Search

This study aims to examine research collaboration between universities and industry in the field of computer science using bibliometric methods. To further understand the impact of individual countries on university-industry (UI) collaboration, data were retrieved from the computer science journal papers included in the Science Citation Index and published during the period 2002--2011. The density, degree centrality, betweenness centrality, and closeness centrality of UI collaborative networks were calculated in order to ascertain the core countries involved in international UI collaboration. This study investigates university-industry collaborative papers (UI papers) at the global and country levels. At the global level, the results show an increasing trend in UI papers and a stable UI collaboration ratio during the last decade. The average number of authors for UI papers is 4.13, which is higher than that for all other papers. Most UI papers result from two-institution collaboration, but we observed an increase in the number of UI papers produced by multiple universities and industrial entities. At the country level, the results also show that international UI paper collaboration has intensified. Meanwhile, the USA is the dominant collaborative partner with many countries and has produced the highest number of UI papers globally. [ABSTRACT FROM AUTHOR]

The present study aimed to discover how selected English language authors employ specific rhetorical, grammatical, and stylistic elements in presenting new knowledge to the target audience and how they communicate science to the community of academicians in order to convey scientific information to various audiences. To this end, the generic structures, as well as lexico-grammaticality systems inbuilt in introduction sections of English academic research papers of three different disciplines, linguistics, chemistry and software engineering, were explored. To collect the data, a corpus consisting of 90 papers, 30 for each discipline, published between 2014 and 2016 in Elsevier journals was selected randomly. For genre analysis, Hasan’s model of generic structure potential was used, while Halliday’s model was used for the analysis of lexico-grammaticality systems. The results showed that ‘Previous study’ and ‘Purpose of study’ were the obligatory elements among the 11 types of generic structures. Furthermore, material process, declarative mood, the use of conjunctions in textual theme and circumstantial adjunct were mostly used, while no interpersonal theme was found in the obligatory elements. The findings promise pedagogical implications for novice writers and university students of English language generally, and second language or foreign language writers from different cultures in different fields of study, in particular. [ABSTRACT FROM AUTHOR]

Despite rapid advances, modeling a variety of instructional designs to support variations in teaching and learning during the design of educational technologies is still an open challenge. In this paper, we propose a patterns based approach for the design of educational technologies to address this challenge. This is in contrast with existing literature that focuses either on patterns in education or in software, and not both. The core idea of our approach is to leverage patterns for modeling instructional design knowledge and to connect it with patterns in software architecture. We discuss different categories of patterns in instructional design. We then present the notion of Pattern-Oriented Instructional Design (POID) as a way to model instructional design as a connection of patterns (ProcessPattern, ContentPattern) and integrate it with Pattern-Oriented Software Architecture (POSA) based on fundamental principles in software engineering. We demonstrate our approach through adult literacy case study (287 million learners, 22 Indian Languages and a variety of instructional designs). The results of our approach (both web and mobile versions) are available at http://rice.iiit.ac.in and were transferred to National Literacy Mission Authority of Government of India for further proliferation. [ABSTRACT FROM AUTHOR]

Organizational dependency on Information and Communication Technology (ICT) drives the preparedness challenge to cope with business process disruptions. Business Continuity Management (BCM) encompasses effective planning to enable business functions to resume to an acceptable state of operation within a defined timeframe. This paper presents a systematic literature review that communicates the strategic guidelines to streamline the organizational processes in the BCM program, culminating in the Business Continuity Plan design, according to the organization's maturity. The systematic literature review methodology follows the Evidence-Based Software Engineering protocol assisted by the Parsifal tool, using the EbscoHost, ScienceDirect, and Scopus databases, ranging from 2000 to February 2021. International Standards and Frameworks guide the BCM program implementation, however, there is a gap in communicating metrics and what needs to be measured in the BCM program. The major paper result is the confirmation of the identified gap, through the analysis of the studies that, according to the BCM components, report strategic guidelines to streamline the BCM program. The analysis quantifies and discusses the contribution of the studies on each BCM component to design a framework supported by metrics, that allows assessing the organization's preparedness in each BCM component, focusing on Information Systems and ICT strategies. [ABSTRACT FROM AUTHOR]

