Declarative Approach Research Articles

A declarative approach and benchmark tool for controlled evaluation of microservice resiliency patterns

A declarative approach and benchmark tool for controlled evaluation of microservice resiliency patterns

From Single-Objective to Bi-Objective Maximum Satisfiability Solving

The declarative approach is key to efficiently finding optimal solutions to various types of NP-hard real-world combinatorial optimization problems. Most work on practical declarative solvers—ranging from classical integer programming to finite-domain constraint optimization and maximum satisfiability (MaxSAT)—has focused on optimization under a single objective; fewer advances have been made towards efficient declarative techniques for multi-objective optimization problems. Motivated by significant recent advances in practical solvers for MaxSAT, in this work we develop BiOptSat, an exact declarative approach for finding Pareto-optimal solutions to bi-objective optimization problems, with propositional logic as the underlying constraint language. BiOptSat can be viewed as an instantiation of the lexicographic method. The approach makes use of a single Boolean satisfiability solver that is incrementally employed throughout the entire search procedure, allowing for finding a single Pareto-optimal solution, finding one representative solution for each non-dominated point, and enumerating all Pareto-optimal solutions. We detail several algorithmic instantiations of BiOptSat, each building on recent algorithms proposed for single-objective MaxSAT. We empirically evaluate the instantiations compared to recently-proposed alternative approaches to multi-objective MaxSAT solving on several real-world domains from the literature, showing the practical benefits of our approach.

Choreographing the disabled spectator: Disrupting audience expectations in Dancer and rampa landscape

Representation of ‘differing bodyminds’ in dance has expanded how dancing bodies are imagined. Examining two performances in Helsinki, Finland, Dancer and rampa landscape: lazy, late, absent through collaborative autoethnography we consider in what ways these works might choreograph for disabled spectators. We argue that choreography addressing disability and neurodivergence that does not consider the diverse access needs of spectators, risks creating hermeneutical injustice. This occurs when individuals experience harm due to their inability to understand or articulate their own experiences. Hermeneutical injustice is characterized by inequitable access to disability knowledge and a declarative approach to access where performances, venues and artists claim to be accessible for spectators without attention to what is necessary for access. Through this process, spectators without access needs have more access to the choreographic knowledge of disability. We alternate our experiences of these performances with reflections on spectator access and draw on framing materials to provide context. We focus on how the performance choreographs for disabled spectators – relating our own embodied experiences and observations as audience members. Ultimately, cripping choreography cannot just involve onstage representation; it must consider and welcome the disabled spectator.

Collection skeletons: Declarative abstractions for data collections

Modern programming languages provide programmers with rich abstractions for data collections as part of their standard libraries, e.g., Containers in the C++ STL, the Java Collections Framework, or the Scala Collections API. Typically, these collections frameworks are organised as hierarchies that provide programmers with common abstract data types (ADTs) like lists, queues, and stacks. While convenient, this approach introduces problems which ultimately affect application performance due to users over-specifying collection data types limiting implementation flexibility. In this article, we develop Collection Skeletons which provide a novel, declarative approach to data collections. Using our framework, programmers explicitly select properties for their collections, thereby truly decoupling specification from implementation. By making collection properties explicit, immediate benefits materialise in forms of reduced risk of over-specification and increased implementation flexibility. We have prototyped our declarative abstractions for collections as a C++ library, and demonstrate that benchmark applications rewritten to use Collection Skeletons incur little or no overhead. We also show how Collection Skeletons help shielding the application developer from parallel implementation details, either by encapsulating implicit parallelism or through explicit properties that capture the requirements of parallel algorithmic skeletons. We observe performance improvements across most of the 17 benchmarks resulting from the use of Collection Skeletons before trying to parallelise those benchmarks, while also enhancing performance portability across three different hardware platforms.

A declarative approach to detecting design patterns from Java execution traces and source code

Design patterns are invaluable for software engineers because they help obtain well-structured and reusable object-oriented software components and contribute towards ease of software comprehension, maintenance, and modification. However, identifying design patterns from an inspection of the source code is not easy because, in most cases, there are no syntactic cues that signal their presence. This topic has therefore elicited considerable interest in the field. The novel aspect of our work is that we propose a set of primitives using which we can declaratively specify design patterns based on a combination of static and dynamic information. Our experimental work is carried out in the context of Java: static information is extracted from Java source code, and dynamic information from an execution trace of a program. Each declarative pattern specification is automatically translated into an SQL query which retrieves all instances of the design pattern present in the program. We illustrate our approach with the well-known Gang-of-Four design patterns and the approach extends to other such design patterns. The experimental results show the efficacy of our approach for representative programs for all GoF patterns in addition to more extensive case studies, JHotDraw, Junit, and QuickUML.

