Verifying big data topologies by-design: a semi-automated approach

Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topics. However, architectures that process big data involve many different components interconnected via semantically different connectors. Such complex architectures make possible refactoring of the applications a difficult task for software architects, as applications might be very different with respect to the initial designs. As an aid to designers and developers, we developed OSTIA (Ordinary Static Topology Inference Analysis) that allows detecting the occurrence of common anti-patterns across big data architectures and exploiting software verification techniques on the elicited architectural models. This paper illustrates OSTIA and evaluates its uses and benefits on three industrial-scale case-studies

Rapid Prototyping of Domain-Specific Architecture Languages

International audienceSoftware architecture has become a sensitive discipline, which consists in concretizing the user requirements into a set of artifacts that can be used to model and reason about the software to be developed. However, the architect often relies on its own knowledge to map domain-specific requirements onto generic software abstractions. Most of the time, this leads to the definition of repetitive tasks and architecture fragments, which can be particularly error prone. We therefore believe that architects need a more flexible approach to cope with the definition of domain-specific architectures by leveraging general purpose architecture description languages. This paper introduces the FraSCAla framework as an architectural framework that can be used to rapidly prototype and experiment domain-specific ADLs in order to catalyze the definition and to improve the reliability of software architectures. We demonstrate the merits of this approach on two case studies that illustrate component-based architectures exhibiting various categories of architectural patterns

Domain architecture a design framework for system development and integration

The ever growing complexity of software systems has revealed many short-comings in existing software engineering practices and has raised interest in architecture-driven software development. A system\u27s architecture provides a model of the system that suppresses implementation detail, allowing the architects to concentrate on the analysis and decisions that are most critical to structuring the system to satisfy its requirements. Recently, interests of researchers and practi-tioners have shifted from individual system architectures to architectures for classes of software systems which provide more general, reusable solutions to the issues of overall system organization, interoperability, and allocation of services to system components. These generic architectures, such as product line architectures and domain architectures, promote reuse and interoperability, and create a basis for cost effective construction of high-quality systems. Our focus in this dissertation is on domain architectures as a means of development and integration of large-scale, domain-specific business software systems. Business imperatives, including flexibility, productivity, quality, and ability to adapt to changes, have fostered demands for flexible, coherent and enterprise--wide integrated business systems. The components of such systems, developed separately or purchased off the shelf, need to cohesively form an overall compu-tational environment for the business. The inevitable complexity of such integrated solutions and the highly-demanding process of their construction, management, and evolution support require new software engineering methodologies and tools. Domain architectures, prescribing the organization of software systems in a business domain, hold a promise to serve as a foundation on which such integrated business systems can be effectively constructed. To meet the above expectations, software architectures must be properly defined, represented, and applied, which requires suitable methodologies as well as process and tool support. Despite research efforts, however, state-of-the-art methods and tools for architecture-based system development do not yet meet the practical needs of system developers. The primary focus of this dissertation is on developing methods and tools to support domain architecture engineering and on leveraging architectures to achieve improved system development and integration in presence of increased complexity. In particular, the thesis explores issues related to the following three aspects of software technology: system complexity and software architectures as tools to alleviate complexity; domain architectures as frameworks for construction of large scale, flexible, enterprise-wide software systems; and architectural models and representation techniques as a basis for good” design. The thesis presents an archi-tectural taxonomy to help categorize and better understand architectural efforts. Furthermore, it clarifies the purpose of domain architectures and characterizes them in detail. To support the definition and application of domain architectures we have developed a method for domain architecture engineering and representation: GARM-ASPECT. GARM, the Generic Architecture Reference Model, underlying the method, is a system of modeling abstractions, relations and recommendations for building representations of reference software architectures. The model\u27s focus on reference and domain architectures determines its main distinguishing features: multiple views of architectural elements, a separate rule system to express constraints on architecture element types, and annotations such as “libraries” of patterns and “logs” of guidelines. ASPECT is an architecture description language based on GARM. It provides a normalized vocabulary for representing the skeleton of an architecture, its structural view, and establishes a framework for capturing archi-tectural constraints. It also allows extensions of the structural view with auxiliary information, such as behavior or quality specifications. In this respect, ASPECT provides facilities for establishing relationships among different specifications and gluing them together within an overall architectural description. This design allows flexibility and adaptability of the methodology to the specifics of a domain or a family of systems. ASPECT supports the representation of reference architectures as well as individual system architectures. The practical applicability of this method has been tested through a case study in an industrial setting. The approach to architecture engineering and representation, presented in this dissertation, is pragmatic and oriented towards software practitioners. GARM-ASPECT, as well as the taxonomy of architectures are of use to architects, system planners and system engineers. Beyond these practical contributions, this thesis also creates a more solid basis for expbring the applicability of architectural abstractions, the practicality of representation approaches, and the changes required to the devel-opment process in order to achieve the benefits from an architecture-driven software technology

Connecting the Brain to Itself through an Emulation.

Pilot clinical trials of human patients implanted with devices that can chronically record and stimulate ensembles of hundreds to thousands of individual neurons offer the possibility of expanding the substrate of cognition. Parallel trains of firing rate activity can be delivered in real-time to an array of intermediate external modules that in turn can trigger parallel trains of stimulation back into the brain. These modules may be built in software, VLSI firmware, or biological tissue as in vitro culture preparations or in vivo ectopic construct organoids. Arrays of modules can be constructed as early stage whole brain emulators, following canonical intra- and inter-regional circuits. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors. In this manner, closed-loop brain-computer interface pilot clinical trials can advance strong artificial intelligence development and forge new therapies to restore independence in children and adults with neurological conditions

PATTERN MATCHING IN MODELS

The goal of this paper is to investigate how such a pattern matching could be performed on models,including the definition of the input language as well as the elaboration of efficient matchingalgorithms. Design patterns can be considered reusable micro-architectures that contribute to anoverall system architecture. Frameworks are also closely related to design patterns. Componentsoffer the possibility to radically change the behaviors and services offered by an application bysubstitution or addition of new components, even a long time after deployment. Software testing isanother aspect of reliable development. Testing activities mainly consist in ensuring that a systemimplementation conforms to its specifications

Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

Formalizing the Execution Context of Behavior Trees for Runtime Verification of Deliberative Policies

In this paper, we enable automated property verification of deliberative components in robot control architectures. We focus on formalizing the execution context of Behavior Trees (BTs) to provide a scalable, yet formally grounded, methodology to enable runtime verification and prevent unexpected robot behaviors. To this end, we consider a message-passing model that accommodates both synchronous and asynchronous composition of parallel components, in which BTs and other components execute and interact according to the communication patterns commonly adopted in robotic software architectures. We introduce a formal property specification language to encode requirements and build runtime monitors. We performed a set of experiments, both on simulations and on the real robot, demonstrating the feasibility of our approach in a realistic application and its integration in a typical robot software architecture. We also provide an OS-level virtualization environment to reproduce the experiments in the simulated scenario