Search

This paper combines revealed preference and nonparametric estimation techniques to obtain nonparametric bounds on the distribution of the money metric utility and demand functions over a population of heterogeneous households. Our approach is independent of any functional specification on the household utility functions. Our method applies the weak axiom of revealed preference to a population of heterogeneous households. Although this does not produce the sharpest bounds, we show that it is computationally attractive and provides narrow bounds.We demonstrate the usefulness of our results by applying it to the Consumer Expenditure Survey, a U.S. cross-sectional consumption data set., SCOPUS: ar.j, info:eu-repo/semantics/published

This paper addresses the analysis issue of the complex interactions arising among different components of a warehouse logistic system. In particular, the focus is on a case study related to the handling operations required by the flow of goods within a store of Ikea, located in the center of Italy. The proposed study has been performed using Petri Nets (PNs) as discrete event modelling and simulation framework. In particular, this paper aims to bring out the innovative aspect of the use of PNs as tools to support the functional specifications of warehouse systems, highlighting their strengths and weakness. The goal is to emphasize critical factors in the entire logistic chain within the store and suggest solutions for improving its efficiency. In this regards, PNs have been proved to be quite suitable to easily represent the main features of the departments under consideration, showing at the same time the main logistic processes in which both labor and equipment are involved. The dynamics of the considered logistic system is evaluated, focusing on the three main operating cycles implemented at the Ikea store under consideration. Further, simulating directly the PN model, along with a quantitative analysis, has been possible to identify delays in the complete logistic chain and determine performance indices, such as utilization rate of the resources. Suggestions for improving the productivity of the system are given.

Safety and security are essential properties required by network and mobile applications. The former is concerned with detection of software faults and recovery from failures, and the latter is mainly about specifying and enforcing security policies. However, how to precisely understand and formally specify essential notations in safety and security disciplines, and how to integrate these properties with functional behaviour of programs, are still open issues. For this sake, in this paper, we propose a formal framework, trying to interpret safety and security notations on a common ontology, and combine security property with functional specification in a unified formalism. Our main contributions are two-folds: first, we formally define the notions of fault, failure and error in the traditional state-based model; and secondly, formally define permission mechanism in Android security system, and represent Hoare triples for security-related actions.

Flow cytometry is an invaluable tool utilized in modern biomedical research and clinical applications requiring high throughput, high resolution particle analysis for cytometric characterization and/or sorting of cells and particles as well as for analyzing results from immunocytometric assays. In recent years, research has focused on developing microfluidic flow cytometers with the motivation of creating smaller, less expensive, simpler, and more autonomous alternatives to conventional flow cytometers. These devices could ideally be highly portable, easy to operate without extensive user training, and utilized for research purposes and/or point-of-care diagnostics especially in limited resource facilities or locations requiring on-site analyses. However, designing a device that fulfills the criteria of high throughput analysis, automation and portability, while not sacrificing performance is not a trivial matter. This review intends to present the current state of the field and provide considerations for further improvement by focusing on the key design components of microfluidic flow cytometers. The recent innovations in particle focusing and detection strategies are detailed and compared. This review outlines performance matrix parameters of flow cytometers that are interdependent with each other, suggesting trade offs in selection based on the requirements of the applications. The ongoing contribution of microfluidics demonstrates that it is a viable technology to advance the current state of flow cytometry and develop automated, easy to operate and cost-effective flow cytometers.

Property prices are affected by changing market conditions, incomes and preferences of people. Price trends in natural hazard zones may shift significantly and abruptly after a disaster signalling structural systemic changes in property markets. It challenges accurate market assessments of property prices and capital at risk after major disasters. A rigorous prediction of property prices in this case should ideally be done based only on the most recent sales, which are likely to form a rather small dataset. Hedonic analysis has been long used to understand how various factors contribute to the housing price formation. Yet, the robustness of its assessment is undermined when the analysis needs to be performed on relatively small samples. The purpose of this study is to suggest a model that can be widely applicable and quickly calibrated in a changing environment. We systematically study four statistical models: starting from a typical standard hedonic function and gradually changing its functional specification by reducing the hedonic analysis to some basic property characteristics and applying kriging to control for neighbourhood effects. Across different sample sizes we find that the latter performs consistently better in the out-of-sample predictions than other traditional price prediction methods. We present the specific improvements to the traditional spatial hedonic model that enhance the model’s prediction accuracy. The improved model can be used to monitor price changes in risk-prone areas, accounting for changes in flood risk and at the same time controlling for autonomous market responses to flood risk.