Contamination and suitability of soils for growing bio products in Russia

The area of impact zones of industrial contamination, oil and oil products spills, motor vehicle emissions, radioactive substances, as well as pesticides and mineral fertilizers application on agricultural lands of the Russian Federation is calculated. The share of the territory under consideration in the total area of agricultural lands of the country does not exceed 3%. Soils in the zone of contamination influence are considered to be potentially polluted and should be included in the monitoring program of agricultural land. Soils outside the zone of influence of pollutant dissemination are uncontaminated. Regular monitoring of contamination of these soils should not be carried out, which will reduce the costs of monitoring. More than 97% of the Russian agricultural land is represented by uncontaminated soils and is suitable for the production of bio products. Regular monitoring of contamination of these soils should not be conducted, which will reduce the cost of the survey, including sample collection, preparation and analysis. In view of the lack of soil contamination, the transition to the cultivation of bio products should be based on declarative approach. In this case, bio production should meet the requirements of special cultivation technologies and the product quality standards.

Проповедь личного безличного Бога в учении Свами Вивекананды

The article examines the concept of God presented in the teachings of the world famous Indian religious reformer and public figure Swami Vivekananda. The thinker seeks to reconcile the understanding of God in Hinduism and Western religious traditions, and therefore argues that God has both personal and impersonal aspects at the same time. The purpose of the research is to reveal the essence of the idea of a personal impersonal God proposed by Vivekananda, as well as to clarify the possibilities and conditions for the predominance of one aspect of God over another. Modern philosophers distinguish three approaches to the consideration of God as a person: God is a person and so personal, God is non-personal, and so is not a person, God is a personal non-person. The article takes the characteristics of the personal existence of God in Christianity as the basis for understanding God as a person in the views of the Indian thinker. To estimate the presentation of the personal aspect of God by Vivekananda, a combination of approaches is used: declarative, anthropocentric, attributive, substantive-hypostatic and biographical. The declarative approach points to the equivalence of the personal and impersonal aspects of God in Vivekananda's views, the anthropocentric and attributive approaches speak of the predominance of the personal aspect of God. The substantial-hypostatic approach demonstrates the philosopher's attitude to God as a substance, but not a hypostasis, which is characteristic of Indian religious metaphysics. The biographical approach indicates the displacement of the impersonal aspect of God by the personal aspect. The study concludes that Vivekananda's views on the idea of a personal impersonal God must be placed between the ideas of proponents of the impersonal Absolute and theistic personalists who consider God as a person and so personal. The author considers the influence of socio-historical conditions of the formation of Indian society at the turn of the XIX-XX centuries to be the reason for the closeness of the philosopher's views to theistic personalism. The philosopher built his religious and philosophical teaching taking into account the need to educate a free personality for a future independent India. Therefore, God in Vivekananda's views has acquired the characteristics of a personality in its modern understanding.

A review on declarative approaches for constrained clustering

Clustering is an important Machine Learning task, which aims at discovering the implicit structure of data. Applying a clustering algorithm is easy but since clustering is an unsupervised task, tuning it so that the results is appropriate to the expert expectations is much less obvious. To overcome this, expert knowledge can be integrated into a clustering process; this is generally formalized as constraints on the desired output, thus leading to constrained clustering. There are two lines of research for clustering: distance based clustering, where data are grouped into clusters according to their dissimilarity and conceptual clustering, where a cluster must be a concept that is a set of objects and a set of properties that describe them. This second approach relies on Formal Concept Analysis and benefits from advances in Pattern Mining. [66] has shown the interest of declarative approaches for pattern mining and has led to a new research direction for clustering that is interested in the use of declarative frameworks, such as Integer Linear Programming, Constraint Programming or SAT. This has several advantages: finding a global optimum, integrating different kinds of constraints, even complex ones in a clustering process and even combining conceptual and distance-based clustering. In this paper we present an inventory of constraints and a survey of declarative methods for constrained clustering.

