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In this paper, we consider the problem of minimising the cost of data transmission as a function of the capacity of telecommunication links. To solve this problem, we first formulated a mathematical model, and then we designed and developed a software that enables the optimisation of the given or randomly generated telecommunications network. Declarative programming is a good choice for optimisation problems because it is enough to specify only the relations that must be satisfied, without giving any effective procedure for finding the values for the decision variables. To test the application, we developed a software that randomly generates a telecommunications network that meets the given requirements. This enables us to test the application on an arbitrary number of different telecommunication networks with different numbers of nodes and links, and analyse the impact of changing network parameters on the flow and results of the optimisation. As telecommunications networks operate in conditions of uncertainty, the subject of special analysis was the potential failure of some of the network links. The paper presents and thoroughly analyses the optimisation results for several selected networks, as well as summary results for a number of telecommunications networks.

The security of Cloud applications is a major concern for application developers and operators. Protecting users' data confidentiality requires methods to avoid leakage from vulnerable software and unreliable Cloud providers. Recently, trusted execution environments (TEEs) emerged in Cloud settings to isolate applications from the privileged access of Cloud providers. Such hardware-based technologies exploit separation kernels, which aim at safely isolating the software components of applications. In this article, we propose a methodology to determine safe partitionings of Cloud applications to be deployed on TEEs. Through a probabilistic cost model, we enable application operators to select the best trade-off partitioning in terms of future re-partitioning costs and the number of domains. To the best of our knowledge, no previous proposal exists addressing such a problem. We exploit information-flow security techniques to protect the data confidentiality of applications by relying on declarative methods to model applications and their data flow. The proposed solution is assessed by executing a proof-of-concept implementation that shows the relationship among the future partitioning costs, number of domains and execution times. [ABSTRACT FROM AUTHOR]

The decision-making related to the placement of applications made from orchestrated serverless functions onto Cloud-Edge infrastructures is a challenging problem as it must consider functional and non-functional requirements. In this article, we propose a novel declarative methodology to determine the placement of FaaS orchestration onto Cloud-Edge resources while satisfying all the requirements of the FaaS orchestrations and relying on information-flow analyses and padding techniques to prevent information leaks through side channels. A motivating example from Augmented Reality is used to showcase the open-source declarative prototype implementing our proposal. Besides, the prototype is assessed via simulation to evaluate execution times, placement success rates and energy consumption. [ABSTRACT FROM AUTHOR]

Intensional sets are sets given by a property rather than by enumerating their elements. In a previous work, we have proposed a decision procedure for a first-order logic language which provides restricted intensional sets (RISs), i.e. a sub-class of intensional sets that are guaranteed to denote finite—though unbounded—sets. In this paper, we show how RIS can be exploited as a convenient programming tool also in a conventional setting, namely the imperative O-O language Java. We do this by considering a Java library, called JSetL, that integrates the notions of logical variable, (set) unification and constraints that are typical of constraint logic programming languages into the Java language. We show how JSetL is naturally extended to accommodate for RIS and RIS constraints and how this extension can be exploited; on the one hand, to support a more declarative style of programming and, on the other hand, to effectively enhance the expressive power of the constraint language provided by the library. [ABSTRACT FROM AUTHOR]

Application of Vehicular Ad Hoc Networks (VANETs) aims to help in the solution of some problems that have arisen in road transportation systems via short-range, low-latency mobile communication. The application of V2X (Vehicle-to-Everything) communication technologies to the next generation of Advanced Driver Assistance Systems (ADAS) is essential to the extension of the operational design domain (ODD) of the systems to provide safe, secure, and efficient automated driving solutions. Due to the safety-critical nature of the problem, the large-scale testing of V2X enabled ADAS solutions to evaluate and measure the anticipated quality and functionality of the experimental system is of great significance. This article proposes a novel ADAS application prototyping framework, using declarative programming, built on top of the popular Artery/OMNeT++ simulator. The framework is capable of simulating V2X-enabled ADAS applications using accurate network simulation and realistic simulated traffic on real-world maps. The solution features XML descriptions for application specification. The sensor model of Artery is used to provide information to applications. By using the simulator, one can conclude the performance of the applications and discover locations, circumstances and design patterns, where design limits should apply. [ABSTRACT FROM AUTHOR]

Osmotic computing encompasses emerging Cloud‐Internet of Things (IoT) computing paradigms, by featuring the possibility for application services to adapt into different functionally equivalent flavours, depending on the contextually available resources and on specific requirements of running applications. This article proposes a fully decentralised declarative framework that enables both application and infrastructure operators to declare management policies for the service instances and the nodes they manage, respectively. Policies are composed of a simple and well‐defined set of management operations, declared in Prolog, which trigger based on locally available contextual information on application requests and infrastructure resources. A prototype implementation of the framework is showcased and assessed via simulation over a lifelike Smart Campus use case with multiple applications, at increasing infrastructure sizes and number of mobile users. Experimental results show that the proposed management framework scales to large infrastructure sizes and suits the needs of multiflavoured Osmotic applications in dynamic deployment conditions, by improving the trade‐off between their response times and suitable service usage. [ABSTRACT FROM AUTHOR]