Trusses are load-carrying light-weight structures consisting of bars connected at joints ubiquitously applied in a variety of engineering scenarios. Designing optimal trusses that satisfy functional specifications with a minimal amount of material has interested both theoreticians and practitioners for more than a century. In this paper, we introduce two main ideas to improve upon the state of the art. First, we formulate an alternating linear programming problem for geometry optimization. Second, we introduce two sets of complementary topological operations, including a novel subdivision scheme for global topology refinement inspired by Michell’s famed theoretical study. Based on these two ideas, we build an efficient computational framework for the design of lightweight trusses. We show that our method achieves trusses with smaller volumes and is faster compared with recent state-of-the-art approaches.

Software requirements changes are often inevitable due to the changing nature of running a business and operating the Information Technology (IT) system which supports the business. As such, managing software requirements changes is an important part of software development. Past research has shown that failing to manage software requirements changes effectively is a main contributor to project failure. One of the difficulties in managing requirements changes is the lack of effective methods for communicating changes from the business to the IT professionals. In this paper, we present an approach to managing requirements change by improving the change communication and elicitation through a method of change specification and a method of classification. Change specification provides a way such that communication ambiguities can be avoided between business and IT staff. The change classification mechanism identifies the type of the changes to be made and preliminary identification of the actions to be taken. We illustrate the usefulness of the methods by applying them to a case study of course management system.

Advances in theoretical and computable general equilibrium modeling brought their conceptual foundations more in line with standard microeconomic constructs. This reduced the theoretical gap between welfare measurements using a partial or a general equilibrium approach. However, the separation of the partial and general equilibrium literatures lingers in many applications that this manuscript seeks to bridge. The now shared conceptual foundations, the importance of functional specification, the role of common price movements and closure rules are discussed. The continuing stricture in U.S. Government guidelines against including secondary effects in welfare measures is questioned.

This paper presents natural synthesis, which generalizes the proof-theoretic synthesis technique to support very expressive logic theories. This approach leverages the natural proof methodology and reduces an intractable, unbounded-size synthesis problem to a tractable, bounded-size synthesis problem, which is amenable to be handled by modern inductive synthesis engines. The synthesized program admits a natural proof and is a provably-correct solution to the original synthesis problem. We explore the natural synthesis approach in the domain of imperative data-structure manipulations and present a novel syntax-guided synthesizer based on natural synthesis. The input to our system is a program template together with a rich functional specification that the synthesized program must meet. Our system automatically produces a program implementation along with necessary proof artifacts, namely loop invariants and ranking functions, and guarantees the total correctness with a natural proof. Experiments show that our natural synthesizer can efficiently produce provably-correct implementations for sorted lists and binary search trees. To our knowledge, this is the first system that can automatically synthesize these programs, their functional correctness and their termination in tandem from bare-bones control flow skeletons.

Not only system assurance drives a need for semantically richer relationships across various artifacts, work products, and items of information than are implied in the terms "trace and traceability" as used in current standards and textbooks. This paper deals with the task of working out artifacts in software and system development, their representation, and the analysis and documentation of the relationships between their logical contents--herein referred to as tracing and traceability; this is a richer meaning of traceability than in standards like IEEE STD 830. Among others, key tasks in system development are as follows: capturing, analyzing, and documenting system-level requirements, the step to functional system specifications, the step to architectures given by the decomposition of systems into subsystems with their connections and behavioral interactions. Each of these steps produces artifacts for documenting the development, as a basis for a specification and a design rationale, for documentation, for verification, and impact analysis of change requests. Crucial questions are how to represent and formalize the content of these artifacts and how to relate their content to support, in particular, system assurance. When designing multi-functional systems, key artifacts are system-level requirements, functional specifications, and architectures in terms of their subsystem specifications. Links and traces between these artifacts are introduced to relate their contents. Traceability has the goal to relate artifacts. It is required for instance in standards for functional system safety such as the ISO 26262. An approach to specifying semantic relationships is shown, such that the activity of creating and using (navigating through) these relationships can be supported with automation.

