Genericity for model management operations

Models are the core assets in model-driven engineering, and are therefore subject to all kind of manipulations, such as refactorings, animations, transformations into other languages, comparisons and merging. This set of model-related activities is known as model management. Even though many languages and approaches have been proposed for model management, most of them are type-centric, specific to concrete meta-models, and hence leading to specifications with a low level of abstraction and difficult to be reused in practice. In this paper, we introduce ideas from generic programming into model management to raise the level of abstraction of the specifications of model manipulations and facilitate their reuse. In particular we adopt generic meta-model concepts as an intermediate, abstract meta-model over which model management specifications are defined. Such meta-model concepts are mapped to concrete meta-models, so that specifications can be applied to families of meta-models satisfying the concept requirements. As a proof of concept, we show the implementation of these ideas using the Eclipse Modeling Framework and the Epsilon family of languages for model management.     

From types to type requirements: genericity for model-driven engineering

Model-driven engineering (MDE) is a software engineering paradigm that proposes an active use of models during the development process. This paradigm is inherently type-centric, in the sense that models and their manipulation are defined over the types of specific meta-models. This fact hinders the reuse of existing MDE artefacts with other meta-models in new contexts, even if all these meta-models share common characteristics. To increase the reuse opportunities of MDE artefacts, we propose a paradigm shift from type-centric to requirement-centric specifications by bringing genericity into models, meta-models and model management operations. For this purpose, we introduce so-called concepts gathering structural and behavioural requirements for models and meta-models. In this way, model management operations are defined over concepts, enabling the application of the operations to any meta-model satisfying the requirements imposed by the concept. Model templates rely on concepts to define suitable interfaces, hence enabling the definition of reusable model components. Finally, similar to mixin layers, templates can be defined at the meta-model level as well, to define languages in a modular way, as well as layers of functionality to be plugged-in into other meta-models. These ideas have been implemented in MetaDepth, a multi-level meta-modelling tool that integrates action languages from the Epsilon family for model management and code generation.     

Grammar-based model transformations: Definition,execution, and quality properties

Model transformation is a key concept in model-driven software engineering. The definition of model transformations is usually based on meta-models describing the abstract syntax of languages. While meta-models are thereby able to abstract from superfluous details of concrete syntax, they often loose structural information inherent in languages, like information on model elements always occurring together in particular shapes. As a consequence, model transformations cannot naturally re-use language structures, thus leading to unnecessary complexity in their development as well as in quality assurance.In this paper, we propose a new approach to model transformation development which allows to simplify the developed transformations and improve their quality via the exploitation of the languages׳ structures. The approach is based on context-free graph grammars and transformations defined by pairing productions of source and target grammars. We show that such transformations have important properties: they terminate and are sound, complete, and deterministic.     

Blockchain verification and validation: Techniques,challenges, and research directions

As blockchain technology is gaining popularity in industry and society, solutions for Verification and Validation (V&V) of blockchain-based software applications (BC-Apps) have started gaining equal attention. To ensure that BC-Apps are properly developed before deployment, it is paramount to apply systematic V&V to verify their functional and non-functional requirements. While existing research aims at addressing the challenges of engineering BC-Apps by providing testing techniques and tools, blockchain-based software development is still an emerging research discipline, and therefore, best practices and tools for the V&V of BC-Apps are not yet sufficiently developed. In this paper, we provide a comprehensive survey on V&V solutions for BC-Apps. Specifically, using a layered approach, we synthesize V&V tools and techniques addressing different components at various layers of the BC-App stack, as well as across the whole stack. Next, we provide a discussion on the challenges associated with BC-App V&V, and summarize a set of future research directions based on the challenges and gaps identified in existing research work. Our study aims to highlight the importance of BC-App V&V and pave the way for a disciplined, testable, and verifiable BC development.     

A Meta-Model for Model-Driven Web Development

Several model-driven development (MDD) techniques for web applications exist; these techniques use meta-models for defining transformations and designing models. In this paper, we propose a meta-model for abstract web applications that can be mapped to multiple platforms. We extend a UML-based model to support specific features of the Web and Web 2.0 as well as to establish a bridge to functional and usability requirements through use cases and user interface (UI) prototypes. The meta-model also helps avoid a common MDD-related problem caused by name-based dependencies. Finally, mappings to a number of specific web platforms are presented in order to validate the appropriateness of the meta-model as an abstract web model.     

