Extra-functional Properties Research Articles

Information-flow interfaces

AbstractContract-based design is a promising methodology for taming the complexity of developing sophisticated systems. A formal contract distinguishes between assumptions, which are constraints that the designer of a component puts on the environments in which the component can be used safely, and guarantees, which are promises that the designer asks from the team that implements the component. A theory of formal contracts can be formalized as an interface theory, which supports the composition and refinement of both assumptions and guarantees. Although there is a rich landscape of contract-based design methods that address functional and extra-functional properties, we present the first interface theory designed to ensure system-wide security properties. Our framework provides a refinement relation and a composition operation that support both incremental design and independent implementability. We develop our theory for both stateless and stateful interfaces. Additionally, we introduce information-flow contracts where assumptions and guarantees are sets of flow relations. We use these contracts to illustrate how to enrich information-flow interfaces with a semantic view. We illustrate the applicability of our framework with two examples inspired by the automotive domain.

ExTrA: Explaining architectural design tradeoff spaces via dimensionality reduction

In software design, guaranteeing the correctness of run-time system behavior while achieving an acceptable balance among multiple quality attributes remains a challenging problem. Moreover, providing guarantees about the satisfaction of those requirements when systems are subject to uncertain environments is even more challenging. While recent developments in architectural analysis techniques can assist architects in exploring the satisfaction of quantitative guarantees across the design space, existing approaches are still limited because they do not explicitly link design decisions to satisfaction of quality requirements. Furthermore, the amount of information they yield can be overwhelming to a human designer, making it difficult to see the forest for the trees. In this paper we present ExTrA (Explaining Tradeoffs of software Architecture design spaces), an approach to analyzing architectural design spaces that addresses these limitations and provides a basis for explaining design tradeoffs. Our approach employs dimensionality reduction techniques employed in machine learning pipelines like Principal Component Analysis (PCA) and Decision Tree Learning (DTL) to enable architects to understand how design decisions contribute to the satisfaction of extra-functional properties across the design space. Our results show feasibility of the approach in two case studies and evidence that combining complementary techniques like PCA and DTL is a viable approach to facilitate comprehension of tradeoffs in poorly-understood design spaces.

On the Functional and Extra-Functional Properties of IMU Fusion Algorithms for Body-Worn Smart Sensors.

In this work, four sensor fusion algorithms for inertial measurement unit data to determine the orientation of a device are assessed regarding their usability in a hardware restricted environment such as body-worn sensor nodes. The assessment is done for both the functional and the extra-functional properties in the context of human operated devices. The four algorithms are implemented in three data formats: 32-bit floating-point, 32-bit fixed-point and 16-bit fixed-point and compared regarding code size, computational effort, and fusion quality. Code size and computational effort are evaluated on an ARM Cortex M0+. For the assessment of the functional properties, the sensor fusion output is compared to a camera generated reference and analyzed in an extensive statistical analysis to determine how data format, algorithm, and human interaction influence the quality of the sensor fusion. Our experiments show that using fixed-point arithmetic can significantly decrease the computational complexity while still maintaining a high fusion quality and all four algorithms are applicable for applications with human interaction.

Online Testing of Dynamic Reconfigurations w.r.t. Adaptation Policies

Self-adaptation of complex systems is a very active domain of research with numerous application domains. Component systems are designed as sets of components that may reconfigure themselves according to adaptation policies, which describe needs for reconfiguration. In this context, an adaptation policy is designed as a set of rules that indicate, for a given set of configurations, which reconfiguration operations can be triggered, with fuzzy values representing their utility. The adaptation policy has to be faithfully implemented by the system, especially w.r.t. the utility occurring in the rules, which are generally specified for optimizing some extra-functional properties (e.g. minimizing resource consumption). In order to validate adaptive systems’ behaviour, this paper presents a model-based testing approach, which aims to generate large test suites in order to measure the occurrences of reconfigurations and compare them to their utility values specified in the adaptation rules. This process is based on a usage model of the system used to stimulate the system and provoke reconfigurations. As the system may reconfigure dynamically, this online test generator observes the system responses and evolution in order to decide the next appropriate test step to perform. As a result, the relative frequencies of the reconfigurations can be measured in order to determine whether the adaptation policy is faithfully implemented. To illustrate the approach the paper reports on experiments on the case study of platoons of autonomous vehicles.