Objectives. The goal of the paper is to identify and generalize the main structural and functional specifications of non-imitative polyphony at its various system levels – elements (components), their relationships and the resulting type of their integrity. Methods. The methodology of the work is based on the сhronotypological approach, which is inextricably linked with the modeling process and makes it possible to comprehend typologically the main manifestations of polyphony in their location on a single historical axis more flexibly, in particular, in the "longitudinal" incision, that is, diachronously. Scientific novelty consists in singling out the logic of polyphonic thinking as an actual and perspective problem now, in particular in the context of ancient and modern music. Conclusions. New methodological bases of selection and systemic consideration of the main varieties of non-imitative polyphony are proposed. As the initial elements are chosen such defining basic components of polyphonic texture, as voices, - relatively autonomous horizontal-melodic structures. As a result of the research, it becomes possible to establish a typology of non-imitative polyphony in accordance with the melos criterion and its further consideration as a certain type of musical thinking.Keywords: non-imitative polyphony, typology, polyphonic systems, musical thinking.

Background Several functional size measurement methods have been proposed. A few ones –like IFPUG and COSMIC methods– are widely used, while others –like Simple Function Points method– are interesting new proposals, which promise to deliver functional size measures via a faster and cheaper measurement process. Objectives Since all functional size measurement methods address the measurement of the same property of software (namely, the size of functional specifications), it is expected that measures provided in a given measurement unit can be converted into a different measurement unit. In this paper, convertibility of IFPUG Function Points, COSMIC Function Points, and Simple Function Points is studied. Method Convertibility is analyzed statistically via regression techniques. Seven datasets, each one containing measures of a set of software applications expressed in IFPUG Function Points, COSMIC Function Points and Simple Function Points, were analyzed. The components of functional size measures (usually known as Base Functional Components) were also involved in the analysis. Results All the analyzed measures appear well correlated to each other. Statistically significant quantitative models were found for all the combinations of measures, for all the analyzed datasets. Several models involving Base Functional Components were found as well. Conclusions From a practical point of view, the paper shows that converting measures from a given functional size unit into another one is viable. The magnitude of the conversion errors is reported, so that practitioners can evaluate if the expected conversion error is acceptable for their specific purposes. From a conceptual point of view, the paper shows that Base Functional Components of a given method can be used to estimate measures expressed in a different measurement unit: this seems to imply that different functional size measurement methods are ‘structurally’ strongly correlated.

The target of the study is to apply the success of engineering psychology to the area of Formal Engineering Methods, concentrating on validating the requirement specification at system analysis phase of a system development process. This paper presents a systematic approach to integrating specification animation into the process of writing requirements specification. The informal specification animation is used to enhance comprehensible interactions in obtaining feedbacks from the user for the purpose of specification validation, which also improve the current specification. A case study for a travel agent system is used to proof the practicality of the proposed approach. An empirical experiment on the approach is also presented to demonstrate the effectiveness of the approach.

Complex decision-making is a prominent aspect of Requirements Engineering. This work presents the Bayesian network Requisites that predicts whether the requirements specification documents have to be revised. We test Requisites’ suitability by means of metrics obtained from a large complex software project. Furthermore, this Bayesian network has been integrated into a software tool by defining a communication interface inside a multilayered architecture. In this way, we add a new decision-making functionality that provides requirements engineers with a feature to explore software requirement specification by combining requirement metrics and the probability values estimated by the Bayesian network.

Paradigms such as smart factory and industry 4.0 enable the collection of data in enterprises. To enhance decision making in design, computational support that is driven by data seems to be beneficial. With this respect, an identification of data-driven use cases is needed. Still, the state of practice does not reflect the potential of data-driven design in engineering product development. With this respect, a method is proposed addressing the business and data understanding in industrial contexts and corresponding Product Lifecycle Management (PLM) environments. This allows to identify use cases for data-driven design taking into account business processes as well as the related data. In the proposed method, first the main process tasks are analyzed using a SIPOC analysis that is followed by a process decomposition to further detail and highlight corresponding applications using Enterprise Architecture principles. Following this, value stream mapping and design process failure mode effect analysis are used to identify sources of waste and the related causes. With this, a feature analysis of given data is proposed to identify use cases and enable to further use standard data science methods like CRISP-DM. The method is validated using the infrastructure of the Pilotfabrik at TU Vienna. The use case shows the applicability of the method to identify features that influence the cost of a product during the manufacturing without changing the functional specifications. The results highlight that different methods need to be combined to attain a comprehensive business and data understanding. Further, a comprehensive view of the processes is yielded that enables to further identify use cases for data-driven design. This work lays a foundation for future research with respect to data-driven design use cases identification in engineering product development.

