Formal Notation Research Articles

Smart-KG: Partition-Based Linked Data Fragments for querying knowledge graphs

RDF and SPARQL provide a uniform way to publish and query billions of triples in open knowledge graphs (KGs) on the Web. Yet, provisioning of a fast, reliable, and responsive live querying solution for open KGs is still hardly possible through SPARQL endpoints alone: while such endpoints provide a remarkable performance for single queries, they typically can not cope with highly concurrent query workloads by multiple clients. To mitigate this, the Linked Data Fragments (LDF) framework sparked the design of different alternative low-cost interfaces such as Triple Pattern Fragments (TPF), that partially offload the query processing workload to the client side. On the downside, such interfaces still come with the expense of unnecessarily high network load due to the necessary transfer of intermediate results to the client, leading to query performance degradation compared with endpoints. To address this problem, in the present work, we investigate alternative interfaces, refining and extending the original TPF idea, which also aims at reducing server-resource consumption, by shipping query-relevant partitions of KGs from the server to the client. To this end, first, we align formal definitions and notations of the original LDF framework to uniformly present existing LDF implements and such “partition-based” LDF approaches. These novel LDF interfaces retrieve, instead of the exact triples matching a particular query pattern, a subset of pre-materialized, compressed, partitions of the original graph, containing all answers to a query pattern, to be further evaluated on the client side. As a concrete representative of partition-based LDF, we present smart-KG+, extending and refining our prior work (In WWW ’20: The Web Conference 2020 (2020) 984–994 ACM / IW3C2) in several respects. Our proposed approach is a step forward towards a better-balanced share of the query processing load between clients and servers by shipping graph partitions driven by the structure of RDF graphs to group entities described with the same sets of properties and classes, resulting in significant data transfer reduction. Our experiments demonstrate that the smart-KG+ significantly outperforms existing Web SPARQL interfaces on both pre-existing benchmarks for highly concurrent query execution as well as an accustomed query workload inspired by query logs of existing SPARQL endpoints.

Bridging musical gaps: creating educational songs with thematic learning for primary school students

This study investigates how elementary school teachers without musical backgrounds create educational songs to support thematic learning under Indonesia's Kurikulum Merdeka. Thematic learning aims to integrate various subjects into cohesive themes, fostering student-centered learning (SCL) and emphasizing active engagement and critical thinking. Although the government provided the guiding textbooks, teachers face challenges in implementing SCL. Eventually, they often revert to conventional, teacher-centered methods. Previous research indicates that songs can serve as effective educational tools, but there is still a lack of thematic songs that align with the curriculum's specific themes. Using a case study approach, this research involved classroom observations, document analysis, and interviews with two first-grade teachers who developed songs for an environmental theme. The study found that teachers could create educational songs by deriving lyrics from teaching materials and improvising melodies, although they needed formal musical notation skills. Teachers and students then used these songs in classroom instruction, engaging in singing and physical activities. Despite inconsistencies in musical performance, the findings indicated that students were enthusiastic and better understood the material through these songs. The study highlights teachers' adaptive nature in leveraging available resources to meet educational objectives and emphasizes the importance of integrating arts, particularly music, into educational practices. The research contributes to the broader discourse on educational innovation, suggesting that even teachers without musical training can effectively create and use educational songs to enhance learning. Empowering teachers with resources and training in songwriting could further enrich thematic learning, fostering creativity, critical thinking, and collaboration among students. This approach aligns with the goals of the Kurikulum Merdeka, supporting holistic educational reforms and improving learning outcomes in Indonesian elementary education.