РОЛЬ ESG-ІНВЕСТУВАННЯ В ЗАБЕЗПЕЧЕННІ ІНКЛЮЗИВНОГО РОЗВИТКУ ПІДПРИЄМСТВ, РЕГІОНІВ, ДЕРЖАВИ

The article presents the results of a study of the content of the concept of inclusive development of economic systems in modern conditions and outlines the priority areas of responsible financing as a mechanism for overcoming the current political challenges and post-war reconstruction of the Ukrainian state. The importance of the environmental, social and governance component (ESG factors) as investment benchmarks in the context of ensuring inclusive development and achieving sustainable development goals is proved. The evolution of methodological tools for assessing the effectiveness of social responsibility of business and ESG parameters is analysed. The article establishes that algorithms for effective comparison of ESG investment performance are currently available to investment investors, which allows them to qualitatively measure, evaluate and manage processes in the field of responsible entrepreneurship. The global trend towards the implementation of the ESG approach by key financial market institutions of the world is identified and the dynamics of growth in the number of ESG exchange-traded funds is summarised. The positive achievements and inhibiting factors on the way to scaling the ESG transition in the strategies of domestic companies are outlined. The current state of implementation of ESG factors in the Ukrainian business environment is determined. The discrepancy between declarative approaches to the development strategies of companies and the content of their non-financial reporting is revealed. The national portal is evaluated in the context of presenting and promoting key ESG aspects. The need to increase attention to ensuring inclusive development of the state and its economic systems within the framework of ESG strategies as one of the priority solutions in the context of post-war reconstruction of the country was identified. The practical impact of ESG investing on the inclusive development of systems of different levels – from corporate to macroeconomic – is diversified. The article emphasises the interconnection and interdependence of social values with fiduciary benefits, which makes it a priority to further search for incentives to attract business structures to socially responsible entrepreneurship at the state level.

Prototyping a ROOT-based distributed analysis workflow for HL-LHC: The CMS use case

The challenges expected for the next era of the Large Hadron Collider (LHC), both in terms of storage and computing resources, provide LHC experiments with a strong motivation for evaluating ways of rethinking their computing models at many levels. Great efforts have been put into optimizing the computing resource utilization for the data analysis, which leads both to lower hardware requirements and faster turnaround for physics analyses. In this scenario, the Compact Muon Solenoid (CMS) collaboration is involved in several activities aimed at benchmarking different solutions for running High Energy Physics (HEP) analysis workflows. A promising solution is evolving software towards more user-friendly approaches featuring a declarative programming model and interactive workflows. The computing infrastructure should keep up with this trend by offering on the one side modern interfaces, and on the other side hiding the complexity of the underlying environment, while efficiently leveraging the already deployed grid infrastructure and scaling toward opportunistic resources like public cloud or HPC centers. This article presents the first example of using the ROOT RDataFrame technology to exploit such next-generation approaches for a production-grade CMS physics analysis. A new analysis facility is created to offer users a modern interactive web interface based on JupyterLab that can leverage HTCondor-based grid resources on different geographical sites. The physics analysis is converted from a legacy iterative approach to the modern declarative approach offered by RDataFrame and distributed over multiple computing nodes. The new scenario offers not only an overall improved programming experience, but also an order of magnitude speedup increase with respect to the previous approach.

Using facial emotion recognition to research emotional phases in an inquiry-based science activity

ABSTRACT Background Observational and declarative approaches applied by human observers have dominated the study of emotions, engagement, and attention. However, these approaches are susceptible to biases such as social desirability. Additionally, declarative approach cannot measure these parameters in real-time. Purpose This study aims to apply Facial Emotion Recognition (FER) technology in an inquiry-based activity to address the limitations of traditional observational and declarative approaches. We measured students’ emotions, engagement, and attention through the parametric measurement of facial expressions frame by frame. Method and procedure We recruited a convenience sample of 12 secondary education pre-service teachers. Students participated in a 20-minute inquiry-based activity where they were tasked with identifying the contents of a sealed black box. We recorded their facial expressions and actions with a video camera, and the collected data was subsequently analysed by both a FER automatic software and a human observer. Results During the activity, Attention had a mean presence of 81.24% ±5.93, Engagement had a presence of 31.86% ±9.10, Joy of 7.62% ±7.11, and Surprise of 6.57% ±4.61. The presence of the other discrete emotions was low. Our analysis further revealed an evolution of these parameters and students’ actions, progressing through three distinct phases: accommodation to the problem (Phase 1), exploration of problem-solving strategies (Phase 2), and implementation of problem-solving strategies (Phase 3). Based on these observations, we grouped students into three patterns based on the phases they underwent throughout the activity. Conclusion This study shows the application of FER technology for identifying and analysing the progression of students’ emotions, engagement, and attention during an inquiry-based activity. FER technology allows real-time and systematic measurement of emotions, engagement, and attention. However, this technology has inherent limitations, and further research is needed to optimise its application in the educational setting.