Formal methods offer a precise and concise way of expressing system requirements which can be tested and validated with formal proofs techniques. However, their application in the development of security aware industrial systems have been associated with high costs due to the difficulty in integrating the functional and security requirements which are generated in an ad hoc manner. Reducing this cost has been a subject of interest in software requirements engineering research. In this paper we propose a formal technique for concurrent generation of functional and security requirements that can help provide a systematic way of accounting for security requirements while specifying the functional requirements of a software. With this technique, the functional behaviors of the system are precisely defined using the Structured Object-Oriented Formal Language (SOFL). The security rules are systematically explored with the results incorporated into the functional specification as constraints. The resultant specification then defines the system functionality that implies the conformance to the security rules. Such a specification can be used as a firm foundation for implementation and testing of the implementation. We discuss the principle of integrating security rules with functional specifications and present a case study to demonstrate the feasibility of our technique.

The SEMFIRE project proposes the development of a multi-robot system to assist in woodland landscaping maintenance tasks for wildfire prevention, addressing in the process several challenges in forestry and field robotics. In this paper, we identify these challenges following a requirement analysis stage and delineated intervention scenarios, proposing detailed specification of the SEMFIRE ecosystem. This includes a technical and functional specification and the integration architecture of the software and hardware system components, with a special focus on the modules responsible for enacting cooperative perception with the team of robots. This team encompasses multiple UAVs and a heavy-duty forestry UGV. A plan for system development, integration and deployment is also described to lay out upcoming work.

Functional specifications describe what program components do: the sufficient conditions to invoke a component's operations. They allow us to reason about the use of components in the closed world setting, where the component interacts with known client code, and where the client code must establish the appropriate pre-conditions before calling into the component. Sufficient conditions are not enough to reason about the use of components in the open world setting, where the component interacts with external code, possibly of unknown provenance, and where the component itself may evolve over time. In this open world setting, we must also consider the necessary} conditions, i.e, what are the conditions without which an effect will not happen. In this paper we propose the language Chainmail for writing holistic specifications that focus on necessary conditions (as well as sufficient conditions). We give a formal semantics for \Chainmail. The core of Chainmail has been mechanised in the Coq proof assistant., 44 pages, 1 Table, 11 Figures

The Federal Circuit’s decisions in Oracle v. Google conflict with this Court’s seminal decision in Baker v. Selden, 101 U.S. 99 (1879), misinterpret Congress’s codification of this Court’s fundamental channeling principle and related limiting doctrines, and upend nearly three decades of sound, well-settled, and critically important decisions of multiple regional circuits on the scope of copyright protection for computer software. Based on the fundamental channeling principle enunciated in Baker v. Selden, as reflected in § 102(b) of the Copyright Act, the functional requirements of APIs for computer systems and devices, like the internal workings of other machines, are outside of the scope of copyright protection even as non-merged aspects of the implementing code for APIs are protectable. Google independently implemented the functional specifications of the 37 APIs at issue and hence did not infringe Oracle’s copyrights. By way of brief illustration, copyright protects artistic and literary works, such as a creative metal sculpture or haiku. Nonetheless, the proprietors of those works cannot complain when third parties replicate elements of that expression that are essential to the operation of a particular machine. For instance, a car manufacturer could secure the ignition switch for its automobiles via a metal key with an original cut pattern on the blade. Although that pattern might be protected as a modern sculpture, the car manufacturer could not use copyright law to prevent others from utilizing the same expression for the purpose of starting the car. The same consideration applies to a car manufacturer that secures a digital ignition switch via entry of a haiku. Copyright law does not bar third parties from utilizing the necessary expression of that otherwise protectable literary work for the purpose of starting the car. The computer program implementing that digital key may be protected by copyright law, but the law places no bar on copying the essential functional elements needed to operate the ignition switch — the haiku text and any other indispensable functional features of the computer program. As Baker v. Selden recognized, copyright law’s limiting doctrines implement a constitutional and statutory balance intended to promote progress by channeling functional features exclusively to the utility patent regime. Although copyright can protect separable expressive features, such as surface ornamentation of an ignition key or non-merged implementing code of a digital ignition key, it does not bar the use of functional specifications — the essential technological elements. Only utility patent law can protect those features.