Ring: A unifying meta-model and infrastructure for Smalltalk source code analysis tools

Source code management systems record different versions of code. Tool support can then compute deltas between versions. To ease version history analysis we need adequate models to represent source code entities. Now naturally the questions of their definition, the abstractions they use, and the APIs of such models are raised, especially in the context of a reflective system which already offers a model of its own structure.We believe that this problem is due to the lack of a powerful code meta-model as well as an infrastructure. In Smalltalk, often several source code meta-models coexist: the Smalltalk reflective API coexists with the one of the Refactoring engine or distributed versioning system such as Monticello or Store. While having specific meta-models is an adequate engineered solution, it multiplies meta-models and it requires more maintenance efforts (e.g., duplication of tests, transformation between models), and more importantly hinders navigation tool reuse when meta-models do not offer polymorphic APIs.As a first step to provide an infrastructure to support history analysis, this article presents Ring, a unifying source code meta-model that can be used to support several activities and proposes a unified and layered approach to be the foundation for building an infrastructure for version and stream of change analyses. We re-implemented three tools based on Ring to show that it can be used as the underlying meta-model for remote and off-image browsing, scoping refactoring, and visualizing and analyzing changes. As a future work and based on Ring we will build a new generation of history analysis tools.     

Pointwise ensemble of meta-models using v nearest points cross-validation

As the use of meta-models to replace computationally-intensive simulations for estimating real system behaviors increases, there is an increasing need to select appropriate meta-models that well represent real system behaviors. Since in most cases designers do not know the behavior of the real system a priori, however, they often have trouble selecting a suitable meta-model. In order to provide robust prediction performance, ensembles of meta-models have been developed which linearly combines stand-alone meta-models. In this study, we propose a new pointwise ensemble of meta-models whose weights vary according to the prediction point of interest. The suggested method can include all kinds of stand-alone meta-models for ensemble construction, and can interpolate real system response values at training points, even if regression models are included as stand-alone meta-models. To evaluate the effectiveness of the proposed method, its prediction performance is compared with those of existing ensembles of meta-models using well-known mathematical functions. The results show that our pointwise ensemble of meta-models provides more robust and accurate predictions than existing models for a majority of test problems.     

The VALU3S ECSEL project: Verification and validation of automated systems safety and security

Manufacturers of automated systems and their components have been allocating an enormous amount of time and effort in R&D activities, which led to the availability of prototypes demonstrating new capabilities as well as the introduction of such systems to the market within different domains. Manufacturers need to make sure that the systems function in the intended way and according to specifications. This is not a trivial task as system complexity rises dramatically the more integrated and interconnected these systems become with the addition of automated functionality and features to them. This effort translates into an overhead on the V&V (verification and validation) process making it time-consuming and costly. In this paper, we present VALU3S, an ECSEL JU (joint undertaking) project that aims to evaluate the state-of-the-art V&V methods and tools, and design a multi-domain framework to create a clear structure around the components and elements needed to conduct the V&V process. The main expected benefit of the framework is to reduce time and cost needed to verify and validate automated systems with respect to safety, cyber-security, and privacy requirements. This is done through identification and classification of evaluation methods, tools, environments and concepts for V&V of automated systems with respect to the mentioned requirements. VALU3S will provide guidelines to the V&V community including engineers and researchers on how the V&V of automated systems could be improved considering the cost, time and effort of conducting V&V processes. To this end, VALU3S brings together a consortium with partners from 10 different countries, amounting to a mix of 25 industrial partners, 6 leading research institutes, and 10 universities to reach the project goal.     

Approximate declarative semantics for rule base anomalies

Despite the fact that there has been a surge of publications in verification and validation of knowledge-based systems and expert systems in the past decade, there are still gaps in the study of verification and validation (V&V) of expert systems, not the least of which is the lack of appropriate semantics for expert system programming languages. Without a semantics, it is hard to formally define and analyze knowledge base anomalies such as inconsistency and redundancy, and it is hard to assess the effectiveness of V&V tools, methods and techniques that have been developed or proposed. In this paper, we develop an approximate declarative semantics for rule-based knowledge bases and provide a formal definition and analysis of knowledge base inconsistency, redundancy, circularity and incompleteness in terms of theories in the first order predicate logic. In the paper, we offer classifications of commonly found cases of inconsistency, redundancy, circularity and incompleteness. Finally, general guidelines on how to remedy knowledge base anomalies are given.     