Multifaceted formal methods and their interdisciplinary role — From the cathedral of ‘components as coalgebras’ to the HCI context and the open source software bazaar

In this article we revisit the history of formal methods with a focus on important aspects that contribute to their interdisciplinary role. We consider: the variability of mathematical representation techniques on which the theoretical foundations of formal methods are based; formal methods multidisciplinarity; their capability to serve at a meta-level in providing the semantics of programming languages, specification and modelling languages as well as higher-level and domain-specific formal notations; and, finally, how some of these higher-level and domain-specific notations may be lifted at an interdisciplinary level.Within this historical review, we are inspired by Luís Barbosa's “components as coalgebras” approach in seeing that the duality data-process is underlying all those aspects of formal methods. We also see that such a duality may not only be expressed in universal terms within category theory, but may also be characterised in practical terms and focused applications by two distinct logic paradigms, equational logic for the data and rewriting logic for the process, by two modelling directions, forward process definitions and backward data-driven process transformations, and by the distinction between syntax, defined by the data structures, and semantics, provided by rewrite rules. We use the Maude modelling language to illustrate the application of the data-process duality. In fact, Maude use equational logic to define data types and rewriting logic to express system evolution. Illustrative examples are from the areas of cognitive science and human-computer interaction (HCI).We then define a data-driven model transformation, which we call elaborative mining, which adopts a backward perspective to recover a behaviour that was observed in real life but was not predicted forward by the original model. Finally, we see how the “open source software bazaar”, which is a metaphor for the apparently chaotic open source development process, offers us a big data context to lift the driving process for model transformation from deterministic to statistical.

Mapping Petri Nets onto a Calculus of Context-Aware Ambients

Petri nets are a graphical notation for describing a class of discrete event dynamic systems whose behaviours are characterised by concurrency, synchronisation, mutual exclusion and conflict. They have been used over the years for the modelling of various distributed systems applications. With the advent of pervasive systems and the Internet of Things, the Calculus of Context-aware Ambients (CCA) has emerged as a suitable formal notation for analysing the behaviours of these systems. In this paper, we are interested in comparing the expressive power of Petri nets to that of CCA. That is, can the class of systems represented by Petri nets be modelled in CCA? To answer this question, an algorithm is proposed that maps any Petri net onto a CCA process. We prove that a Petri net and its corresponding CCA process are behavioural equivalent. It follows that CCA is at least as expressive as Petri nets, i.e., any system that can be specified in Petri nets can also be specified in CCA. Moreover, tools developed for CCA can also be used to analyse the behaviours of Petri nets.

From programming-to-modeling-to-prompts smart ubiquitous applications

Since its introduction by Mark Weiser, ubiquitous computing has received increased interest in the dawn of technological advancement. Supported by wireless technology advancement, embedded systems, miniaturization, and the integration of various intelligent and communicative devise, context-aware ubiquitous applications actively and intelligently use rich contextual information to assist their users. However, their designs are subject to continuous changes imposed by external factors. Nowadays, software engineering, particularly in the fields of Model-Driven Engineering, displays a strong tendency towards developing applications for pervasive computing. This trend is also fueled by the rise of generative artificial intelligence, paving the way for a new generation of no-code development tools and models specifically trained on open-source code repositories to generate applications from their descriptions. The specificities of our approach lies in starting with a graphical model expressed using a domain-specific language (DSL) composed of symbols and formal notations. This allows for graphically instantiating and editing applications, guiding and assisting experts from various engineering fields in defining ubiquitous applications that are eventually transformed into peculiar models. We believe that creating intelligent models is the best way to promote software development efficiency. We have used and evaluated recurrent neural networks, leveraging the recurrence of processing the same contextual information collected within this model, and enabling iterative adaptation to future evolutions in ubiquitous systems. We propose a prototype instantiated by our meta-model which tracks the movements of individuals who were positive for COVID-19 and confirmed to be contagious. Different deep learning models and classical machine learning techniques are considered and compared for the task of detection/classification of COVID-19. Results obtained from all techniques were evaluated with confusion matrices, accuracy, precision, recall and F1-score. In summary, most of the results are very impressive. Our deep learning approach used a RNN architecture produced up to 92.1% accuracy. With the recent development of OpenAI Codex, optimized for programming languages, we provided the same requirements to the Codex model and asked it to generate the source code for the COVID-19 application, comparing it with the application generated by our workshop.