With the advent of smart contracts that execute on the blockchain ecosystem, a new mode of reasoning is required for developers that must pay meticulous attention to the gas spent by their smart contracts, as well as for optimization tools that must be capable of effectively reducing the gas required by the smart contracts. Super-optimization is a technique which attempts to find the best translation of a block of code by trying all possible sequences of instructions that produce the same result. This paper presents a novel approach for super-optimization of smart contracts based on Max-SMT which is split into two main phases: (i) the extraction of a stack functional specification from the basic blocks of the smart contract, which is simplified using rules that capture the semantics of the arithmetic, bit-wise, relational operations, etc. (ii) the synthesis of optimized blocks which, by means of an efficient Max-SMT encoding, finds the bytecode blocks with minimal gas cost whose stack functional specification is equal (modulo commutativity) to the extracted one. Our experimental results are very promising: we are able to optimize 55.41 % of the blocks, and prove that 34.28 % were already optimal, for more than 61000 blocks from the most called 2500 Ethereum contracts.

The chapter discusses about the complex RTL design and verification scenarios. The chapter even describes the case study of processor architecture and discusses about the thought process while developing the architecture and micro-architecture using the functional specifications of SOC. The chapter is useful to understand the strategies and the processes during the architecture design, RTL design, and verification. The verification planning and the basic verification architecture for the complex designs and strategies are also discussed in this chapter.

In floating-point programs, guard instability occurs when the control flow of a conditional statement diverges from its ideal execution under real arithmetic. This phenomenon is caused by the presence of round-off errors in floating-point computations. Writing programs that correctly handle guard instability often requires expertise on finite precision arithmetic. This paper presents a fully automatic toolchain that generates and formally verifies a guard-stable floating-point C program from its functional specification in real arithmetic. The generated program is instrumented to soundly detect when unstable guards may occur and, in these cases, to issue a warning. The proposed approach combines the PRECiSA floating-point static analyzer, the Frama-C software verification suite, and the PVS theorem prover.

Embedded systems are the principal element in modern electronic devices and in intelligent systems. An Embedded system (ES) is generally composed of hardware blocks (ASIC, FPGA) and software blocks that run on a microprocessor. The hardware (HW) and the software (SW) are executing in collaboration to achieve specific functionalities of the system. The non-functional requirements have a big impact on the design of modern ES. The objective of new design methodologies such as the Co-design is to meet the functional specifications and to achieve the best possible balance between the non-functional requirements. The Hardware Software Partitioning (HSP) is a key step in this process of Co-design. For each block of the system, the HSP decides whether it is more advantageous to be assigned to the hardware part or to the software part. The most important metrics involved in the HSP process, are the cost of the hardware area and the execution time. The majority of previous works study the optimization of one metric with the respect of a given constraint on the other metric. In this paper, we propose a novel approach aimed to simultaneously optimize the hardware area and the execution time of the system. The approach is inspired from the GO game and based on Minimax algorithm. Experimental results show that the proposed approach leads to more optimal solutions compared to the Genetic Algorithm (GA).

To secure a system effectively, you need to take a structured approach. You must fully understand the intended function of the system. What applications are required? What processes and services are needed? Regardless of the type of software, there is a universal requirement that the software performs the desired functions and performs them in the correct manner. Developers know that functional specifications must be met for the software to be satisfactory. As we depend more and more on computers driven by software, we will need systems to do the same—to not only function now but to be protected from malfunction in the future. In this chapter you will learn about the importance of application and data security and procedures required for host security.

This paper describes a model-based flow for the development of Interlocking Systems. The flow starts from a set of specifications in Controlled Natural Language (CNL), that are close to the jargon adopted in by domain experts, but fully formal. From the CNL, a complete SysML specification is extracted, leveraging various forms of diagrams, and enabling automated code generation. Several formal verification methods are supported. A complementary part of the flow supports the extraction of formal properties from legacy Interlocking Systems designed as Relay circuits. The flow is implemented in a comprehensive toolset, and is currently used by railway experts.

International audience; This paper relates to a central problem in synthetic biology, which is that of designing Recombinase-based biological devices by matching a functional specification expressed as a Boolean function. This task is challenging as exploring the space of possibilities is typically unfeasible, and therefore many non-trivial design alternatives remain unexplored. Also, the issue has been so far regarded mainly from a practical perspective and is still lacking of formal foundations on which the definition of algorithms for assisting the biologists in their design tasks can be based. In this work, we present the first formal study of the problem, and give a formal semantics for a family of Recombinase-based biological devices. We then exhibit a set of semantic properties leading to the definition of representative devices, a notion that allows one to express infinitely large classes of design possibilities in a finite way. Building on this, we then provide a terminating algorithm for generating representative devices for n-input Boolean functions. An open online database of 18M design solutions for 4-inputs devices generated with our method has been released at http://recombinator.lirmm.fr.

