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Many REpresentational State Transfer (RESTful) Web services suffered from anti-patterns problem, which may diminish the sustainability of the services. The anti-patterns problem could happen in the code of the programme or the uniform resource identifiers (URIs) of RESTful Web services. This study aims to address the problem by proposing a technique and an algorithm for detecting anti-patterns in RESTful Web services. Specifically, the technique is designed based on URIs parsing process.

The study was conducted following the design science research process, which has six activities, namely, identifying problems, identifying solutions, design the solutions, demonstrate the solution, evaluation and communicate the solution. The proposed technique was embedded in an algorithm and evaluated in four phases covering the process of extracting the URIs, implementing the anti-pattern detection algorithm, detecting the anti-patterns and validating the results.

The results of the study suggested an acceptable level of accuracy for the anti-patterns detection with 82.30% of precision, 87.86% of recall and 84.93% of F-measure.

The technique and the algorithm can be used by developers of RESTful Web services to detect possible anti-pattern occurrences in the service-based systems.

The technique is personalised to detect amorphous URI and ambiguous name anti-patterns in which it scans the Web service URIs using specified rules and compares them with pre-determined syntax and corpus.

Context‐awareness is an essential property of any pervasive system perceiving its environment. Such a system captures and processes context, i.e. the features describing the relevant aspects of environment state and user behaviour. However, development of these systems still requires solving a number of research and engineering challenges. The purpose of this paper is to propose perception framework, a RESTful middleware which simplifies and accelerates the development of pervasive systems. Perception framework allows constructing services' application logic using rules and context. Moreover, it collects sensor data and produces the context information that is required for the rules. The authors present the architecture, design, complete implementation, and prototype‐based verification of perception framework.

Development of context‐aware services is achieved with a novel architecture supporting building of the logic of web services using rules which directly manipulate the available elementary context represented with the Web Ontology Language (OWL) ontology. These rules are described using the Rule Interchange Format (RIF) with support for different rule languages. The implementation of this framework is aligned with RESTful principles, providing a lightweight and flexible solution for large‐scale context‐aware systems.

The fully implemented prototype verifies the feasibility of constructing the logic of context‐aware web services with the rules supported by perception framework.

The contributions of this paper include: the requirement specification for a generic context‐aware pervasive middleware; and the design and implementation of the framework (i.e. perception framework) supporting the development of context‐aware web services. The perception framework includes a generic rule‐based reasoner allowing developers to use several RIF‐compliant rule description languages.

This column aims to investigate the possibilities of web services for the integration of information with relevant services.

This is a viewpoint paper.

This column encourages the exploration of web services based on careful analysis and semantic ontologies in order to provide relevant integration of services and information.

The rapid proliferation of web services – whether RESTful or SOAP based – offers many opportunities both internally and externally for libraries, but the adoption of web services needs to be tempered with careful planning and analysis.

The column offers some interesting suggestions for exploring theoretical options in the adoption of web service information and services. Some technical aspects of web service technology are discussed and then related to the core mission of librarianship, which is to assist patrons in navigating the great breadth of data available in increasing quantities via web service technology.

Drones are used in several purposes including examining areas, mapping surroundings and rescue mission operations. During these tasks, they could encounter compound surroundings having multiple obstacles, acute edges and deadlocks. The purpose of this paper is to propose an obstacle dodging technique required to move the drones autonomously and generate the obstacle's map of an unknown place dynamically.

Therefore, an obstacle dodging technique is essentially required to move autonomously. The automaton of drones requires complicated vision sensors and a high computing force. During this research, a methodology that uses two basic ultrasonic-oriented proximity sensors placed at the center of the drone and applies neural control using synaptic plasticity for dynamic obstacle avoidance is proposed. The two-neuron intermittent system has been established by neural control. The synaptic plasticity is used to find turning angles from different viewpoints with immediate remembrance, so it helps in decision-making for a drone. Hence, the automaton will be able to travel around and modify its angle of turning for escaping objects during the route in unknown surroundings with narrow junctions and dead ends. Furthermore, wherever an obstacle is detected during the route, the coordinate information is communicated using RESTful Web service to an android app and an obstacle map is generated according to the information sent by the drone. In this research, the drone is successfully designed and automated and an obstacle map using the V-REP simulation environment is generated.