Novel adaptive DCOPA using dynamic weighting for vector of performances indicators optimization of IoT networks

Clustering in the Internet of Things (IoT) involves organizing devices into groups to streamline network management and optimize resource utilization, including Internet connections, energy usage, coverage, quality of service, and connectivity. DCOPA (A Distributed Clustering Based on Objects Performances Aggregation for Hierarchical Communications in IoT Applications) is a recent distributed clustering protocol based on a timer for cluster formation where the election of Cluster Heads (CHs) is modeled as a multicriteria problem. In this paper, three contributions are presented. Firstly, the DCOPA protocol is analyzed with a focus on its multi-criteria aggregation function T(i) which directly contributes to the election of the CHs and the formation of the network’s clusters. This is then followed by an in-depth analysis of the impact and the variation of the weights assigned to the two aggregated criteria which are the energy and the distance from the base station. A verification of the scalability, load balancing and distribution of the clusters and CHs will follow. Secondly, a new formal notation for the performance analysis, specifically focusing on the mortality and lifetime based on the Vector of Performance Indicators (VPI), will be introduced for IoT. As a third contribution, a revised version of DCOPA is introduced called ADCOPA (Adaptive DCOPA Using Dynamic Weighting for Vector of Performances Indicators Optimization of IoT Networks). ADCOPA is based on a new property which is the dynamicity or the variability of the weights of the criteria used in the election function of CHs. The simulation results show that the ADCOPA algorithm, which dynamically adjusts the weights of the criteria during the network’s lifetime, outperforms the DCOPA algorithm. The latter uses static weights for the criteria that remain unchanged for the entire lifetime of the network. This confirms that the ability to dynamically adjust the weighting of the criteria is an important factor in achieving better performance.

User Centered Non-Functional Requirements Specification – An Extended Use-Case Diagram

Requirements Engineering (RE) activity is often initiated with vaguely specified software requirements. The ambiguities must be overcome to the extent possible when the requirements are specified. Both functional (FRs) and non-functional (NFRs) requirements should be correctly and unambiguously specified. Users communicate about the NFRs in informal discussions. Requirements engineers use formal or semi-formal language notations to manually convey the NFRs. A laborious and ineffective manual approach, however, is unable to identify all likely NFRs and resolve ambiguities in those NFRs. This paper discusses an approach that attempts to overcome ambiguities from natural language requirements, recognize NFRs, and generate NFR specification through the extended Unified Modelling Language (UML) viz. use-case diagram. The empirical evaluation of the proposed approach on the PROMISE dataset achieves an average result of 79.76% recall, 90.05% precision, and 84.59% F-measure. The proposed approach allows the requirements analyst to semi-automatically recognize NFRs and visualize them using an extended use-case diagram at an early stage of RE.

Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems

Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allows them to meet latency requirements and real-time operation. Highly relevant to the industry and our reference case-study, the challenging field of nuclear fusion deploys the aforementioned applications, involving high-frequency control with hard real-time and safety constraints. The use of fog computing and MPSoCs is promising to achieve safety, low latency, and timeliness of such control. Indeed, on one hand, applications designed according to fog computing distribute computation across hierarchically organized and geographically distributed edge devices, enabling timely anomaly detection during high-frequency sampling of time series, and, on the other hand, MPSoCs allow leveraging fog computing and integrating monitoring by deploying tasks on a flexible platform suited for mixed-criticality software, leading to so-called mixed criticality systems (MCSs). However, the integration of such software on the same MPSoC opens challenges related to predictability and reliability guarantees, as tasks interfering with each other when accessing the same shared MPSoC resources may introduce non-deterministic latency, possibly leading to failures on account of deadline overruns. Addressing the design, deployment, and evaluation of MCSs on MPSoCs, we propose a model-based system development process that facilitates the integration of real-time and monitoring software on the same platform by means of a formal notation for modeling the design and deployment of MPSoCs. The proposed notation allows developers to leverage embedded hypervisors for monitoring real-time applications and guaranteeing predictability by isolation of hardware resources. Providing evidence of the feasibility of our system development process and evaluating the industry-relevant class of nuclear fusion applications, we experiment with a safety-critical case-study in the context of the ITER nuclear fusion reactor. Our experimentation involves the design and evaluation of several prototypes deployed as MCSs on a virtualized MPSoC, showing that deployment choices linked to the monitor placement and virtualization configurations (e.g., resource allocation, partitioning, and scheduling policies) can significantly impact the predictability of MCSs in terms of Worst-Case Execution Times and other related metrics.