Additively manufactured Ti6Al4V lattice structures: mechanical characterization and numerical investigation

The interest in manufacturing complex devices with integrated extra-functional properties is steadily growing for high technological application fields, such as the aerospace and biomedical ones. Among advanced methods of manufacturing, additive manufacturing allows to produce complex three-dimensional geometries, like lattice structures, which possess mechanical and functional properties unachievable by their constituent materials. The present work investigates Ti6Al4V lattice structures produced by Selective Laser Melting (SLM) through a combined experimental and numerical campaign. The effects of the relative density of the elementary cell, building direction (along horizontal and vertical building directions), and sample condition (as-built and heat treated at 850°C) on the mechanical properties of the lattice structures are investigated through tensile testing. Finite element analysis is performed to analyze the stress/strain distribution due to the different investigated effects. The results provide useful insight into the deformation/failure mechanisms, stress concentrations, and mechanical properties of the studied structures as well as into their correlation to the relative density and printing process parameters. The resulting performances of the lattice structures are compared with the ones of the bulk samples.

A Platform-Aware Model-Driven Embedded Software Engineering Process Based on Annotated Analysis Models

In this work a platform-aware model-driven engineering process for building component-based embedded software systems using annotated analysis models is described. The process is supported by a framework, called MICOBS, that allows working with different component technologies and integrating different tools that, independently of the component technology, enable the analysis of non-functional properties based on the principles of composability and compositionality. An actor, called Framework Architect, is responsible for this integration. Three other actors take a relevant part in the analysis process. The Component Provider supplies the components, while the Component Tester is in charge of their validation. The latter also feeds MICOBS with the annotated analysis models that characterize the extra-functional properties of the components for the different platforms on which they can be deployed. The Application Architect uses these components to build new systems, performing the trade-off between different alternatives. At this stage, and in order to verify that the final system meets the extra-functional requirements, the Application Architect uses the reports generated by the integrated analysis tools. This process has been used to support the validation and verification of the on-board application software for the Instrument Control Unit of the Energetic Particle Detector of the Solar Orbiter mission.

Incremental, Distributed, and Concurrent Service Coordination for Reliable and Deterministic Systems-of-Systems

Systems-of-systems (SoS) are gaining increasing attention for the realization of safety-relevant applications with reliability and real-time requirements, by coordinating autonomous constituent systems from different application areas. For a given application that is initiated at a constituent system, the provision and use of services between constituent systems must be coordinated. This involves identifying constituent systems that can provide the services, optimizing the use of the services driven by extra-functional properties, performing admission control for service provision, reserving resources for provided services, and recursively using services from subcontracted constituent systems to realize service provisions. In this article, new conceptual models with service provisioning for reliable and deterministic SoS applications, as well as, distributed algorithms for the discovery, optimized selection, and admission of service provisions are introduced. The proposed models will result in a two-step admission control algorithm with short- and long-term admissions based on schedulabiliy tests, resulting in service provisions between constituent systems. Furthermore, this article will investigate the integration of cloud resources for the on-demand instantiation of services. The models and the service coordination are evaluated in a use case from the health-care domain, which investigates the execution time and the scalability of the service coordination.

Development of a novel component-based open CNC software system

Component-based software development (CBSD) is widely utilized to develop open CNC applications. It aims to build an open CNC application by composing a set of components, each implementing specific CNC sub-domain logic. Components conform to a certain component model to keep conformant interactive behaviors. Due to there is no standard granularity to decompose CNC domain and no general component model, as well as seldom consider extra-functional properties, components are heterogeneous. Moreover, they have a direct dependency rather than depending on abstractions. In a nutshell, there are many open-source CNC applications built by heterogeneous and tightly coupled components. They can implement CNC functionality but are good at functional extension and reconfiguration. In this paper, we apply CBSD and dependency inversion principle to develop a novel open CNC application which allows customizing CNC functionality. Specifically, a new granularity to decompose CNC domain is proposed. A special sub-domain is designed to encapsulate the execution logic of other sub-domains at an abstract level and instantiate concrete implementation details at runtime according to configuration. The functional properties of sub-domains are exposed via abstractions. Therefore, as long as re-writing the execution logic and configuring corresponding implementation details, CNC functionality can be extended or reconfigured. A prototype and several components have been developed to test the performance of the application.

