Declarative Approach Research Articles

A declarative enhancement of JavaScript programs by leveraging the Java metadata infrastructure

Web browsers have evolved into indispensable software platforms for modern applications. Although JavaScript has become a de-facto lingua franca for developing web applications, the JavaScript software development tools and methodologies lag behind those of languages such as Java and C#. In particular, to enhance JavaScript programs with non-functional concerns (e.g., persistence, security, transactions, and logging) JavaScript developers need to modify the source code by hand. Developers then often end up having to maintain the resulting modified version separately for reasons that include poor design, the complexities of program evolution, and fundamental language limitations. The necessity to modify code by hand could be avoided if JavaScript had metadata facilities for developers to specify non-functional concerns declaratively. To address this problem, we present a novel declarative approach, T ransparent A utomated E nhancement for J ava S cript (TAE-JS) that enhances JavaScript programs with the ability to use declarative metadata. The metadata is expressed by means of Java annotations. We have implemented our technique in an open-source plug-in for the Eclipse IDE. This plug-in allows a developer to enhance the original version of a JavaScript program by specifying concerns declaratively using Java annotations. It then analyzes an original version of the program to automatically generate enhanced program versions by adding the declared concerns. We evaluated TAE-JS with four practical examples that enhance JavaScript programs by declaratively adding concerns such as persistence, security, transactions, and logging. In a user study with ten student developers and three professional engineers at PayPal, the participants viewed favorably TAE-JS's flexible declarative enhancement capabilities, seeing them as a valuable mechanism for implementing non-functional concerns in JavaScript programs. Our evaluation results are promising in demonstrating the potential benefits of our approach to complement existing JavaScript development tools.

Governance and control in distributed ledgers: Understanding the challenges facing blockchain technology in financial services

As blockchain platforms are becoming increasingly noticeable in financial services and beyond, questions arise regarding their suitability to compete with or replace existing payment systems and marketplaces and redesign the financial infrastructures of the future. Prominent among these concerns are issues around governance and control in distributed ledgers: How are distributed ledger technologies governed? Can blockchains address complex administration problems? What key issues of note for practitioners and academics have emerged thus far? In this paper we aim to review the existing governance practices of established or popular blockchain and decentralized autonomous organization (DAO) systems with a view to understanding how they hold up in times of crises. What questions are raised when they are compromised or faced consensus challenges in coordinating action especially around control and accountability? We use a translational process, generating focal insights about present concerns from the reference point of completed academic studies and extensive practitioner consultation. Rather than adopting a declarative approach attempting to provide all the answers, we draw insights from the IT platform governance literature to offer a critical perspective for asking the right questions around key governance issues in financial infrastructure such as decision rights, control mechanisms, and incentives.

Fuzzy lattice operations on first-order terms over signatures with similar constructors: A constraint-based approach

Unification and generalization are operations on two terms computing respectively their greatest lower bound and least upper bound when the terms are quasi-ordered by subsumption up to variable renaming (i.e., t1⪯t2 iff t1=t2σ for some variable substitution σ). When term signatures are such that distinct functor symbols may be related with a fuzzy equivalence (called a similarity), these operations can be formally extended to tolerate mismatches on functor names and/or arity or argument order. We reformulate and extend previous work with a declarative approach defining unification and generalization as sets of axioms and rules forming a complete constraint-normalization proof system. These include the Reynolds-Plotkin term-generalization procedures, Maria Sessa's “weak” unification with partially fuzzy signatures and its corresponding generalization, as well as novel extensions of such operations to signatures with weaker functor similarities (i.e., with possibly different arities). One advantage of this approach is that it requires no modification of the conventional data structures for terms and substitutions. This and the fact that these declarative specifications are efficiently executable conditional Horn-clauses offers great practical potential for fuzzy information-handling applications.