Cross-project defect prediction (CPDP) technology can effectively ensure software quality, which plays an important role in software engineering. When encountering a newly developed project with insufficient training data, CPDP can be used to build defect predictors using other projects. However, CPDP does not take into account the prior knowledge of the target items and the class imbalance in the source item data. In this paper, we design an active learning selection algorithm for cross-project defect prediction to alleviate the above problems. First, we use clustering and active learning algorithms to filter and label some representative data from the target items and use these data as prior knowledge to guide the selection of source items. Then, the active learning algorithm is used to filter representative data from the source items. Finally, the balanced cross-item dataset is constructed using the active learning algorithm, and the defect prediction model is built. In this article, we selected 10 open-source projects by using common defect prediction models, active learning algorithms, and common evaluation metrics. The results show that the proposed algorithm can effectively filter the data, solve the class imbalance problem in cross-project data, and improve the defect prediction performance. [ABSTRACT FROM AUTHOR]

The use of robust software engineering processes is essential in the design and development of interactive systems. This ensures that software is both functionally correct and also usable in the required context. There are a variety of software engineering techniques that can be used to consider different aspects of a system under construction, and at different stages in the development process. There is, however, a natural tension between formal approaches (typically used in the domain of safety-critical systems to consider functional correctness) and informal design approaches, which focus on users and user requirements in a manner which is accessible by stakeholders. In this paper we present two new approaches which enable a tighter coupling of informal design requirements with formal models. We present examples of these two approaches and discuss the benefits that transformations between the informal and formal provide. We also discuss the current limitations of such work along with recommendations about how these might be addressed. [ABSTRACT FROM AUTHOR]

Sustainable tourism research focuses on mitigating or remediating environmental, social and economic impacts on tourism. In the past years, Big Data approaches have been applied to the field of tourism allowing for remarkable progress. However, there seems to be little evidence to support that such approaches are an inspiration to sustainable tourism and are being implemented. In this context, we aim to obtain a comprehensive overview of the use of Big Data in sustainable tourism to address various issues and understand how Big Data can support decision-making in such scenarios. To that end, this paper reports on the results of a literature review via a combination of a Systematic Literature Review (SLR) in Software Engineering, and the use of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. In summary, we investigated four facets: (a) sources of big data, (b) approaches, (c) purposes, and (d) contexts of application. The results suggest that the use of various approaches have impacted practices in sustainable tourism. The findings provide a thorough understanding of the state of the art of Big Data application in sustainable tourism and provide valuable insights to foster growth both in terms of research and practice. [ABSTRACT FROM AUTHOR]

This paper introduces a new framework for understanding, modelling and software engineering in construction information activities. The current framework is based on understanding that products are the results of processes, which are performed by actors. Such frameworks are influenced by the available technology. The Internet of today is supporting also other kinds of human activities: communication and social interactions among humans. The construction industry uses them as well but without having a proper understanding of their role. There is a gap in the current framework. In this paper, the relevant theories to specify this gap in terms of what could exist in theory and what is offered by technology are analysed. As a result, a new framework of construction information activities that fills the gap is proposed. The key concepts and relations among them are identified and elaborated within the existing framework. The framework introduces the third major integrative element of the otherwise fragmented construction information activities – the social network – the existing two being the physical building and its digital twin. The framework provides a theoretical and conceptual basis for designing, planning, creating, monitoring and evaluating construction-related online services that include a strong social component and use social media services. [ABSTRACT FROM AUTHOR]

This paper argues that current practice in the Operational Research (OR) discipline needs to tackle management problems from a broader point of view by including a new perspective. While Hard OR is posed as the means to a solution, and Soft OR covers the stakeholder/business perspective, this paper proposes OR Engineering to tackle the model/program perspective. This proposal is substantiated by an empirical study that explored OR history and the rise of "wicked problems" in contrast to Software Engineering (SE) history and the idea of "no silver bullet". The main findings are five areas for future works, intertwined between Soft OR and OR Engineering: agility, documentation of versioning, technical debt, systems testing and architecture. Overall, although the goal may be ambitious, this paper aims to stimulate reflective thinking and promote a novel and different line of action and research among OR and SE practitioners present and future. [ABSTRACT FROM AUTHOR]

