A GRL-compliant iStar extension for collaborative cyber-physical systems

Collaborative cyber-physical systems are capable of forming networks at runtime to achieve goals that are unachievable for individual systems. They do so by connecting to each other and exchanging information that helps them coordinate their behaviors to achieve shared goals. Their highly complex dependencies, however, are difficult to document using traditional goal modeling approaches. To help developers of collaborative cyber-physical systems leverage the advantages of goal modeling approaches, we developed a GRL-compliant extension to the popular iStar goal modeling language that takes the particularities of collaborative cyber-physical systems and their developers’ needs into account. In particular, our extension provides support for explicitly distinguishing between the goals of the individual collaborative cyber-physical systems and the network and for documenting various dependencies not only among the individual collaborative cyber-physical systems but also between the individual systems and the network. We provide abstract syntax, concrete syntax, and well-formedness rules for the extension. To illustrate the benefits of our extension for goal modeling of collaborative cyber-physical systems, we report on two case studies conducted in different industry domains.

Tunnel Parsing with counted repetitions

The article describes a new and efficient algorithm for parsing, called Tunnel Parsing, that parses from left to right on the basis of a context-free grammar without left recursion and rules that recognize empty words. The algorithm is applicable mostly for domain-specific languages. In the article, particular attention is paid to the parsing of grammar element repetitions. As a result of the parsing, a statically typed concrete syntax tree is built from top to bottom, that accurately reflects the grammar. The parsing is not done through a recursion, but through an iteration. The Tunnel Parsing algorithm uses the grammars directly without a prior refactoring and is with a linear time complexity for deterministic context-free grammars.

DSML4CS

Cyber physical systems (CPS's) are a kind of complex system with highly integrated interaction between computing resources and physical environment in a network environment. There are some challenges in modeling and simulation of heterogeneous CPS due to its hybrid and heterogenous characteristics. To address the issue, we propose an executable domain specific modeling language for co-simulation (DSML4CS) to model the co-simulation of CPS. According to the construction method of domain modeling language, we present the abstract syntax, concrete syntax and operational semantics of DSML4CS. We also propose a flexible co-simulation mechanism, which supports partial step revision of specific co-simulation process with the state event fault-tolerant mechanism. The co-simulation language for heterogeneous CPS is implemented based on the GEMOC platform. Our aim is to provide the co-simulation service in CPS. The usability of DSML4CS is illustrated with a case study of a temperature control system in an energy-aware building.

Abstract-Syntax-Driven Development of Oberon-0 Using YAJCo

YAJCo is a tool for the development of software languages based on an annotated language model. The model is represented by Java classes with annotations defining their mapping to concrete syntax. This approach to language definition enables the abstract syntax to be central point of the development process, instead of concrete syntax. In this paper a case study of Oberon-0 programming language development is presented. The study is based on the LTDA Tool Challenge and showcases details of abstract and concrete syntax definition using YAJCo, as well as implementation of name resolution, type checking, model transformation and code generation. The language was implemented in modular fashion to demonstrate language extension mechanisms supported by YAJCo.

Model Driven Development Applied to Complex Event Processing for Near Real-Time Open Data

Nowadays, data are being produced like never before because the use of the Internet of Things, social networks, and communication in general are increasing exponentially. Many of these data, especially those from public administrations, are freely offered using the open data concept where data are published to improve their reutilisation and transparency. Initially, the data involved information that is not updated continuously such as budgets, tourist information, office information, pharmacy information, etc. This kind of information does not change during large periods of time, such as days, weeks or months. However, when open data are produced near to real-time such as air quality sensors or people counters, suitable methodologies and tools are lacking to identify, consume, and analyse them. This work presents a methodology to tackle the analysis of open data sources using Model-Driven Development (MDD) and Complex Event Processing (CEP), which help users to raise the abstraction level utilised to manage and analyse open data sources. That means that users can manage heterogeneous and complex technology by using domain concepts defined by a model that could be used to generate specific code. Thus, this methodology is supported by a domain-specific language (DSL) called OpenData2CEP, which includes a metamodel, a graphical concrete syntax, and a model-to-text transformation to specific platforms, such as complex event processing engines. Finally, the methodology and the DSL have been applied to two near real-time contexts: the analysis of air quality for citizens’ proposals and the analysis of earthquake data.

User-friendly Support for Common Mathematical Concepts in a Lightweight Verifier

Machine verification of formal arguments can only increase our confidence in the correctness of those arguments, but the costs of employing machine verification still outweigh the benefits for some common kinds of formal reasoning activities. As a result, usability is becoming increasingly important in the design of formal verification tools. We describe the ``aartifact" lightweight verification system, designed for processing formal arguments involving basic, ubiquitous mathematical concepts. The system is a prototype for investigating potential techniques for improving the usability of formal verification systems. It leverages techniques drawn both from existing work and from our own efforts. In addition to a parser for a familiar concrete syntax and a mechanism for automated syntax lookup, the system integrates (1) a basic logical inference algorithm, (2) a database of propositions governing common mathematical concepts, and (3) a data structure that computes congruence closures of relations found in this database. Together, these components allow the system to better accommodate the expectations of users interested in verifying typical formal arguments involving algebraic manipulations of numbers, sets, vectors, and related operators and predicates. We demonstrate the reasonable performance of this system on typical formal arguments and briefly discuss how the system's design contributes to its usability in two use cases.