Automated testing techniques are often assessed on coverage based metrics. However, despite giving good coverage, the test cases may miss the gap between functional specification and the code implementation. This gap may be subtle in nature, arising due to the absence of logical checks, either in the implementation or in the specification, resulting in inconsistencies in the input definition. The inconsistencies may be prevalent especially for structured inputs, commonly specified using string-based data types. Our study on defects reported over popular libraries reveals that such gaps may not be limited to input validation checks. We propose a test generation technique for structured string inputs where we infer inconsistencies in input definition to expose semantic gaps in the method under test and the method specification. We assess this technique using our tool Segate, Semantic Gap Tester. Segate uses static analysis and automaton modeling to infer the gap and generate test cases. On our benchmark dataset, comprising of defects reported in 15 popular open-source libraries, written in Java, Segate was able to generate tests to expose 80% of the defects.

Software engineers working in industry seldom try to apply formal methods to solve problems. There are various reasons for this. Sometimes these reasons are understandable---the cost of using formal methods does not make economic sense in many contexts. However, formal methods are also often greeted with scepticism. Formal methods are assumed to take too much time, require tools that are too academic, or to be too mathematical to be understood by practice-oriented software engineers. We tested these assumptions by designing a small course around a framework for program verification, aimed at regular computer science students enrolled in a Master's programme. After four lectures and associated exercises, students were given a small verification task where they had to model and verify a real, non-trivial, C function in Why3. A significant majority of students managed to prove a non-trivial functional specification of this C function in the time allotted, and many also pointed out inherent flaws of this function discovered during formalization. Participants reported no major difficulties or mental hurdles in learning Why3, and considered its approach to be appropriate for selected components of safety-critical software. While formal verification tools such as Why3 still have lots of room for improvement, this experience shows that in a short amount of time, software engineers can be taught to use a program verification tool, and obtain usable results without being fully proficient in it. We further recommend that courses on formal methods should also let students explore these as techniques to be applied, instead of only focusing on the theory behind them, as we expect this to gradually lower the barrier to wider acceptance.

Embedded systems (ES) represent the most important elements in modern intelligent systems. An ES is a mix of hardware blocks (HW) and software blocks (SW), executing in collaboration to achieve specific functionalities. Designing a good ES is driven by several factors, related to non-functional requirements. The most influencing factors are the cost of the hardware area and the execution time. The Co-design is one of the most design methodologies, used to optimize those factors while meeting the functional specifications. The Hardware Software Partitioning (HSP) is a major step in this process of Co-design. The HSP decides for each block, whether it is more advantageous to be affected to the hardware part or to the software part. Most of previous works study the optimization of one factor with the respect of a given constraint on the other factor. In this paper, we propose a novel approach aimed to simultaneously optimize the hardware area and the execution time of the system. The approach is inspired from the GO game and based on Minimax algorithm. Experimental results show that the proposed approach leads to more optimal solutions comparing to the Genetic Algorithm (GA).

One of main contributions to the consumption of energy in buildings is the heating, ventilation and air condition (HVAC) system. In fact, it consumes more than half of the energy. Multi-HVAC systems can be seen as an intermediate level of modeling, composed by different HVAC subsystems (e.g. boilers, chillers, heat pumps, among others), that define their operations and enabling the simulation of their behavior at a given time. The main purpose is to develop effective control systems with multi-objective optimization to improve the energy efficiency and the reduction of greenhouse gas (GHG) emissions in the cities. This article proposes the simulation of the behavior and operations of different HVAC subsystems in a particular building making use of physical models. The objective is achieved with different approaches, taking the functional specifications provided by the vendors of the HVAC subsystems.

An understanding of the functional repertoire of neural circuits and their plasticity requires knowledge of neural connectivity diagrams and their dynamical evolution. However, one must additionally take into account the fast and reversible functional effects induced by neuromodulatory mechanisms which do not alter neural circuit diagrams. Neuromodulators contribute crucially to determine the performativity of a neural circuit, that is, its ability to change behavior, and especially behavioral changes occurring under temporal constraints that are incompatible with the longer time scales of Hebbian learning and other forms of neural learning. This paper focuses on two properties of neuromodulatory action that have been relatively neglected so far. These properties are the functional soundness of neuromodulated circuits and the robustness of neuromodulatory action. Both properties are analyzed here as sources of functional specifications for the computational modeling of neural circuit performativity. In particular, taking dynamical systems that are based on CTRNNs (Continuous Time Recurrent Neural Networks) as an exemplary class of computational models, it is argued that robustness is suitably modeled there by means of a hysteresis process, and functional soundness by means of a multiplicity of stable fixed points.

