Derivation and consistency checking of models in early software product line engineering

Dissertação para obtenção do Grau de Doutor em Engenharia InformáticaSoftware Product Line Engineering (SPLE) should offer the ability to express the derivation of product-specific assets, while checking for their consistency. The derivation of product-specific assets is possible using general-purpose programming languages in combination with techniques such as conditional compilation and code generation. On the other hand, consistency checking can be achieved through consistency rules in the form of architectural and design guidelines, programming conventions and well-formedness rules. Current approaches present four shortcomings: (1) focus on code derivation only, (2) ignore consistency problems between the variability model and other complementary specification models used in early SPLE, (3) force developers to learn new, difficult to master, languages to encode the derivation of assets, and (4) offer no tool support. This dissertation presents solutions that contribute to tackle these four shortcomings. These solutions are integrated in the approach Derivation and Consistency Checking of models in early SPLE (DCC4SPL) and its corresponding tool support. The two main components of our approach are the Variability Modelling Language for Requirements(VML4RE), a domain-specific language and derivation infrastructure, and the Variability Consistency Checker (VCC), a verification technique and tool. We validate DCC4SPL demonstrating that it is appropriate to find inconsistencies in early SPL model-based specifications and to specify the derivation of product-specific models.European Project AMPLE, contract IST-33710; Fundação para a Ciência e Tecnologia - SFRH/BD/46194/2008

Reusable textual styles for domain-specific modeling languages

Domain-specific languages enable concise and precise formalization of domain concepts and promote direct employment by domain experts. Therefore, syntactic constructs are introduced to empower users to associate concepts and relationships with visual textual symbols. Model-based language engineering facilitates the description of concepts and relationships in an abstract manner. However, concrete representations are commonly attached to abstract domain representations, such as annotations in metamodels, or directly encoded into language grammar and thus introduce redundancy between metamodel elements and grammar elements. In this work we propose an approach that enables autonomous development and maintenance of domain concepts and textual language notations in a distinctive and metamodel-agnostic manner by employing style models containing grammar rule templates and injection-based property selection. We provide an implementation and showcase the proposed notationspecification language in a comparison with state of the art practices during the creation of notations for an executable domain-specific modeling language based on the Eclipse Modeling Framework and Xtext

Developing a Generic Debugger for Advanced-Dispatching Languages

Programming-language research has introduced a considerable number of advanced-dispatching mechanisms in order to improve modularity. Advanced-dispatching mechanisms allow changing the behavior of a function without modifying their call sites and thus make the local behavior of code less comprehensible. Debuggers are tools, thus needed, which can help a developer to comprehend program behavior but current debuggers do not provide inspection of advanced-\ud dispatching-related language constructs. In this paper, we present a debugger which extends a traditional Java debugger with the ability of debugging an advanced-dispatching language constructs and a user interface for inspecting this

Evolution specification evaluation in industrial MDSE ecosystems

Domain-specific languages (DSLs) allow users to model systems using concepts from a specific domain. Evolution of DSLs triggers co-evolution of models developed in these languages. When the number of models that needs to co-evolve increases, so does the required effort to do so. This is called the co-evolution problem. We have investigated the extent of the co-evolution problem at ASML [1], provider of lithography equipment for the semiconductor industry. Here we have described the structure and evolution of a large-scale ecosystem of DSLs. We have observed that due to the large number of artifacts that require coevolutionary activity, manual solutions have become unfeasible, and an automated approach is required. A popular approach for automating co-evolution is the operator-based approach. In this paper we have evaluated the operator-based approach on a large-scale industrial case-study of twenty-two DSLs and 95 model-to-model transformations with a revision history of over three years, and have revealed deficiencies in existing operator libraries. To address these deficiencies we have presented a topdown methodology to derive a complete set of operators

A Feature Model for an IDE4OCL

An Integrated OCL Development Environment (IDE4OCL) can significantly improve the pragmatics and practice of OCL. Therefore we started a comprehensive requirement analysis with the long term vision of a multisite IDE4OCL project. In this paper we present a feature model for the IDE4OCL vision based on this analysis. In an earlier work we identified domain concepts, tool–level interactions with IDE4OCL, and use cases for OCL developers including a set predefined features. In the second step, we asked the OCL community members for their feedback on our proposal. Around 100 researchers, tool developers and practitioners who gained experience with OCL have voted in an online–survey. The results gave us a valuable insight in the needs of OCL usage both in usual and advanced OCL applications. One of the important results is a collection of features that have been proposed additionally to our predefined features. We analysed all the comments of the participants of the survey and consolidated them into an extended set of IDE4OCL features and eventually into a feature model