Knowledge representation analysis of graph mining

This paper analyses the graph mining problem, and the frequent pattern mining task associated with it. In general, frequent pattern mining looks for a graph which occurs frequently within a network or, in the transactional setting, within a dataset of graphs. We discuss this task in the transactional setting, which is a problem of interest in many fields such as bioinformatics, chemoinformatics and social networks. We look at the graph mining problem from a Knowledge Representation point of view, hoping to learn something about support for higher-order logics in declarative languages and solvers. Graph mining is studied as a prototypical problem; it is easily expressible mathematically and exists in many variations. As such, it appears to be a prime candidate for a declarative approach; one would expect this allows for a clear, structured, statement of the problem combined with easy adaptation to changing requirements and variations. Current state-of-the-art KR languages such as IDP and ASP aspire to be practical solvers for such problems (Bruynooghe, Theory Practice Logic Program. (TPLP) 15(6), 783–817 2015). Nevertheless, expressing the graph mining problem in these languages requires unexpectedly complicated and unintuitive encoding techniques. These techniques are in contrast to the ease with which one can transform the mathematical definition of graph mining to a higher-order logic specification, and distract from the problem essentials, complicating possible future adaptation. In this paper, we argue that efforts should be made towards supporting higher-order logic specifications in modern specification languages, without unintuitive and complicated encoding techniques. We argue that this not only makes representation clearer and more susceptible to future adaptation, but might also allow for faster, more competitive solver techniques to be implemented.

Scalable computation of high-order optimization queries

Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. We present a complete system that supports package queries , a new query model that extends traditional database queries to handle complex constraints and preferences over answer sets, allowing the declarative specification and efficient evaluation of a significant class of constrained optimization problems---integer linear programs (ILP)---within a database.

Replication of the Question-Based Spatial Computing Approach – Experiences and Suggestions for Further Developments

Geographic Information Systems (GIS) have developed into complex toolboxes and require analysts to formulate spatial questions according to the requirements of the data formats and tools provided by their specific GIS-application. The recently proposed language for spatial computing aims to provide a question-based and thus more comprehensible approach for spatial analyses that especially supports scientists and experts from other disciplines to conduct spatial analyses in their fields. In this contribution, we apply the question-based spatial computing approach to a case study in the humanitarian field and compare the resulting script to one written using a conventional GIS tool. The comparison of the two versions of the script is based on six criteria covering qualitative and quantitative aspects of the analysis. We also discuss the implementation concept behind the new language. Our results show that the new approach requires fewer computational steps than the conventional script. In addition, the declarative approach allows users to focus on the content of the spatial question, and the query-like character of the language makes it easier to understand for non-GIS specialists. In addition, we share observations on challenges of the further development of the language as an outcome of this study.

Declarative Construction of Distributed Event-driven IoT Services Based on IoT Resource Models

In Internet of Things (IoT)scenarios, the coordination of physical systems is often complex and rigid. Work to date has not comprehensively explored how to flexibly construct distributed IoT services to satisfy the coordination requirement. In our work, we propose a declarative approach to construct an event-driven IoT service system, where physical devices and systems are explicitly modeled as a service architecture foundation, the service behavior is flexibly declared based on distributed events, and it is step-by-step refined to have rigid service properties while allowing runtime adaptation. As an example, the controllability property of physical systems is discussed. Finally, we establish a distributed event-driven IoT service platform to test our method. Some experiments are performed to concept-prove our work.

DIFF

A range of explanation engines assist data analysts by performing feature selection over increasingly high-volume and high-dimensional data, grouping and highlighting commonalities among data points. While useful in diverse tasks such as user behavior analytics, operational event processing, and root cause analysis, today's explanation engines are designed as standalone data processing tools that do not interoperate with traditional, SQL-based analytics workflows; this limits the applicability and extensibility of these engines. In response, we propose the DIFF operator, a relational aggregation operator that unifies the core functionality of these engines with declarative relational query processing. We implement both single-node and distributed versions of the DIFF operator in MB SQL, an extension of MacroBase, and demonstrate how DIFF can provide the same semantics as existing explanation engines while capturing a broad set of production use cases in industry, including at Microsoft and Facebook. Additionally, we illustrate how this declarative approach to data explanation enables new logical and physical query optimizations. We evaluate these optimizations on several real-world production applications, and find that DIFF in MB SQL can outperform state-of-the-art engines by up to an order of magnitude.