Validation of intelligent systems: a critical study and a tool

One of the most important phases in the methodology for the development of intelligent systems is that corresponding to the evaluation of the performance of the implemented product. This process is popularly known as verification and validation (V&V). The majority of tools designed to support the V&V process are preferentially directed at verification in detriment to validation, and limited to an analysis of the internal structures of the system. The authors of this article propose a methodology for the development of a results-oriented validation, and a tool (SHIVA) is presented which facilitates the fulfilment of the tasks included in the methodology, whilst covering quantitative as well as heuristic aspects. The result is an intelligent tool for the validation of intelligent systems.     

A multi-level approach to modeling language extension in the Enterprise Systems Domain

As the number and diversity of technologies involved in building enterprise systems continues to grow so does the importance of modeling tools that are able to present customized views of enterprise systems to different stakeholders according to their needs and skills. Moreover, since the range of required view types is continuously evolving, it must be possible to extend and enhance the languages and services offered by such tools on an ongoing basis. However, this can be difficult with today׳s modeling tools because the meta-models that define the languages, views and services they support are usually hardwired and thus not amenable to extensions. In practice, therefore, various workarounds have to be used to extend a tool׳s underlying meta-model. Some of these are built into the implemented modeling standards (e.g. UML 2, BPMN 2.0 and ArchiMate 2.0) while others have to be applied by complementary, external tools (e.g. annotation models). These techniques not only increase accidental complexity, they also reduce the ability of the modeling tool to ensure adherence to enterprise rules and constraints. In this paper we discuss the strengths and weaknesses of the various approaches for language extension and propose a modeling framework best able to support the main extension scenarios currently found in practice today.     

Meta-environment and executable meta-language using smalltalk: an experience report

Object-oriented modelling languages such as EMOF are often used to specify domain specific meta-models. However, these modelling languages lack the ability to describe behavior or operational semantics. Several approaches have used a subset of Java mixed with OCL as executable meta-languages. In this experience report we show how we use Smalltalk as an executable meta-language in the context of the Moose reengineering environment. We present how we implemented EMOF and its behavioral aspects. Over the last decade we validated this approach through incrementally building a meta-described reengineering environment. Such an approach bridges the gap between a code-oriented view and a meta-model driven one. It avoids the creation of yet another language and reuses the infrastructure and run-time of the underlying implementation language. It offers an uniform way of letting developers focus on their tasks while at the same time allowing them to meta-describe their domain model. The advantage of our approach is that developers use the same tools and environment they use for their regular tasks. Still the approach is not Smalltalk specific but can be applied to language offering an introspective API such as Ruby, Python, CLOS, Java and C#.

Early verification and validation of mission critical systems

Complex software and systems are pervasive in today’s world. In a growing number of fields they come to play a critical role. In order to provide a high assurance level, verification and validation (V&V) should be considered early in the development process. This paper shows how this can be achieved based on a goal-oriented requirements engineering framework which combines complementary semi-formal and formal notations. This allows the analyst to formalize only when and where needed and also preserves optimal communication with stakeholders and developers. For the industrial application of the methodology, a supporting toolbox was developed. It consist of a number of tightly integrated tools for performing V&V tasks at requirements level. This is achieved through the use of (1) a roundtrip mapping between the requirements language and the specific formal languages used in the underlying formal tools (such as SAT or constraint solvers) and (2) graphical views using domain-based representations. This paper will focus on two major and representative tools: the Refinement Checker (about verification) and the Animator (about validation).     