Architectural synthesis is a key phase of the conceptual design process. In the constant evolution of complex systems, architects have found it difficult to carry out an exhaustive search of all the feasible architectural solutions for a set of given requirements. This paper proposes a computational synthesis framework that automatically generates, from a set of formatted requirements and a sub-systems database, all architectures that are requirement consistent, minimalist regarding the number of components and non-redundant. The resolution principles are based on graph theory representations and Constraint Programming solving techniques. Key features of the framework and an application example are also detailed. Abbreviations: AO: architectural object; BPMN: business process model and notation; CSP: constraint satisfaction problem; DSM: design structure matrix; SE: systems engineering. [ABSTRACT FROM AUTHOR]

Collaboration Engineering (CE) is an approach for the design and deployment of repeatable collaborative work practices that can be executed by domain experts without the ongoing support of external collaboration professionals. Since 2001, CE has been an active and productive topic of research that has attracted scientists from different backgrounds and disciplines. CE research started with studies on ways to transfer professional collaboration expertise to novices using a pattern language called thinkLets. Subsequent research focused on the development of theories to explain key phenomena, the development of a structured design methodology, training methods, technology support, design theories, and various field and experimental studies focusing on specific aspects of the CE approach. This paper details the contributions from CE research and practice based on a literature assessment of 331 publications. It extracts the key insights from the body of CE research thus far, identifies significant areas of inquiry that have not yet been explored, and looks ahead at the CE research opportunities that are emerging as our society, organizations, technologies, and the nature of collaboration evolve. [ABSTRACT FROM AUTHOR]

Transactional memory (TM) is being viewed by researchers as a suitable mechanism to perform shared-memory synchronization on upcoming many-core systems. This paper provides an introductory material on TM, followed by a background of important historical work on synchronization leading to current TM research. The paper reviews recent pure hardware and hardware-software TM design proposals, and finally brings out a list of interesting open problems in this field. [ABSTRACT FROM AUTHOR]

First, I thank Dr. Jensen for a paper that provides a great overview of the various disciplines that involve analysis of data, and which stimulated much discussion at the 2019 Stu Hunter conference. Because modeling and analysis is almost always an iterative process, version control systems are useful for managing analytics workflows, even beyond the Statistical or Machine Learning Engineering domains, and are commonly used by many industry analytics teams. Extensions to the commonly used version-control system git, such as git-annex ([4]) and Data Version Control (DVC [1]) (Open-source version control system) have been developed to try and address these issues. [Extracted from the article]

This paper contributes to rapid prototyping for Aboleth, a mobile application designed as a virtual character sheet for Dungeons and Dragons 5th edition. We propose augmenting an API framework, including details of the general design process and crucial details regarding the specific implementation of the project. The prototype is developed using Computer-Assisted Designs and Xamarin. Software engineering is integrated into game design to improve Human-Computer Interaction and eventually enhance user experiences. Additionally, we discuss the relevance of using such a tool to achieve rapid prototyping for enterprise mobile applications and Metaverse and explore opportunities to improve the project design. [ABSTRACT FROM AUTHOR]

Learning from success projects to build business process for customer requirements change is critical successful factor for other project in IoT enterprise systems. We proposed an ontology-based technology to mine the core knowledge of successful projects. From precious experiences of each successful projects, two ways of ontology-based domain knowledge pattern will be defined, first is for application project management, and second is for software engineering process. To decompose the project knowledge from the same application domain with tree structures. The results of this paper reduce development and requirement cost, and user satifaction is better than without ontology. [ABSTRACT FROM AUTHOR]

This section introduces a series of articles on software engineering.