Search is one of the more common strategies used by problem-solving agents. For many hard problems, a backtracking search can be the most effective approach for finding a solution. Logic programming languages provide, as a core feature of the language, the mechanics for the search behind the scenes without requiring the user to specify the algorithm. However, this functionality has been generally left out of the core features of imperative programming languages. In this work, we propose integrating a search agent into an imperative programming language through a search construct in the syntax. By doing so, our intention is that the user may apply a declarative approach to problem solving. We extend the Go programming language with this search construct and develop an agent to perform the search. The algorithm behind the search is implicitly handled by the agent. We demonstrate the effectiveness of this search construct through solutions to an exhaustive search over a file-system, the NQueens problem, and the monkey and the bananas problem. To evaluate the performance of our agent, we compare its runtime performance against two of the common Prolog implementations, SWI-Prolog and GNU Prolog. [ABSTRACT FROM AUTHOR]

The security of Cloud applications is a major concern for application developers and operators. Protecting users’ data confidentiality requires methods to avoid leakage from vulnerable software and unreliable Cloud providers. Recently, trusted execution environments (TEEs) emerged in Cloud settings to isolate applications from the privileged access of Cloud providers. Such hardware-based technologies exploit separation kernels, which aim at safely isolating the software components of applications. In this article, we propose a methodology to determine safe partitionings of Cloud applications to be deployed on TEEs. Through a probabilistic cost model, we enable application operators to select the best trade-off partitioning in terms of future re-partitioning costs and the number of domains. To the best of our knowledge, no previous proposal exists addressing such a problem. We exploit information-flow security techniques to protect the data confidentiality of applications by relying on declarative methods to model applications and their data flow. The proposed solution is assessed by executing a proof-of-concept implementation that shows the relationship among the future partitioning costs, number of domains and execution times.

Application of Vehicular Ad Hoc Networks (VANETs) aims to help in the solution of some problems that have arisen in road transportation systems via short-range, low-latency mobile communication. The application of V2X (Vehicle-to-Everything) communication technologies to the next generation of Advanced Driver Assistance Systems (ADAS) is essential to the extension of the operational design domain (ODD) of the systems to provide safe, secure, and efficient automated driving solutions. Due to the safety-critical nature of the problem, the large-scale testing of V2X enabled ADAS solutions to evaluate and measure the anticipated quality and functionality of the experimental system is of great significance. This article proposes a novel ADAS application prototyping framework, using declarative programming, built on top of the popular Artery/OMNeT++ simulator. The framework is capable of simulating V2X-enabled ADAS applications using accurate network simulation and realistic simulated traffic on real-world maps. The solution features XML descriptions for application specification. The sensor model of Artery is used to provide information to applications. By using the simulator, one can conclude the performance of the applications and discover locations, circumstances and design patterns, where design limits should apply.

Thom Frühwirth presented a short, elegant, and efficient Prolog program for the n queens problem. However, the program may be seen as rather tricky and one may not be convinced about its correctness. This paper explains the program in a declarative way and provides proofs of its correctness and completeness. The specification and the proofs are declarative, that is they abstract from any operational semantics. The specification is approximate, it is unnecessary to describe the program's semantics exactly. Despite the program works on non-ground terms, this work employs the standard semantics, based on logical consequence and Herbrand interpretations. Another purpose of the paper is to present an example of precise declarative reasoning about the semantics of a logic program. [ABSTRACT FROM AUTHOR]

Data-driven approaches are becoming increasingly common as problem-solving tools in many areas of science and technology. In most cases, machine learning models are the key component of these solutions. Often, a solution involves multiple learning models, along with significant levels of reasoning with the models' output and input. However, the current tools are cumbersome not only for domain experts who are not fluent in machine learning but also for machine learning experts who evaluate new algorithms and models on real-world data and develop AI systems. We review key efforts made by various AI communities in providing languages for high-level abstractions over learning and reasoning techniques needed for designing complex AI systems. We classify the existing frameworks based on the type of techniques and their data and knowledge representations, compare the ways the current tools address the challenges of programming real-world applications and highlight some shortcomings and future directions. Our comparison is only qualitative and not experimental since the performance of the systems is not a factor in our study.