A user study for evaluation of formal verification results and their explanation at Bosch

ContextEnsuring safety for any sophisticated system is getting more complex due to the rising number of features and functionalities. This calls for formal methods to entrust confidence in such systems. Nevertheless, using formal methods in industry is demanding because of their lack of usability and the difficulty of understanding verification results.ObjectiveWe evaluate the acceptance of formal methods by Bosch automotive engineers, particularly whether the difficulty of understanding verification results can be reduced.MethodWe perform two different exploratory studies. First, we conduct a user survey to explore challenges in identifying inconsistent specifications and using formal methods by Bosch automotive engineers. Second, we perform a one-group pretest-posttest experiment to collect impressions from Bosch engineers familiar with formal methods to evaluate whether understanding verification results is simplified by our counterexample explanation approach.ResultsThe results from the user survey indicate that identifying refinement inconsistencies, understanding formal notations, and interpreting verification results are challenging. Nevertheless, engineers are still interested in using formal methods in real-world development processes because it could reduce the manual effort for verification. Additionally, they also believe formal methods could make the system safer. Furthermore, the one-group pretest-posttest experiment results indicate that engineers are more comfortable understanding the counterexample explanation than the raw model checker output.LimitationsThe main limitation of this study is the generalizability beyond the target group of Bosch automotive engineers.

An Improved User Requirements Notation (URN) Models’ Construction Approach

Semi-formal software techniques have been very successful in industry, government institutions and other areas such as academia. Arguably, they owe a large part of their success to their graphical notation, which is more human-oriented than their counterpart text-based and formal notation techniques. However, ensuring the consistency between two or more models is one of the known challenges of these techniques. This work looks closely at the specific case of the User Requirements Notation (URN) technique. Although the abstract model of URN provides for link elements to ensure the consistency between its two main components, namely, Goal-Oriented Requirement Language (GRL) and Use Case Maps (UCM), the effective implementation of such links is yet to be fully addressed. This paper performs a detailed analysis of the existing URN models construction process and proposes an improved process with some guidelines to ensure, by construction, the correctness and consistency of the GRL and UCM models. A case study is used throughout the paper to illustrate the suggested solution.

Actors, Roles, and Behaviours

This paper attempts to look at Fightbooks as literary sources and apply this reasoning to ADVISE reconstruction methodology. First the concepts of Real and Imaginary Worlds is introduced, followed by the distinction between Actors and Roles. Based on descriptions each Actor and Role can be assigned a set of Actions, Decisions, Intentions and Goals that constitute their Behaviours. Depending on Perspective, such Behaviours can be divided into Expected and Unexpected.
 Reconstruction is then looked at as an effort to gain deeper insight into described Roles and Actors through enacting of their Behaviours. Applying these concepts to ADVISE methodology allows for more nuanced and stricter process by focusing on Actions in Phase 1 and Decisions in Phase 2. Phase 5 introduces formal set theory notation that allows for a consistent high-level reasoning about the content of recorded message. Discussion addresses potential criticisms and further applications of this approach, demonstrating how it can bring more clarity to the whole process, especially when it comes to properly defining future experiments.