The paper presents results of ongoing research to support effective user involvement during systems development projects. The Collaborative Software Engineering Methodology is presented as a framework that contains mechanisms to support three layers of user involvement: selected user representatives, user groups, and the broader user community. Productivity and user participation of traditional group meetings have been limited by chauffeured facilitation and by support of single-user tools designed for analysts rather than users. The paper introduces electronic meeting systems (EMS) modeling tools designed to allow users to work in parallel to contribute directly during meetings. These tools are easy to use while containing support features traditionally associated with CASE tools. The methodology includes a sequence of requirements abstractions that users engage directly including activity models, data models, scenarios, system use eases, and prototypes. This methodology is designed to help organizations respond to today's rapidly changing information processing needs. [ABSTRACT FROM AUTHOR]

Object-oriented analysis (OOA) has become a popular method for analyzing system requirements. Unfortunately, however, none of the current versions of OOA has included a validation technique tailored to the object-oriented approach. Most, instead, merely recommend document reviews without specifying the kinds of problems to look for. This paper explores the question by applying a natural language parser to a requirements document, extracting candidate objects, methods, and associations, composing them into an object model diagram, and then comparing the results with those determined by manual OOA. To do this, we have adapted an automated natural language parser and used it to examine several high-level system descriptions. The results indicate that, with a modest amount of effort, the technique can give valuable feedback to the analyst. [ABSTRACT FROM AUTHOR]

Information technology (IT) projects can fail for any number of reasons, and can result in considerable financial losses for the organizations that undertake them. One pattern of failure that has been observed but seldom studied is the runaway project that takes on a life of its own. Such projects exhibit characteristics that are consistent with the broader phenomenon known as escalating commitment to a failing course of action. Several theories have been offered to explain this phenomenon, including self-justification theory and the so-called sunk cost effect which can be explained by prospect theory. This paper discusses the results of a series of experiments designed to test whether the phenomenon of escalating commitment could be observed in an IT context. Multiple experiments conducted within and across cultures suggest that a high level of sunk cost may influence decision makers to escalate their commitment to an IT project. In addition to discussing this and other findings from an ongoing stream of research, the paper focuses on the challenges faced in carrying out the experiments. [ABSTRACT FROM AUTHOR]

Existing output measurement metrics for cost estimation and development productivity need to be reexamined to determine their performance in computer-aided software engineering (CASE) development environments. This paper critiques and empirically evaluates four approaches to the measurement of outputs. Two of the metrics, raw function counts and function points, are based on the function point analysis methodology pioneered by Albrecht and Gaffney at IBM. The second two, object counts and object points, are based on a new approach—object points analysis—that is introduced here for the first time. The latter metrics are specialized for output measurement in object-based CASE environments that include a centralized object repository. Estimation results for nineteen large-scale CASE projects show that the new metrics have the potential to yield equally accurate, yet easier to obtain estimates than function points-based measures. [ABSTRACT FROM AUTHOR]

This paper describes the results of a survey of members of the American Association for Artificial Intelligence (knowledge engineers) concerning their individual need for growth and their perceptions about their work environment. Responses are compared to those of software engineers whose qualifications are similar to those of knowledge engineers. Comparisons are made on 16 variables. The analysis shows that personnel in the two job categories are quite similar; both have quite high need for growth and therefore need jobs rich in the factors key to motivation. The survey also identified several problems that managers in the artificial intelligence (AI) area need to resolve. [ABSTRACT FROM AUTHOR]

A test case is a cornerstone of the testing process; hence, it is quintessential to ensure the quality of the test cases. However, test case design in the Agile testing process has limitations that affect its quality standards, leading to the failure of many software projects. Previous studies are limited in providing a clear guideline for assessing the test case quality. However, evaluating the quality of test cases will help software testing practitioners to understand some critical issues in designing test cases from various perspectives. Therefore, this paper aims to present the verified factors and criteria of test case quality by software testing experts in an Agile environment. The proposed factors and criteria were verified through expert review techniques, which included an online survey of professionals and those in domain and knowledge experts. Twenty-three industry practitioners, including developers, testers, and systems analysts, were used to identify the domain experts. In contrast, the knowledge experts were drawn from 13 academic areas of software engineering and testing. The results showed that the quality of test cases is paramount in Agile projects; therefore, the experts accept seven factors and 32 criteria with a few mod- ifications and suggestions. The finding may assist the researchers in improving the proposed factors and criteria for validation purposes. Hence, may contribute to soft- ware testing practitioners as a guideline in constructing, designing, and assessing compelling test cases. Most significantly, the fixed factors and criteria may contribute to the body of knowledge in the software testing domain and industries. [ABSTRACT FROM AUTHOR]