Decomposition approaches for scheduling chronic outpatients’ clinical pathways in Answer Set Programming

Abstract Chronic patients suffering from non-communicable diseases are often enrolled into a diagnostic and therapeutic care program featuring a personalized care plan. Healthcare is mostly provided at the patient’s home, but those examinations and treatments that must be delivered at the hospital have to be explicitly booked. Booking is not trivial due to, on the one hand, the several time constraints that become particularly tight in the case of comorbidity, on the other hand, the limited availability of both staff and equipment at the hospital care units. This suggests that the scheduling of the clinical pathways for enrolled outpatients should be managed in a centralized manner, taking advantage of the fact that demand for services is known well in advance. The aim is to serve as many requests as possible (unattended requests are supplied by contracted private health facilities) in a timely manner, taking patients priority into account. Booking involves setting a date and a time for each selected health service, which is rather complex. In this work, we provide a declarative approach by encoding the problem in Answer Set Programming (ASP). In order to improve the scalability of the ASP approach, we present and compare two heuristic approaches, respectively based on service demand and time decomposition. All approaches are tested on instances of increasing size to assess scalability with respect to time horizon and number of requests.

Leveraging HPC resources with distributed RDataFrame

The declarative approach to data analysis provides high-level abstractions for users to operate on their datasets in a much more ergonomic fashion compared to imperative interfaces. ROOT offers such a tool with RDataFrame, which has been tested in production environments and used in real-world analyses with optimal results. Its programming model acts by creating a computation graph with the operations issued by the user and executing it lazily only when the final results are queried. It has always been oriented towards parallelisation, with native support for multi-thread execution on a single machine. Recently, RDataFrame has been extended with a Python layer that is capable of steering and executing the RDataFrame computation graph over a set of distributed resources. In addition, such a layer requires minimal code changes for an RDataFrame application to run distributedly. The new tool effectively allows running a C++ event loop based on RDataFrame while leveraging common industry tools like Dask to schedule the usage of resources. This work presents results and insights gathered through the distributed RDataFrame tool running a physics analysis connecting multiple nodes with a Dask scheduler that requests resources from a Slurm cluster.

Intent-based network slicing for SDN vertical services with assurance: Context, design and preliminary experiments

Network slicing is announced to be one of the key features for 5G infrastructures enabling network operators to provide network services with the flexibility and dynamicity necessary for the vertical services, while relying on Network Function Virtualization (NFV) and Software-defined Networking (SDN). On the other hand, vertical industries are attracted by flexibility and customization offered by operators through network slicing, especially if slices come with in-built SDN capabilities to programmatically connect their application components and if they are relieved of dealing with detailed technicalities of the underlying (virtual) infrastructure.In this paper, we present an Intent-based deployment of a NFV orchestration stack that allows for the setup of Qos-aware and SDN-enabled network slices toward effective service chaining in the vertical domain. The main aim of the work is to simplify and automate the deployment of tenant-managed SDN-enabled network slices through a declarative approach while abstracting the underlying implementation details and unburdening verticals to deal with technology-specific low-level networking directives. In our approach, the intent-based framework we propose is based on an ETSI NFV MANO platform and is assessed through a set of experimental results demonstrating its feasibility and effectiveness.