The ANTAREX domain specific language for high performance computing

The ANTAREX project relies on a Domain Specific Language (DSL) based on Aspect Oriented Programming (AOP) concepts to allow applications to enforce extra functional properties such as energy-efficiency and performance and to optimize Quality of Service (QoS) in an adaptive way. The DSL approach allows the definition of energy-efficiency, performance, and adaptivity strategies as well as their enforcement at runtime through application autotuning and resource and power management. In this paper, we present an overview of the key outcome of the project, the ANTAREX DSL, and some of its capabilities through a number of examples, including how the DSL is applied in the context of the project use cases.

SystemC-AMS Thermal Modeling for the Co-simulation of Functional and Extra-Functional Properties

Temperature is a critical property of smart systems, due to its impact on reliability and to its inter-dependence with power consumption. Unfortunately, the current design flows evaluate thermal evolution ex-post on offline power traces. This does not allow to consider temperature as a dimension in the design loop, and it misses all the complex inter-dependencies with design choices and power evolution. In this article, by adopting the functional language SystemC-AMS (Analog Mixed Signal), we propose a method to enable thermal/power/functional co-simulation. The system thermal model is built by using state-of-the-art circuit equivalent models, by exploiting the support for electrical linear networks intrinsic of SystemC-AMS. The experimental results will show that the choice of SystemC-AMS is a winning strategy for building a simultaneous simulation of multiple functional and extra-functional properties of a system. The generated code exposes an accuracy comparable to that of the reference thermal simulator HotSpot. Additionally, the initial overhead due to the general purpose nature of SystemC-AMS is compensated by the surprisingly high performance of transient simulation, with speedups as high as two orders of magnitude.

Nanoparticle intercalation-modulated stretchable conductive graphene fibers with combined photoelectric properties

Graphene fiber with superb properties poses an important role in future functional fibers and devices. However, the fibers made of neat graphene sheets remain brittle and the electrical conductivity of graphene/polymer fibers is very poor, which all together hiders wide use of graphene fibers. It remains a big challenge to obtain functional graphene fibers with combined electrical and mechanical properties. Here, we demonstrate a simple wet spinning of stretchable conductive graphene fibers through uniform intercalation of TiO2 nanoparticles between graphene sheets. The TiO2 nanoparticles induce formation of numerous winkles on graphene sheets which all together makes the composite fibers show combined superb mechanical, electrical and photoelectric performances. With increasing of TiO2 from 0 to 50%, the fibers still have comparable electrical conductivities, while the breakage elongation greatly increases from less than 6% to higher than 20%, and the fibers with 50% TiO2 have excellent tensile recovery within 15% strain. With TiO2 combined, the fibers have extra functional properties in photoelectric response, which can be further improved by oxygen plasma etching, and no obvious decay is observed even after 100 bending cycles. This study provides useful guidelines for designing of functional conductive graphene fibers with highly stretchable performance towards future uses.

A Layered Methodology for the Simulation of Extra-Functional Properties in Smart Systems

Smart systems represent a broad class of intelligent, miniaturized devices incorporating functionality like sensing, actuation, and control. In order to support these functions, they must include sophisticated and heterogeneous components, such as sensors and actuators, multiple power sources and storage devices, digital signal processing, and wireless connectivity. The high degree of heterogeneity typical of smart systems has a heavy impact on their design: the challenges are not in fact restricted to their functionality, but are also related to a number of extra-functional properties, including power consumption, temperature, and aging. Current simulation- or model-based design approaches do not target a smart system as a whole, but rather single domains (digital, analog, power devices, etc.) or properties. This paper tries to overcome this limitation by proposing a framework for the concurrent simulation of both functionality and such extra-functional properties. The latter are modeled as different information flows, managed by dedicated “virtual buses” and formalized through the adoption of IP-XACT. SystemC, through the support of physical and continuous time modeling provided by its analog and mixed signal extension, is used to implement both functional and extra-functional models. Experimental results show the efficiency, accuracy and modularity of the proposed approach on an example case study, in which substantial speedups with respect to standard model-based design tools go along with a very high degree of accuracy (<; 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> %). Furthermore, the case study highlights that the proposed framework allows to easily capture at run time the mutual impact of properties, e.g., in case of power and temperature.

CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties

The increasing processing power of today’s HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels. This article presents an overview of the CONTREX European project, its main innovative technology (extension of a model based design approach, functional and extra-functional analysis with executable models and run-time management) and the final results of three industrial use-cases from different domain (avionics, automotive and telecommunication).

Multi-objective exploration of architectural designs by composition of model transformations

Designing software architectures and optimizing them based on extra-functional properties (EFPs) require to identify appropriate design decisions and to apply them on valid architectural elements. Software designers have to check whether the resulting architecture fulfills the requirements and how it positively improves (possibly conflicting) EFPs. In practice, they apply well-known solutions such as design patterns manually. This is time-consuming, error-prone, and possibly sub-optimal. Well-established approaches automate the search of the design space for an optimal solution. They are based model-driven engineering techniques that formalized design decisions as model transformations and architectural elements as components. Using multi-objective optimizations techniques, they explore the design space by randomly selecting a set of components and applying to them variation operators that include a fixed set of predefined design decisions. In this work, we claim that the design space exploration requires to reason on both architectural components as well as model transformations. More specifically, we focus on possible instantiations of model transformations materialized as the application of model transformation alternatives on a set of architectural components. This approach was prototyped in RAMSES, a model transformation and code generation framework. Experimental results show the capability of our approach (i) to combine evolutionary algorithms and model transformation techniques to explore efficiently a set of architectural alternatives with conflicting EFPs, (ii) to instantiate, and select transformation instances that generate architectures satisfying stringent structural constraints, and (iii) to explore design spaces by chaining more than one transformation. In particular, we evaluated our approach on EFPs, architectures, and design alternatives inspired from the railway industry by chaining model transformations dedicated to implement safety design patterns and software components allocation on a multi-processor hardware platform.

Exploiting traceability uncertainty between software architectural models and extra-functional results

Automatic generation of traceability links: architecture vs extrafunctional results.Traceability uncertainty mitigated by extra-functional patterns and antipatterns.Validation on three case studies: two academic projects and one industrial system.Experimental results: performance improvement up to 56.6% and uncertainty reduction up to 28.5%. Deriving extra-functional properties (e.g., performance, security, reliability) from software architectural models is the cornerstone of software development as it supports the designers with quantitative predictions of system qualities. However, the problem of interpreting results from quantitative analysis of extra-functional properties is still challenging because it is hard to understand how the analysis results (e.g., response time, data confidentiality, mean time to failure) trace back to the architectural model elements (i.e., software components, interactions among components, deployment nodes).The goal of this paper is to automate the traceability between software architectural models and extra-functional results, such as performance and security, by investigating the uncertainty while bridging these two domains. Our approach makes use of extra-functional patterns and antipatterns, such as performance antipatterns and security patterns, to deduce the logical consequences between the architectural elements and analysis results and automatically build a graph of traces, thus to identify the most critical causes of extra-functional flaws. We developed a tool that jointly considers SOftware and Extra-Functional concepts (SoEfTraceAnalyzer), and it automatically builds model-to-results traceability links. This paper demonstrates the effectiveness of our automated and tool supported approach on three case studies, i.e., two academic research projects and one industrial system.

Architecture optimization: speed or accuracy? both!