We study the feasibility and performance efficiency of expressing a complex financial numerical algorithm with high-level functional parallel constructs. The algorithm we investigate is a least-square regression-based Monte-Carlo simulation for pricing American options. We propose an accelerated parallel implementation in Futhark, a high-level functional data-parallel language. The Futhark language targets GPUs as the compute platform and we achieve a performance comparable to, and in particular cases up to 2.5X better than, an implementation optimised by NVIDIA CUDA engineers. In absolute terms, we can price a put option with 1 million simulation paths and 100 time steps in 17 ms on a NVIDIA Tesla V100 GPU. Furthermore, the high-level functional specification is much more accessible to the financial-domain experts than the low-level CUDA code, thus promoting code maintainability and facilitating algorithmic changes.

The aim of this paper is to provide a theoretical framework to understand how multicellular systems realize functionally integrated physiological entities by organizing their intercellular space. From a perspective centered on physiology and integration, biological systems are often characterized as organized in such a way that they realize metabolic self-production and self-maintenance. The existence and activity of their components rely on the network they realize and on the continuous management of the exchange of matter and energy with their environment. One of the virtues of the organismic approach focused on organization is that it can provide an understanding of how biological systems are functionally integrated into coherent wholes. Organismic frameworks have been primarily developed by focusing on unicellular life. Multicellularity, however, presents additional challenges to our understanding of biological systems, related to how cells are capable to live together in higher-order entities, in such a way that some of their features and behaviors are constrained and controlled by the system they realize. Whereas most accounts of multicellularity focus on cell differentiation and increase in size as the main elements to understand biological systems at this level of organization, we argue that these factors are insufficient to provide an understanding of how cells are physically and functionally integrated in a coherent system. In this paper, we provide a new theoretical framework to understand multicellularity, capable to overcome these issues. Our thesis is that one of the fundamental theoretical principles to understand multicellularity, which is missing or underdeveloped in current accounts, is the functional organization of the intercellular space. In our view, the capability to be organized in space plays a central role in this context, as it enables (and allows to exploit all the implications of) cell differentiation and increase in size, and even specialized functions such as immunity. We argue that the extracellular matrix plays a crucial active role in this respect, as an evolutionary ancient and specific (non-cellular) control subsystem that contributes as a key actor to the functional specification of the multicellular space and to modulate cell fate and behavior. We also analyze how multicellular systems exert control upon internal movement and communication. Finally, we show how the organization of space is involved in some of the failures of multicellular organization, such as aging and cancer. This publication was funded by the Ministerio de Ciencia, Innovacion y Universidades, Spain ("Ramon y Cajal" Programme RYC-2016-19798 for LB). The authors also acknowledge funding from the Ministerio de Economia y Competitividad (MINECO), Spain (research project FFI2014-52173-P for LB), the Basque Government (Project: IT1228-19 for LB) and the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme - grant agreement no. 637647 - IDEM (for TP; preliminary work for LB).

In this paper we address the design and implementation of custom controller interfaces, bridging the issue of user mapping between action and sound in interactive music systems. A simple framework utilizing functional specifications for musical interfaces and their mappings is presented, in terms of a subset of Scalable Vector Graphics (SVG); interfaces can be described using a simple Haskell based `controller DSL' or equally using a vector drawing application (i.e. Illustrator). We demonstrate the practical use of our system for specifying interfaces as SVGs combined with Faust, a functional DSL for Digital Signal Processing (DSP), in the context of building digital musical instruments. We combine these into a hardware and software audio toolkit, with synthesizers, a sampler, effects, and sequencers. Written in the systems programming language Rust, it demonstrates utilizing the output of our DSLs, providing a type safe and high-level framework for DSP and interface development, with the performance benefits of Rust. Working examples of custom interfaces are described, using ROLI's Lightpad and Sensel's Morph.

International audience; In many agri-food companies, food quality is often managed using expertise gained through experience. Overall quality enhancement may come from sharing collective expertise. In this paper, we describe the design and implementation of a complete methodology allowing an expert knowledge base to be created and used to recommend the technical action to take to maintain food quality. We present its functional specifications, defined in cooperation with several industrial partners and technical centres over the course of several projects carried out in recent years. We propose a systematic methodology for collecting the knowledge on a given food process, from the design of a questionnaire to the synthesis of the information from completed questionnaires using a mind map approach. We then propose an original core ontology for structuring knowledge as possible causal relationships between situations of interest. We describe how mind map files generated by mind map tools are automatically imported into a conceptual graph knowledge base, before being validated and finally automatically processed in a graph-based visual tool. A specific end-user interface has been designed to ensure that end-user experts in agri-food companies can use the tool in a convenient way. Finally, our approach is compared with current research.