Declarative Data Flow in a Graph-Based Distributed Memory Runtime System

Runtime systems can significantly reduce the cognitive complexity of scientific applications, narrowing the gap between systems engineering and domain science in HPC. One of the most important angles in this is automating data migration in a cluster. Traditional approaches require the application developer to model communication explicitly, for example through MPI primitives. Celerity, a runtime system for accelerator clusters heavily inspired by the SYCL programming model, instead provides a purely declarative approach focused around access patterns. In addition to eliminating the need for explicit data transfer operations, it provides a basis for efficient and dynamic scheduling at runtime. However, it is currently only suitable for accessing array-like data from runtime-controlled tasks, while real programs often need to interact with opaque data local to each host, such as handles or database connections, and also need a defined way of transporting data into and out of the virtualised buffers of the runtime. In this paper, we introduce a graph-based approach and declarative API for expressing side-effect dependencies between tasks and moving data from the runtime context to the application space.

Cropbox: a declarative crop modelling framework

AbstractWe introduce Cropbox, a novel modelling framework that supports various aspects of crop modelling in a unique yet concise style. Building a crop model can be easily riddled with technical details looking trivial at first but later becoming major obstacles that hamper the whole development or application process. This is particularly the case when implementing models from scratch without relying on an established framework. Cropbox adopts a declarative approach providing a domain-specific language to reduce technical debt and assist modellers to focus on high-level abstraction formed by relations between variables and enclosing systems, rather than tinkering with low-level implementation details. The syntax of Cropbox framework is based on the Julia programming language and is deliberately constrained to avoid unintended side effects caused by common mistakes while its architecture remains open to extension. We highlight key capabilities of the framework through case studies featuring a leaf gas-exchange model and a whole-plant simulation model. We also illustrate potential extensions for supporting functional-structural plant modelling by demonstrating a 3D root architectural model as an example.

An Energy-aware Ad-hoc Routing Strategy for Queriable Wireless Sensor Networks

The data volume handled by wireless sensor networks (WSN) is ever growing due to increasing node counts and node complexity – be it in traditional WSN applications or for Car2X or Internet-of-Things. Queriable WSN are a concept to handle the large data volumes in such networks by abstracting the network as a virtual database table to which users can pose queries. This declarative approach enables networks which can flexibly adapt to changing application requirements. In addition they possess a flat learning curve since users do not need to have a high technological understanding of the sensor node firmware. Upon executing a query it is first propagated through the network and once it has reached the desired nodes, results are collected and send back through the query-posing node (usually the sink). The routing which is used for the data aggregation step plays a major role in the energy efficiency in networks with increasing node and sensor value counts as represented by Car2X networks for instance. In this paper, an ad-hoc routing strategy for queriable WSN is proposed which is both energy-aware and application-specific. It will be shown that this routing can contribute greatly towards decreasing the energy consumption needed for data aggregation and thus helps increasing the network’s lifespan.

A Graph-based and Declarative Approach to a Secure Resource Management in Smart Factories

The article presents an applied research using the Design Science Research Methodology for securely managing resources of smart factories via a graph-based approach combined with a declarative query language. This query language can be used to find appropriate production facilities that are able to fulfill specific manufacturing tasks. This approach is aimed to solve the problem with the management effort for production facilities using enumeration for naming these facilities for the manufacturing tasks. Thus, the security is ensured by identifying the “current” valid identities (resources). Additionally, the usage of deputy relationships leads to alternative production facilities if resources have a breakdown or have to be serviced which has an effect on the availability.

A Graph-based and Declarative Approach to a Secure Resource Management in Smart Factories

A Graph-based and Declarative Approach to a Secure Resource Management in Smart Factories

Circular Economy in the Context of Food Losses and Waste

Although consumption is one of the most important elements of any economy, including those that are developing, excessive consumerism is becoming increasingly common today, often resulting in the phenomenon of food waste. Food waste is a multi-aspect issue. It is a topical problem of varying nature and intensity, particularly for the environment, the economy, and society. In this context, efforts were made to emphasize the importance of the idea of a circular economy, due to the fact that the positive effects of its implementation and correct application may be the minimization of the problem of food waste, which can be seen from an economic, social, or environmental point of view. To obtain this goal, consumer research was conducted among the inhabitants of Eastern Poland. Their principal task was to define social attitudes and explain a problem known as household food waste. The results were subjected to the cluster analysis method and correspondence analysis, and the corresponding calculations and figures made it possible to draw conclusions from the research. Consumers seem to be aware of the dilemma of excessive food discarding in their households. They also recognize their active role in preventing this socio-economic problem. Despite the concerns expressed by consumers, food waste is still very high. This may most likely be because of a declarative approach rather than to the actual attitudes of respondents.