Simulation results show that the drone effectively moves and turns around the obstacles and the experiment of using web services with the drone is also successful in generating the obstacle's map dynamically.

The obstacle map generated by autonomous drone is useful in many applications such as examining fields, mapping surroundings and rescue mission operations.

Semantic categorization of Web services comprises a fundamental requirement for enabling more efficient and accurate search and discovery of services in the semantic Web era. However, to efficiently deal with the growing presence of Web services, more automated mechanisms are required. This paper aims to introduce an automatic Web service categorization mechanism, by exploiting various techniques that aim to increase the overall prediction accuracy.

The paper proposes the use of Error Correcting Output Codes on top of a Logistic Model Trees-based classifier, in conjunction with a data pre-processing technique that reduces the original feature-space dimension without affecting data integrity. The proposed technique is generalized so as to adhere to all Web services with a description file. A semantic matchmaking scheme is also proposed for enabling the semantic annotation of the input and output parameters of each operation.

The proposed Web service categorization framework was tested with the OWLS-TC v4.0, as well as a synthetic data set with a systematic evaluation procedure that enables comparison with well-known approaches. After conducting exhaustive evaluation experiments, categorization efficiency in terms of accuracy, precision, recall and F-measure was measured. The presented Web service categorization framework outperformed the other benchmark techniques, which comprise different variations of it and also third-party implementations.

The proposed three-level categorization approach is a significant contribution to the Web service community, as it allows the automatic semantic categorization of all functional elements of Web services that are equipped with a service description file.

The purpose of this paper is to address the Internet of Things (IoT) service discovery problem and investigate the existing solutions to tackle this problem in many aspects.

This paper presents an overview of IoT services aiming at providing a clear understanding about their features because this term is still ambiguous for the IoT service discovery approaches. Besides, a full comparison study of the most representative service discovery approaches in the literature is presented over four perspectives: the IoT information model, the mechanism of IoT service discovery, the adopted architecture and the context awareness. These perspectives allow classifying, comparing and giving a deeper understanding of the existing IoT service discovery solutions.

This paper presents a new definition and a new classification of IoT services and citation of their features comparing with the traditional Web services. This paper discusses the existing solutions, as well as the main challenges, that face the service discovery issue in the IoT domain. Besides, two classifications of the approaches are adopted on the basis of their service description model and their mechanism of discovery, and a set of requirements that need to be considered when defining an IoT service are proposed.

There are few number works that survey the service discovery approaches in the IoT domain, but none of these surveys discuss the service description models in the IoT or the impact of the context awareness aspect in the service discovery solution. There are also few works that give a comprehensive overview of IoT services to understand their nature to facilitate their description and discovery. This paper fills this gap by performing a full comparison study of multi-category and recent approaches for service discovery in the IoT over many aspects and also by performing a comprehensive study of the IoT service features.

This paper seeks to suggest a model for location‐based recommendation services that enable greater access to print and electronic resources.

The paper takes the form of a synthesis of previous work in basic and applied collections‐based wayfinding incorporating library and information science (LIS) literature on user context and system recommendations.

The paper identifies problems that will need to be solved before implementation of the production‐level recommendation service and suggests possible implications the system may have on reference and instruction services.

The paper provides computing workflows necessary to implement a library recommendation service based on user location. iPhone Software Developer Kit templates are leveraged for modeling data and interface prototypes. Use cases and user models are developed.

This paper aims to identify and propose strategies for development of mobile applications from Web-based enterprise systems and introduce a process called Metamorphosis. This process provides a set of activities subdivided into four phases – requirements, design, development and deployment – to assist in the creation of mobile applications from existing Web information systems.

With the aim to provide a background to propose the Metamorphosis process, a systematic review was performed to identify strategies, good practices and experiences reported in the literature about creation of mobile applications.

This paper identifies and proposes strategies for development of mobile applications from Web-based enterprise systems and introduces a process called Metamorphosis. Then, this process is applied for creation of SIGAA Mobile.

The originality of this paper is the proposal of Metamorphosis process, that is, a process for development of mobile applications from Web-based enterprise systems.

The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.