支持MDA的设计模式建模与模型转换方法研究

设计模式是描述某一类问题的通用解决方案,可以提高软件开发的可重用性,但在设计模式建模中存在模式消失和模式组合复杂化等问题,模型的可扩展性低,不利于模型到代码的自动化转换。由此,在MDA框架下,引入角色的建模思想,提出了一种基于Ecore的设计模式建模和模型转换方法,该方法在元模型层抽象并扩展了设计模式通用元素的元模型,使得不同的模式组合模型通过对相同的模式元素元模型进行转换可以获得相应的应用模型,从而增强了设计模式建模的可扩展性和模型转换的通用性,为MDA框架中设计模式建模和模型转换提供了一种有效的途径。     

自动生成GEF图形编辑器的研究与实现

针对当前GEF编辑器开发难度大、开发周期长的问题,设计了一个能够自动生成GEF图形编辑器的MDA工具GEG的体系结构。它利用EMF的代码自动生成方法JET和JMerge,以及EMF.edit提供的适配器机制,生成了一个完整的基于Eclipse平台的图形编辑器插件。在系统设计和实现过程中,引入了配置元模型和视图元模型。     

EQUITAS: A tool-chain for functional safety and reliability improvement in automotive systems

To support advanced features such as hybrid engine control, intelligent energy management, and advanced driver assistance systems, automotive embedded systems must use advanced technologies. As a result, systems are becoming distributed and include dozens of Electronic Control Units (ECU). On the one hand, this tendency raises the issue of robustness and reliability, due to the increase in the error ratio with the integration level and the clock frequency. On the other hand, due to a lack of automation, software Validation and Verification (V&V) tends to swallow up 40% to 50% of the total development cost. The ``Enhanced Quality Using Intensive Test Analysis on Simulators'' (EQUITAS¹) project aims (1) to improve reliability and functional safety and (2) to limit the impact of software V&V on embedded systems costs and time-to-market. These two achievements are obtained by (1) developing a continuous tool-chain to automate the V&V process, (2) improving the relevance of the test campaigns by detecting redundant tests using equivalence classes, (3) providing assistance for hardware failure effect analysis (FMEA) and finally (4) assessing the tool-chain under the ISO 26262 requirements.     

基于元元模型的多维元数据管理研究与实现

分析了目前元数据管理的研究现状和存在的问题;按照OMG的MOF规范,建立了统一的MOF元元模型,对不同领域的元模型进行统一描述;提出了一个高度可集成可扩展的元数据管理框架和元模型建模规范;介绍了主题与元模型的相容约束规则以及主题与元数据的访问约束规则;通过采用对元数据按主题进行动态分类的方式,实现了对元数据的多维管理.     

TOTEM: Reconciling multi-level modelling with standard two-level modelling

Model driven Engineering (MDE) advocates the active use of models throughout the different software development phases. In MDE, models are described using meta-models, one meta-level above. This approach effectively leaves developers with one single meta-level to create their models. However, there are scenarios where the use of multiple meta-levels results in simpler models with less accidental complexity. Hence, to simplify modelling in these cases, several multi-level modelling approaches and tools have recently emerged to increase the flexibility in modelling. While they provide advanced primitives to simplify modelling, there are possibilities to improve interoperability with mainstream two-level modelling approaches based on the Meta-Object Facility (MOF) standard of the Object Management Group (OMG), and achieve wider adoption.For this purpose, we first characterise the design space of multi-level modelling approaches using a feature model. On such a basis, we provide a detailed comparison of existing multi-level modelling tools, identifying gaps and research opportunities. As a result of this gap analysis, we propose a new approach to multi-level modelling that embeds multiple meta-levels within one meta-model (i.e., encoding objects as classes, and instantiation as inheritance), and a tool – called TOTEM – which implements these concepts. The tool capabilities and its benefits in terms of interoperability with mainstream, standard modelling frameworks are illustrated through an example, as well as with empirical and analytical evaluations.     

Automatic Generation of Test Oracles—From Pilot Studies to Application

We describe a progression from pilot studies to development and use of domain-specific verification and validation (V&V) automation. Our domain is the testing of an AI planning system that forms a key component of an autonomous spacecraft. We used pilot studies to ascertain opportunities for, and suitability of, automating various analyses whose results would contribute to V&V in our domain. These studies culminated in development of an automatic generator of automated test oracles. This was then applied and extended in the course of testing the spacecraft's AI planning system.Richardson et al. (1992, In Proceedings of the 14th International Conference on Software Engineering, Melbourne, Australia, pp. 105–118), presents motivation for automatic test oracles, and considered the issues and approaches particular to test oracles derived from specifications. Our work, carried through from conception to application, confirms many of their insights. Generalizing from our specific domain, we present some additional insights and recommendations concerning the use of test oracles for V&V of knowledge-based systems.