositories on defining strategies and initiatives to leverage data reuse and make publicly available data more actionable

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Quality-aware model-driven service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services