DEVELOPMENT OF PROBLEM-SPECIFIC MODELING LANGUAGE TO SUPPORT SOFTWARE VARIABILITY IN "SMART HOME" SYSTEMS

Building conceptual models for software design, in particular for high-tech applications such as smart home systems, is a complex task that significantly affects the efficiency of their development processes. One of the innovative methods of solving this problem is the use of domain-specific modeling languages (DSMLs), which can reduce the time and other project resources required to create such systems. The subject of research in this paper is approaches to the development of DSML for Smart Home systems as a separate class of Internet of Things systems. The purpose of this work is to propose an approach to the development of DSMLs based on a model of variability of the properties of such a system. The following tasks are being solved: analysis of some existing approaches to the creation of DSMLs; construction of a multifaceted classification of requirements for them, application of these requirements to the design of the syntax of a specific DSML-V for the creation of variable software in smart home systems; development of a technological scheme and quantitative metrics for experimental evaluation of the effectiveness of the proposed approach. The following methods are used: variability modeling based on the property model, formal notations for describing the syntax of the DSML-V language, and the use of the open CASE tool metaDepth. Results: a multifaceted classification of requirements for a broad class of DSML languages is built; the basic syntactic constructions of the DSML-V language are developed to support the properties of software variability of "Smart Home" systems; a formal description of such syntax in the Backus-Naur notation is given; a technological scheme for compiling DSML-V specifications into the syntax of the language of the open CASE tool metaDepth is created; the effectiveness of the proposed approach using quantitative metrics is experimentally investigated. Conclusions: the proposed method of developing a specialized problem-oriented language for smart home systems allows for multilevel modeling of the variability properties of its software components and provides an increase in the efficiency of programming such models by about 14% compared to existing approaches.

Architecture and Governance of Digital Business Ecosystems: A Systematic Literature Review

ABSTRACT The purpose of this study is to examine the reported architectural approaches and governance mechanisms for digital business ecosystems (DBEs). A systematic literature review is employed, in which 92 relevant articles are selected for analysis. This study provides an overview of articles, reports the formal modeling notations, modeling viewpoints, and design patterns used for DBEs in the reviewed articles, discusses DBE governance mechanisms, and provides evidence of the alignment between DBE architecture and DBE governance.

Survey of window types for aggregation in stream processing systems

In this paper, we present the first comprehensive survey of window types for stream processing systems which have been presented in research and commercial systems. We cover publications from the most relevant conferences, journals, and system whitepapers on stream processing, windowing, and window aggregation which have been published over the last 20 years. For each window type, we provide detailed specifications, formal notations, synonyms, and use-case examples. We classify each window type according to categories that have been proposed in literature and describe the out-of-order processing. In addition, we examine academic, commercial, and open-source systems with respect to the window types that they support. Our survey offers a comprehensive overview that may serve as a guideline for the development of stream processing systems, window aggregation techniques, and frameworks that support a variety of window types.

Methodological aspects of risk mapping in multimode transport systems

Efficient transport solutions are based on multimodal systems, with the dominant role of rail and road transport in land versions of the systems and the connecting and directing part of intermodal terminals, transhipment terminals or warehouse centres. The implementation of transport processes is always associated with the risk of lack of timeliness (quality) or threats to people, equipment and cargo (safety) resulting from human, technical, organizational and global factors like pandemics or war. The article contains a risk mapping method in multimodal transport systems configured to estimate the risk of lowering the quality of logistics services (on-time deliveries, etc.). The method combines factors usually considered separately in studies on individual modes of transport. A formal notation of risk factors as a mathematical model was proposed, and a case study was provided to picture the implementation.

Formalizing Attack Tree on Security Object for MySANi in Legal Metrology

Illegal software manipulation is one of the biggest issues in software security. This includes the legally relevant software which are now crucial modules in weight and measuring instruments such as weighbridges. Despite the advancement and complexity of weight and measuring instruments, the inspection methodology is weak and lacks of innovation. The conventional inspection method is merely based on the observation printed certificate of the software. This paper introduces Malaysia Software-Assisted Non-Automatic Weighing Instrument (NAWI) Inspection (MySANI), a method used to enhance the software inspection scheme in legal metrology. MySANI introduces security objects in order to assist and enhance the inspection process. The security evaluation is based on the best practices in IT in metrology, where the attack model on relevant assets of the security objects is simulated for the Attack Probability Tree. The attack tree is verified by integrating formal notation and comparison with finite state transition system domain to verify the correctness properties of the tree design before the model can be further used in a risk analysis procedure within the Attack Probability Tree framework. Results show that the designed attack tree is consistent with the designed simulation.