Programming Robots for Activities of Everyday Life

Text-based programming remains a challenge to novice programmers in\ua0all programming domains including robotics. The use of robots is gainingconsiderable traction in several domains since robots are capable of assisting\ua0humans in repetitive and hazardous tasks. In the near future, robots willbe used in tasks of everyday life in homes, hotels, airports, museums, etc.\ua0However, robotic missions have been either predefined or programmed usinglow-level APIs, making mission specification task-specific and error-prone.\ua0To harness the full potential of robots, it must be possible to define missionsfor specific applications domains as needed. The specification of missions of\ua0robotic applications should be performed via easy-to-use, accessible ways, and\ua0at the same time, be accurate, and unambiguous. Simplicity and flexibility in\ua0programming such robots are important, since end-users come from diverse\ua0domains, not necessarily with suffcient programming knowledge.The main objective of this licentiate thesis is to empirically understand the\ua0state-of-the-art in languages and tools used for specifying robot missions byend-users. The findings will form the basis for interventions in developing\ua0future languages for end-user robot programming.During the empirical study, DSLs for robot mission specification were\ua0analyzed through published literature, their websites, user manuals, samplemissions and using the languages to specify missions for supported robots.After extracting data from 30 environments, 133 features were identified.\ua0A feature matrix mapping the features to the environments was developedwith a feature model for robotic mission specification DSLs.Our results show that most end-user facing environments exist in the\ua0education domain for teaching novice programmers and STEM subjects. Mostof the visual languages are developed using Blockly and Scratch libraries.\ua0The end-user domain abstraction needs more work since most of the visualenvironments abstract robotic and programming language concepts but not\ua0end-user concepts. In future works, it is important to focus on the development\ua0of reusable libraries for end-user concepts; and further, explore how end-user\ua0facing environments can be adapted for novice programmers to learn\ua0general programming skills and robot programming in low resource settings\ua0in developing countries, like Uganda

Pattern-based refactoring in model-driven engineering

L’ingénierie dirigée par les modèles (IDM) est un paradigme du génie logiciel qui utilise les modèles comme concepts de premier ordre à partir desquels la validation, le code, les tests et la documentation sont dérivés. Ce paradigme met en jeu divers artefacts tels que les modèles, les méta-modèles ou les programmes de transformation des modèles. Dans un contexte industriel, ces artefacts sont de plus en plus complexes. En particulier, leur maintenance demande beaucoup de temps et de ressources. Afin de réduire la complexité des artefacts et le coût de leur maintenance, de nombreux chercheurs se sont intéressés au refactoring de ces artefacts pour améliorer leur qualité. Dans cette thèse, nous proposons d’étudier le refactoring dans l’IDM dans sa globalité, par son application à ces différents artefacts. Dans un premier temps, nous utilisons des patrons de conception spécifiques, comme une connaissance a priori, appliqués aux transformations de modèles comme un véhicule pour le refactoring. Nous procédons d’abord par une phase de détection des patrons de conception avec différentes formes et différents niveaux de complétude. Les occurrences détectées forment ainsi des opportunités de refactoring qui seront exploitées pour aboutir à des formes plus souhaitables et/ou plus complètes de ces patrons de conceptions. Dans le cas d’absence de connaissance a priori, comme les patrons de conception, nous proposons une approche basée sur la programmation génétique, pour apprendre des règles de transformations, capables de détecter des opportunités de refactoring et de les corriger. Comme alternative à la connaissance disponible a priori, l’approche utilise des exemples de paires d’artefacts d’avant et d’après le refactoring, pour ainsi apprendre les règles de refactoring. Nous illustrons cette approche sur le refactoring de modèles.Model-Driven Engineering (MDE) is a software engineering paradigm that uses models as first-class concepts from which validation, code, testing, and documentation are derived. This paradigm involves various artifacts such as models, meta-models, or model transformation programs. In an industrial context, these artifacts are increasingly complex. In particular, their maintenance is time and resources consuming. In order to reduce the complexity of artifacts and the cost of their maintenance, many researchers have been interested in refactoring these artifacts to improve their quality. In this thesis, we propose to study refactoring in MDE holistically, by its application to these different artifacts. First, we use specific design patterns, as an example of prior knowledge, applied to model transformations to enable refactoring. We first proceed with a detecting phase of design patterns, with different forms and levels of completeness. The detected occurrences thus form refactoring opportunities that will be exploited to implement more desirable and/or more complete forms of these design patterns. In the absence of prior knowledge, such as design patterns, we propose an approach based on genetic programming, to learn transformation rules, capable of detecting refactoring opportunities and correcting them. As an alternative to prior knowledge, our approach uses examples of pairs of artifacts before and after refactoring, in order to learn refactoring rules. We illustrate this approach on model refactoring

Honors College 2015 APR Self-Study & Documents

UNM Honors College APR self-study report, review team report, and initial action plan for Fall 2015, fulfilling requirements of the Higher Learning Commission