A Hybrid Approach for Spatio-Temporal Validation of Declarative Multimedia Documents

Declarative multimedia documents represent the description of multimedia applications in terms of media items and relationships among them. Relationships specify how media items are dynamically arranged in time and space during runtime. Although a declarative approach usually facilitates the authoring task, authors can still make mistakes due to incorrect use of language constructs or inconsistent or missing relationships in a document. In order to properly support multimedia application authoring, it is important to provide tools with validation capabilities. Document validation can indicate possible inconsistencies in a given document to an author so that it can be revised before deployment. Although very useful, multimedia validation tools are not often provided by authoring tools. This work proposes a multimedia validation approach that relies on a formal model called Simple Hypermedia Model ( SHM ). SHM is used for representing a document for the purpose of validation. An SHM document is validated using a hybrid approach based on two complementary techniques. The first one captures the document’s spatio-temporal layout in terms of its state throughout its execution by means of a rewrite theory, and validation is performed through model-checking . The second one captures the document’s layout in terms of intervals and event occurrences by means of Satisfiability Modulo Theories (SMT) formulas, and validation is performed through SMT solving. Due to different characteristics of both approaches, each validation technique complements the other in terms of expressiveness of SHM and tests to be checked. We briefly present validation tools that use our approach. They were evaluated with real NCL documents and by usability tests.

Variability in business processes: Automatically obtaining a generic specification

The existence of different process variants is inevitable in many modern organizations. However, variability in business process support has proven to be a challenge as it requires a flexible business process specification that supports the required process variants, while at the same time being compliant with policies and regulations. Declarative approaches could support variability, by providing rules constraining process behavior and thereby allowing different variants. However, manual specification of these rules is complicated and error-prone. As such, tools are required to ensure that duplication and overlap of rules is avoided as much as possible, while retaining maintainability. In this paper, we present an approach to represent different process variants in a single compound prime event structure, and provide a method to subsequently derive variability rules from this compound prime event structure. The approach is evaluated by conducting an exploratory evaluation on different sets of real-life business process variants, including a real-life case from the Dutch eGovernment, to demonstrate the effectiveness and applicability of the approach.

Human-Centric Automation and Optimization for Smart Homes

A smart home needs to be human-centric, where it tries to fulfill human needs given the devices it has. Various works are developed to provide homes with reasoning and planning capability to fulfill goals, but most do not support complex sequence of plans or require significant manual effort in devising subplans. This is further aggravated by the need to optimize conflicting personal goals. A solution is to solve the planning problem represented as constraint satisfaction problem (CSP). But CSP uses hard constraints and, thus, cannot handle optimization and partial goal fulfillment efficiently. This paper aims to extend this approach to weighted CSP. Knowledge representation to help in generating planning rules is also proposed, as well as methods to improve performances. Case studies show that the system can provide intelligent and complex plans from activities generated from semantic annotations of the devices, as well as optimization to maximize personal constraints’ fulfillment. Note to Practitioners —Smart home should maximize the fulfillment of personal goals that are often conflicting. For example, it should try to fulfill as much as possible the requests made by both the mother and daughter who wants to watch TV but both having different channel preferences. That said, every person has a set of goals or constraints that they hope the smart home can fulfill. Therefore, human-centric system that automates the loosely coupled devices of the smart home to optimize the goals or constraints of individuals in the home is developed. Automated planning is done using converted services extracted from devices, where conversion is done using existing tools and concepts from Web technologies. Weighted constraint satisfaction that provides the declarative approach to cover large problem domain to realize the automated planner with optimization capability is proposed. Details to speed up planning through search space reduction are also given. Real-time case studies are run in a prototype smart home to demonstrate its applicability and intelligence, where every planning is performed under a maximum of 10 s. The vision of this paper is to be able to implement such system in a community, where devices everywhere can cooperate to ensure the well-being of the community.

Routing Driverless Transport Vehicles in Car Assembly with Answer Set Programming

AbstractAutomated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such ad-hoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.

Answer set programming unleashed!

Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)].

Constrained distance based clustering for time-series: a comparative and experimental study

Constrained clustering is becoming an increasingly popular approach in data mining. It offers a balance between the complexity of producing a formal definition of thematic classes-required by supervised methods-and unsupervised approaches, which ignore expert knowledge and intuition. Nevertheless, the application of constrained clustering to time-series analysis is relatively unknown. This is partly due to the unsuitability of the Euclidean distance metric, which is typically used in data mining, to time-series data. This article addresses this divide by presenting an exhaustive review of constrained clustering algorithms and by modifying publicly available implementations to use a more appropriate distance measure-dynamic time warping. It presents a comparative study, in which their performance is evaluated when applied to time-series. It is found that k-Means based algorithms become computationally expensive and unstable under these modifications. Spectral approaches are easily applied and offer state-of-the-art performance, whereas declarative approaches are also easily applied and guarantee constraint satisfaction. An analysis of the results raises several influencing factors to an algorithm's performance when constraints are introduced.

Declarative Web services composition using proofs

Over the last decade, Web services composition has become a thriving area of research and development endeavors for application integration and interoperability. Although Web services composition has been heavily investigated, several issues still need to be addressed. In this paper, we mainly discuss two major bottlenecks in the current process of modeling compositions. The first bottleneck is related to the level of expertise required to achieve a composition process. Typical procedural style of modeling, inspired by workflow/business process paradigm, do not provide the required abstractions. Therefore, they fail to support dynamic and self-managed compositions able to adapt to unpredictable changes. The second bottleneck in current service compositions concerns their life cycle and their management, also called their governance. In this context, we propose a declarative proof-based approach to Web service composition. Based on the three stages of pre-composition, abstraction, and composition, our solution provides an easy way to specify functional and non-functional requirements of composite services in a precise and declarative manner. It guides the user through the composition process while allowing detection and recovery of violations at both design and run-time using proofs and planning. Experiment results clearly show the added value of the proof-based solution as a viable strategy to improve the composition process.

A fuzzy ontology-based approach for tool-supported decision making in architectural design

In software development, non-functional requirements (NFRs) play a crucial role in decision-making procedures for architectural solutions. A strong relation exists between NFRs and design patterns, a powerful method to support the architectural design of software systems, but due to their complexity and abstraction, NFRs are rarely taken into account in software design. In fact, the knowledge on NFRs is usually owned by designers and not formalized in a structured way. We propose to structure the knowledge associated with NFRs via a Fuzzy Ontology, which we show is able to model their mutual relations and interactions. The declarative approach makes possible to represent and maintain the above-mentioned knowledge by keeping the flexibility and fuzziness of modeling thanks to the use of fuzzy concepts such as high, low, fair. We present a decision support system based on (i) a fuzzy OWL 2 ontology that encodes 109 design patterns, 28 pattern families and 37 NFRs and their mutual relations, (ii) a novel reasoning service to retrieve a ranked list of pattern sets able to satisfy the non-functional requirements within a system specification.

A Templating System to Generate Provenance

prov-template is a declarative approach that enables designers and programmers to design and generate provenance compatible with the prov standard of the World Wide Web Consortium. Designers specify the topology of the provenance to be generated by composing templates, which are provenance graphs containing variables, acting as placeholders for values. Programmers write programs that log values and package them up in sets of bindings, a data structure associating variables and values. An expansion algorithm generates instantiated provenance from templates and sets of bindings in any of the serialisation formats supported by prov . A quantitative evaluation shows that sets of bindings have a size that is typically 40 percent of that of expanded provenance templates and that the expansion algorithm is suitably tractable, operating in fractions of milliseconds for the type of templates surveyed in the article. Furthermore, the approach shows four significant software engineering benefits: separation of responsibilities, provenance maintenance, potential runtime checks and static analysis, and provenance consumption. The article gathers quantitative data and qualitative benefits descriptions from four different applications making use of prov-template . The system is implemented and released in the open-source library ProvToolbox for provenance processing.