Practical Verification of Railway Signalling Programs

SafeCap is a modern toolkit for modelling, simulation and formal verification of railway networks. This paper discusses the use of SafeCap for formal analysis and automated scalable safety verification of solid state interlocking (SSI) programs – a technology at the heart of many railway signalling solutions around the world. The main driving force behind SafeCap development was to make it easy for signalling engineers to use the technology and thus to ensure its smooth industrial deployment. The unique qualities and the novelty of SafeCap are in making the use of formal notations and proofs fully transparent for the engineers. In this paper we explain the formal foundations of the proposed method, its tool support, and its successful application by railway companies in developing industrial signalling projects.

A model-based approach for vulnerability analysis of IoT security protocols: The Z-Wave case study

IoT (Internet of Things) devices are extensively used in security-critical services, as for example home door opening, gas monitoring, alarm systems, etc. Often, they use communication protocols with no standardisation and no security guarantee. Unsecured use of connected devices can cause threats or damages to the users, so security assurance, which can be ensured by the use of formal methods, must be guaranteed. Unfortunately practical usage of formal methods during the protocol design is very limited or missing at all.To address the problem of providing the designer with a user-friendly but rigorous design approach based on the use of formal methods, supporting security assurance already at the model level, but hiding the complexity of formal notations and verification techniques, in this paper we propose an approach, based on the Abstract State Machine formal method, for the specification and verification of security protocols. Specifically, we introduce a set of built-in primitives to model communication protocols and their security properties. Security verification can be carried out under the hypothesis of either a passive or an active attacker.The effectiveness of this approach is shown by means of its application to the Z-Wave protocol, claimed to be one of the most secure protocol for IoT devices communication thanks to the addition of the S2 Security class. We show the formal specification of the Z-Wave protocol and the security verification process.

Historical perspective of code clone refactorings in evolving software.

Cloning in software is generally perceived as a threat to its maintenance and that is why it needs to be managed properly. Understanding clones from a historical perspective is essential for effective clone management. Analysis of code refactorings performed on clones in previous releases will help developers in taking decisions about clone refactoring in future releases. In this paper we perform a longitudinal study on the evolution of clone refactorings in various versions of five software systems. To perform a systematic study on clone refactoring evolution, we define clone evolution patterns for studying refactorings in a formal notation. Our results show that only a small proportion of code clones are refactored between the versions and most of the refactorings are inconsistent within clone classes. Moreover, clone refactorings may cause clone removal. Analysis of the source code of refactored clones reveals similar reasons of inconsistent refactorings and clone removal for five Java systems. This analysis will help in devising appropriate strategies for managing clone refactorings in software and hence provide foundation for devising better clone management tools.

Communication-Focused Top-Down Design of Robotic Systems Based on Binary Decomposition

This article proposes a formal method of designing robotic systems focusing on communication between components, as well as standardization of the messages between those components. The objective is to design a robotic system controller in a systematic way, focusing on communication at an abstract agent level. Communication, thus organized, and its properly defined specification facilitate the system’s further development. The method uses a standard message structure, based on IEEE FIPA standards, for communication within robotic systems composed of agents. Communication-focused top-down design of robotic systems based on binary decomposition is proposed, and used to design a companion robot working in the kitchen environment. The implemented robotic system is verified based on whether or not the specification conforms to the specified requirements. The characteristics of the designed communication are evaluated. The obtained results prove that the proposed method of designing robotic systems is formally correct, it facilitates the implementation of agents, and separates specification of the system from its implementation. The method of designing robotic systems is correct and useful. The proposed formal notation facilitates understanding of how the system operates and organizes the design process. It puts the communication between system components at the forefront. The resulting system specification facilitates the implementation. The tools for experimental evaluation of its characteristics enable the confirmation that it fulfills the requirements, and that the communication between the system components is correct.