Embedded systems are becoming more and more complex, thus demanding innovative means to tame their challenging development. Among others, early architecture optimization represents a crucial activity in the development of embedded systems to maximise the usage of their limited resources and to respect their real-time requirements. Typically, architecture optimization seeks good architecture candidates based on model-based analysis. Leveraging abstractions and estimates, this analysis usually produces approximations useful for comparing architecture candidates. Nonetheless, approximations do not provide enough accuracy in estimating crucial extra-functional properties. In this article, we provide an architecture optimization framework that profits from both the speed of model-based predictions and the accuracy of execution-based measurements. Model-based optimization rapidly finds a good architecture candidate, which is refined through optimization based on monitored executions of automatically generated code. Moreover, the framework enables the developer to leverage her optimization experience. More specifically, the developer can use runtime monitoring of generated code execution to manually adjust task allocation at modeling level, and commit the changes without halting execution. In the article, our architecture optimization mechanism is first described from a general point of view and then exploited for optimizing the allocation of software tasks to the processing cores of a multicore embedded system; we target extra-functional properties that can be concretely represented and automatically compared for different architectural alternatives (such as memory consumption, energy consumption, or response-time).

On applying multiple criteria decision analysis in embedded systems design

We focus here on the application of multi critera decision analysis (MCDA) techniques in hardware/software partitioning activities to be used in the design and deployment of embedded systems. Our goal is to identify the best existing methods and tools suitable to support the approach we have taken for the partitioning process. We provide this via a survey of the most well-known MCDA methods and tools (for a specific class of MCDA methods called multi attribute decision making. We identify a set of criteria that need to be addressed, in some way, by the methods, and implemented by related tools. These "11-suitability criteria" help us in deciding the appropriateness of the analysed methods and tools for the envisaged partitioning approach. In brief, we are interested that the MCDA methods are taking into account multiple extra-functional properties, expressed by a variety of types, with possible missing values, should enable dependency handling, decision traceability, etc. The conclusion is that there are criteria that are not fulfilled by any of the methods, and hence there is no method or tool that can directly used for the partitioning. However, the results shows the potential of using MCDA in the partitioning process and provide a good starting point for future research activities.

Embedded Systems Software Architecture

Embedded Systems are the dominate type of computer systems today; they span a range from small systems that include a simple platform integrated with sensors and actuators, to large distributed systems consisting of hundreds, or possibly thousand, intensely interactive nodes. In recent years Software has become the most important part of Embedded Systems – it implements the complex system functionality, is a currier of the system integration, and it is enabler of important extra-functional system properties. In many aspects, software for Embedded Systems has reached functional complexity of general-purpose software but faces severe constraints. This special issue includes six research papers that address some of the mentioned challenges.

What Industry Needs from Architectural Languages: A Survey

Many times we are faced with the proliferation of definitions, concepts, languages, and tools in certain (research) topics. But often there is a gap between what is provided by existing technologies and what is needed by their users. The strengths, limitations, and needs of the available technologies can be dubious. The same applies to software architectures, and specifically to languages designed to represent architectural models. Tens of different architectural languages have been introduced by the research and industrial communities in the last two decades. However, it is unclear if they fulfill the user's perceived needs in architectural description. As a way to plan for next generation languages for architectural description, this study analyzes practitioners' perceived strengths, limitations, and needs associated with existing languages for software architecture modeling in industry. We run a survey by interviewing 48 practitioners from 40 different IT companies in 15 countries. Each participant is asked to fill in a questionnaire of 51 questions. By analyzing the data collected through this study, we have concluded that 1) while practitioners are generally satisfied with the design capabilities provided by the languages they use, they are dissatisfied with the architectural language analysis features and their abilities to define extra-functional properties; 2) architectural languages used in practice mostly originate from industrial development instead of from academic research; 3) more formality and better usability are required of an architectural language.

Component Models for Reasoning

The world of component-based systems is as appealing as it is challenging. Components, as first-class citizens of component-based systems, serve as the main units of encapsulated functionality and also units of composition, with the intention to improve development efficiency and software quality through reusability, extensibility and analyzability of software. These benefits are obtained especially when the components are understood by means of a formally well-defined component model, amenable to effective reasoning on functional and extra-functional properties at unit- as well as system-level. In this article we present the basic concepts of component-based design, emphasizing the characteristics of different types of component compositions, which dictate particular trade-offs between the degree of assurance and design flexibility. We show that rich and semantically well-defined component models with encapsulated reasoning information enable prediction of the system behavior and in general the system functional and non-functional properties. In this way, the development process is significantly simplified. We illustrate the concept by giving a short overview of the ProCom component model that is designed for enabling predictability in the embedded and real-time systems domain.