Testing of the train control system is a vital factor to ensure the functional and reliability of railway signal system. In the paper, an automated test generation approach based on colored petri net (CPN) and the improved depth first search algorithm, which takes the full path coverage and the full node coverage as criterions, is presented for the train control system. Firstly, CPN model is designed by the functional requirements specification of the Chinese Train Control System Level 3 (CTCS -3) train control system and modeling rules. Secondly, test case suite with least number of repeated paths and least number of test cases is automatically generated by the proposed approach. Finally, the case study of on-board subsystem is employed, which is to show that the proposed approach can deal with complex endless (self-)loops and improve test efficiency.

We investigate the current state of four functional specifications as they relate to EUV photomask blank flatness and the ways in which each functional specification limits, constrains, and controls aspects of image placement and focus error at the wafer following exposure. We explain the relationship between the functional specifications and the ultimate impact they have at wafer, by connecting the key performance indicators (KPIs) to their topographically related features at the mask. Sample mask data sets are then evaluated against the KPIs to demonstrate how such tolerances can open up the process window for certain photomask processing steps, while still achieving the overall lithography process specifications. This exploratory paper aims to offer an interpretation of what these topographic tolerances mean and ultimately help end users understand the potential implications of adopting such functional tolerances. A thorough understanding of such specifications will be necessary as the industry moves forward to future nodes, in order to successfully develop processes which adhere to the upstream tolerances necessary to create mask topographies which enable the mask to meet the high-performance requirements for successful wafer exposures.

Custom mechatronic devices offer personalized functionality, but also come with many non-functional requirements that are unfamiliar to those inexperienced with electronics such as current draw and servo power. The Echidna prototype system enables non-electrical engineers to move from conception to implementation with their mechatronic ideas by generating and searching through a design space that automatically fills in supporting requirements, such as PCB placement and wiring, around their functional specification. The space is modeled as a decision tree whose root is the user's list of lights, motors, sensors, and other functional components that need to be connected, powered, and controlled. Once found, a complete and valid design can be used to synthesize geometry for 3D printing, circuits, and firmware resulting in a set of "plug and fabricate" files for creating their device. We demonstrate how Echidna realizes several designs and discuss how it can be further customized to task-specific applications.

Modern Cyber-Physical Systems (CPSs) need to be able to operate efficiently and reliably within continually changing, uncertain, and unanticipated environments. Namely, these systems should be capable of learning, automatically reconfiguring themselves, and be able to cooperate and collaborate with other CPSs. In a nutshell, exhibit human-like, smart capabilities in an autonomic manner. However, engineering such systems is all but trivial, primarily because we need to develop systems at design-time that are capable of autonomously coping with the uncertainty and change at runtime. Therefore, not only the importance of self-adaptivity as a system's feature increases, but it becomes a fundamental approach for the systems to continue meeting their functional specifications, fulfilling their business objectives while preserving the performance-despite all the runtime changes that the system may encounter. To tackle these challenges, this paper proposes the initial research vision and agenda with the envisioned contributions towards an approach for self-adaptation of cooperative, smart CPSs through shared knowledge and learning.

ABACα is a foundational model for attribute-based access control with a minimal set of capabilities to configure many access control models of interest, including the dominant traditional ones: discretionary (DAC), mandatory (MAC), and role-based (RBAC). A fundamental security problem in the design of ABAC is to ensure safety, that is, to guarantee that a certain subject can never gain certain permissions to access certain object(s). We propose a rule-based specification of ABACα and of its configurations, and the semantic framework of ρLog to turn this specification into executable code for the operational model of ABACα. Next, we identify some important properties of the operational model which allow us to define a rule-based algorithm for the safety problem, and to execute it with ρLog. The outcome is a practical tool to check safety of ABACα configurations. ρLog is a system for rule-based programming with strategies and built-in support for constraint logic programming (CLP). We argue that ρLog is an adequate framework for the specification and verification of safety of ABACα configurations. In particular, the authorization policies of ABACα can be interpreted properly by the CLP component of ρLog, and the operations of its functional specification can be described by five strategies defined by conditional rewrite rules.