Orchestrating next-gen applications over heterogeneous resources along the Cloud-IoT continuum calls for new strategies and tools to enable scalable and application-specific managements. Inspired by the self-organisation capabilities of bacteria colonies, we propose a declarative, fully decentralised application management solution, targeting pervasive opportunistic Cloud-IoT infrastructures. We present a customisable declarative implementation of the approach and validate its scalability through simulation over motivating scenarios, also considering end-user’s mobility and the possibility to enforce application-specific management policies for different (classes of) applications. [ABSTRACT FROM AUTHOR]

Technological progress in Answer Set Programming (ASP) has been stimulated by the use of common standards, such as the ASP-Core-2 language. While ASP has its roots in nonmonotonic reasoning, efforts have also been made to reconcile ASP with classical first-order (FO) logic. This has resulted in the development of FO(·), an expressive extension of FO, which allows ASP-like problem solving in a purely classical setting. This language may be more accessible to domain experts already familiar with FO and may be easier to combine with other formalisms that are based on classical logic. It is supported by the IDP inference system, which has successfully competed in a number of ASP competitions. Here, however, technological progress has been hampered by the limited number of systems that are available for FO(·). In this paper, we aim to address this gap by means of a translation tool that transforms an FO(·) specification into ASP-Core-2, thereby allowing ASP-Core-2 solvers to be used as solvers for FO(·) as well. We present experimental results to show that the resulting combination of our translation with an off-the-shelf ASP solver is competitive with the IDP system as a way of solving problems formulated in FO(·). [ABSTRACT FROM AUTHOR]

We describe a novel approach for experimental High-Energy Physics (HEP) data analyses that is centred around the declarative rather than imperative paradigm when describing analysis computational tasks. The analysis process can be structured in the form of a Directed Acyclic Graph (DAG), where each graph vertex represents a unit of computation with its inputs and outputs, and the graph edges describe the interconnection of various computational steps. We have developed REANA, a platform for reproducible data analyses, that supports several such DAG workflow specifications. The REANA platform parses the analysis workflow and dispatches its computational steps to various supported computing backends (Kubernetes, HTCondor, Slurm). The focus on declarative rather than imperative programming enables researchers to concentrate on the problem domain at hand without having to think about implementation details such as scalable job orchestration. The declarative programming approach is further exemplified by a multi-level job cascading paradigm that was implemented in the Yadage workflow specification language. We present two recent LHC particle physics analyses, ATLAS searches for dark matter and CMS jet energy correction pipelines, where the declarative approach was successfully applied. We argue that the declarative approach to data analyses, combined with recent advancements in container technology, facilitates the portability of computational data analyses to various compute backends, enhancing the reproducibility and the knowledge preservation behind particle physics data analyses.

The area of declarative data analytics explores the application of the declarative paradigm on data science and machine learning. It proposes declarative languages for expressing data analysis tasks and develops systems which optimize programs written in those languages. The execution engine can be either centralized or distributed, as the declarative paradigm advocates independence from particular physical implementations. The survey explores a wide range of declarative data analysis frameworks by examining both the programming model and the optimization techniques used, in order to provide conclusions on the current state of the art in the area and identify open challenges. [ABSTRACT FROM AUTHOR]

Distributed systems are hard to get right, model, test, debug, and teach. Their textbook definitions, typically given in a form of replicated state machines, are concise, yet prone to introducing programming errors if naïvely translated into runnable implementations. In this work, we present Distributed Protocol Combinators (DPC), a declarative programming framework that aims to bridge the gap between specifications and runnable implementations of distributed systems, and facilitate their modeling, testing, and execution. DPC builds on the ideas from the state-of-the art logics for compositional systems verification. The contribution of DPC is a novel family of program-level primitives, which facilitates construction of larger distributed systems from smaller components, streamlining the usage of the most common asynchronous message-passing communication patterns, and providing machinery for testing and user-friendly dynamic verification of systems. This paper describes the main ideas behind the design of the framework and presents its implementation in Haskell. We introduce DPC through a series of characteristic examples and showcase it on a number of distributed protocols from the literature. This paper extends our preceeding conference publication (Andersen & Sergey, 2019a) with an exploration of randomized testing for protocols and their implementations, and an additional case study demonstrating bounded model checking of protocols. [ABSTRACT FROM AUTHOR]

Spreadsheets are commonly declarative, first-order functional programs and are used as organizational tools, for end-user development and for educational purposes. Spreadsheet end users are usually domain experts who use spreadsheets as their main computational model, but are seldom trained IT professionals who can leverage today's abundant multicore processors for spreadsheet computation. In this paper, we present an algorithm for automatic, parallel evaluation of spreadsheets targeting shared-memory multicore architectures, which lets end users transparently make use of their multicore processors. We evaluate our algorithm on a set of synthetic and real-world spreadsheets and obtain up to 16 times speedup on 48 cores. [ABSTRACT FROM AUTHOR]

Static type systems are usually not sufficient to express all requirements on function calls. Hence, contracts with pre- and postconditions can be used to express more complex constraints on operations. Contracts can be checked at run time to ensure that operations are only invoked with reasonable arguments and return intended results. Although such dynamic contract checking provides more reliable program execution, it requires execution time and could lead to program crashes that might be detected with more advanced methods at compile time. To improve this situation for declarative languages, we present an approach to combine static and dynamic contract checking for the functional logic language Curry. Based on a formal model of contract checking for functional logic programming, we propose an automatic method to verify contracts at compile time. If a contract is successfully verified, it can be omitted from dynamic checking. This method decreases execution time without degrading reliable program execution. In the best case, when all contracts are statically verified, it provides trust in the software since crashes due to contract violations cannot occur during program execution. [ABSTRACT FROM AUTHOR]

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