A constraint-driven approach to food supply chain management

PurposeThe purpose of this paper is the need to build a novel approach that would allow flexible modeling and solving of food supply chain management (FSCM) problems. The models developed would use the data (data-driven modeling) as early as possible at the modeling phase, which would lead to a better and more realistic representation of the problems being modeled.Design/methodology/approachAn essential feature of the presented approach is its declarativeness. The use of a declarative approach that additionally includes constraint satisfaction problems and provides an opportunity of fast and easy modeling of constrains different in type and character. Implementation of the proposed approach was performed with the use of an original hybrid method in which constraint logic programming (CLP) and mathematical programming (MP) are integrated and transformation of a model is used as a presolving technique.FindingsThe proposed constraint-driven approach has proved to be extremely flexible and efficient. The findings obtained during part of experiments dedicated to efficiency were very interesting. The use of the constraint-driven approach has enabled finding a solution depending on the instance data up to 1,000 times faster than using the MP.Research limitations/implicationsDue to the limited use of exact methods for NP-hard problems, the future study should be to integrate the CLP with environments other than the MP. It is also possible, e.g., with metaheuristics like genetic algorithms, ant colony optimization, etc.Practical implicationsThere is a possibility of using the approach as a basis to build a decision support system for FSCM, simple integration with databases, enterprise resource planning systems, management information systems, etc.Originality/valueThe new constraint-driven approach to FSCM has been proposed. The proposed approach is an extension of the hybrid approach. Also, a new decision-making model of distribution and logistics for the food supply chain is built. A presolving technique for this model has been presented.

Declarative Approach Design Technique: Requirements Analysis

Рассматриваются актуальные проблемы современных методов проектирования программного обеспечения. Основными недостатками современных методов проектирования программного обеспечения являются несоответствие быстро меняющимся требованиям в условиях стремительно развивающейся индустрии информационных технологий, сложность сопровождения и поддержки программного обеспечения из-за преобладания императивной составляющей и слабой степени документированности. Дана характеристика предметно ориентированного метода проектирования (Domain Driven Design), определены преимущества и недостатки рассматриваемого метода. Сделан вывод о необходимости создания новой методики, учитывающей особенности и требования современных процессов проектирования. Предложена методика декларативного процесса проектирования, рассматривающая процесс проектирования в виде последовательных этапов: определение требований к системе, анализ, проектирование и разработка. Данная методика основана на формальных правилах декларативного перехода между различными состояниями процесса проектирования. Рассмотрены этапы определения требований к системе и анализа с использованием предлагаемой методики на примере проектирования системы проведения онлайн-соревнований по спортивному программированию BACS. На этапе формулирования требований к системе был определен словарь предметной области. Результатом этапа анализа является модель предметной области, формальное определение внешних характеристик процессов и зависимости процессов друг от друга, представленной в виде диаграммы вариантов использования. Полученные описания и диаграммы являются входными данными для следующего этапа «Проектирование».

Declarative Dependency Specification for Inter-connected Large-scale Cyber-physical Systems

Cyber-Physical Systems (CPS) are inter-connected software-hardware artefacts ranging from small-scale bio-electrical implants, medium-scale smart cars and intelligent production lines, to large-scale critical infrastructures with power grids, telecommunication networks and railway systems. Large-scale CPS plays a central role in modern society by delivering essential services for human daily life. Depending on the delivered services, any disruption or mal-function of these systems with a duration of hours or days will have severe societal and economic impacts and consequences, in particularly when the inter-dependencies between these systems are considered: the total consequences resulted by cascading effects is usually much larger than the one caused by the original failure. Federated simulation provides an effective means to analyse the overall dynamics of inter-connected large-scale CPS. In a typical federated simulation environment, dedicated domain-specific simulators, both commercial and open-source, are applied and inter-connected together to provide realistic system behaviours of the complete CPS networks. Specifying the dependencies among different simulator models is however a challenging task, especially for networks involving multiple large-scale CPS. In this paper, a declarative approach for dependency specification based on data stream processing is proposed. Preliminary results show the benefits comparing to the traditionally imperative approaches in terms of flexibility, scalability and usability.