During the last decade, Unmanned Aerial Vehicles (UAVs) gained wide attention and are integrated into diverse systems and deployed into many contexts. The need to assess the UAVs' performances, impacts of applications, routing protocols, mobility as well as other features in a network is necessary. However, conducting real experiments within UAV-based systems and particularly with multi-UAV-based systems can be extremely costly and complex. To fill this gap simulators, emulators, and frameworks are used to evaluate the performance and viability of UAV-based systems with lower cost and in a short period. Accordingly, researchers and software engineers developed several simulators and co-simulators dedicated to the performance evaluations of UAV-based systems. In this regard, this investigation highlights and identifies the most suitable simulators, co-simulators, emulators, and frameworks for UAV flights and management. Both the tools dedicated to mono-UAV-based systems and the tools dedicated to multi-UAV-based systems are pinpointed. In this paper, the goals, the requirements, the strengths, and the limitations of each studied tool are detailed. Besides that, a UAV simulators catalog is provided. It includes guidelines that will be useful for researchers and help them to identify and to select the adequate tools for UAVs performance analysis that meet their needs. [ABSTRACT FROM AUTHOR]

The Journal of Spatial Science has announced the winner of the Best Research Paper award for 2023. The winning paper is titled "Road edge detection based on combined deep learning and spatial statistics of LiDAR data" and was authored by Dragan D. Kukolj, Igor Marinovic, and Sandra D. Nemet. Dragan D. Kukolj is a full professor at the University of Novi Sad and has expertise in machine learning and image processing. Igor Marinovic is the CEO of Manufaktura Ltd and specializes in geographic information systems and AI applications. Sandra D. Nemet works at OBLO Living Ltd and focuses on software engineering and AI development. The authors have published numerous papers in their respective fields. [Extracted from the article]

The presence of defect data related to different projects leads to cross-project defect prediction an open issue in the field of research in software engineering. In cross-project defect prediction, the source and the target projects are different. The prediction model is trained by using the data sources of the different projects and then it is tested on the target data source. The data source from the varying projects leads to a highly imbalanced source dataset. The performance of the predictive model degrades due to this imbalance nature of the dataset. This is termed as the class imbalance problem in machine learning. This paper conducts an empirical analysis in a bi-fold manner. It evaluates whether data sampling techniques can handle the class imbalance problem and improve the performance of the predictive model for cross-project defect prediction (CPDP). Secondly, it also evaluates whether the results of CPDP after data sampling are comparable to within project defect prediction (WPDP). Ensemble learning classifiers are used as the predictive model over 12 publically available object-oriented project datasets. The experimental results infer that SMOTE oversampling can be applied to overcome the problem of class imbalance on CPDP. It also gives comparable results to WPDP with statistical significance. [ABSTRACT FROM AUTHOR]

Test-suite minimization problem is an essential problem in software engineering as its application helps to improve the software quality. This paper proposes a quantum algorithm to solve the test-suite minimization problem with high probability in O 2 n , where n is the number of test cases. It generates an incomplete superposition to find the best solution. It also handles the non-uniform amplitudes' distribution case for the system with multisolutions. The proposed algorithm uses amplitude amplification techniques to search for the minimum number of test cases required to test all the requirements. The proposed algorithm employs two quantum search algorithms, Younes et al. algorithm for quantum searching via entanglement and partial diffusion to prepare incomplete superpositions that represent different search spaces such that the number of test cases is incremented in each search space, and updated Arima's algorithm to handle the multisolutions case. The updated Arima's algorithm searches for a quantum state that satisfies an oracle that represent the instance of the test-suite minimization problem. [ABSTRACT FROM AUTHOR]

Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with complex datasets and producing analyses for multiple audiences. But, we argue, statisticians are now often called upon to develop statistical software, not just analyses, such as R packages implementing new analysis methods or machine learning systems integrated into commercial products. This demands different skills. We describe a graduate course that we developed to meet this need by focusing on four themes: programming practices, software design, important algorithms and data structures, and essential tools and methods. Through code review and revision, and a semester-long software project, students practice all the skills of software engineering. The course allows students to expand their understanding of computing as applied to statistical problems while building expertise in the kind of software development that is increasingly the province of the working statistician. We see this as a model for the future evolution of the computing curriculum in statistics and data science. [ABSTRACT FROM AUTHOR]

Organisational learning is an area that aids organisations in improving their processes by reusing experience so that knowledge is accessible to the entire organisation. However, it is not a trivial task to bring about such learning in software development companies, especially as this is an area where processes and knowledge are often internalised in the minds of employees. Some approaches presented in the literature to facilitate organisational learning aim at transforming content generated within companies with Web 2.0 collaborative tools in courses. These courses are based on learning schema that describes their structure and content. However, the creation of these schemes requires a specialist who knows the company's needs as well as the pedagogical organisation's learning requirements. In order to facilitate learning and minimise dependence on specialists, this paper presents an approach that aims to aid companies in identifying developers' learning needs while creating learning schema in a semiautomatic way. Based on the approach proposed, an environment was implemented and an experimental study was conducted to evaluate the identification of relevant issues to the organisation and development of courses. Results suggest that this approach is feasible for discovering themes and creating in-company courses. [ABSTRACT FROM AUTHOR]

Computer game development has been shown to be an effective hook for motivating students to learn both introductory and advanced computer science topics. While games can be made from scratch, to simplify the programming required game development often uses game engines that handle complicated or frequently used components of the game. These game engines present the opportunity to strengthen programming skills and expose students to a range of fundamental computer science topics. While educational efforts have been effective in using game engines to improve computer science education, there have been no published papers describing and evaluating students building a game engine from scratch as part of their course work. This paper presents the Dragonfly-approach in which students build a fully functional game engine from scratch and make a game using their engine as part of a junior-level course. Details on the programming projects are presented, as well as an evaluation of the results from two offerings that used Dragonfly. Student performance on the projects as well as student assessments demonstrates the efficacy of having students build a game engine from scratch in strengthening their programming skills. [ABSTRACT FROM AUTHOR]

Ubiquitous computing technology has been rapidly advanced and applied to diverse domains. This paper proposes a new approach, called CAUSE (Computer-Aided Ubiquitous System Engineering), for implementing ubiquitous manufacturing systems. This method has great potential compared with the conventional ones that rely on physical implementation and human experience through trial-and-error correction. Specifically, this paper develops a framework for the software supporting the ubiquitous system engineering based on requirement analysis, functional details, and implementation issues including enabling technology. The usefulness of the proposed method is shown by developing a prototype system for a ubiquitous manufacturing system with radio frequency identification (RFID). [ABSTRACT FROM AUTHOR]

This paper describes a French research project to co-design an early literacy/early numeracy tablet app for kindergarten students. In order to create an app that takes into account classroom/teaching constraints and the results of recent research, we adopted a theoretical co-design framework and followed a methodology involving researchers, education professionals and software engineers. We describe the design process and the app's educational content, together with the results of an initial trial of the app on a small sample of preschoolers, which showed that it is ready for larger scale testing. We conclude by discussing the specificities of our project and its contribution to the literature on the development of classroom apps for preschoolers. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Software Engineering are considered as significant fields to solve various problems. However, there are weaknesses in certain problem-solving in each field. Thus, this paper is a broad-based review of using artificial intelligence (AI) to improve software engineering (SE), and vice versa. As well as it intends to review the techniques developed in artificial intelligence from the standpoint of their application in software engineering. The aim of this review is highlighted in how the previous study benefited from incorporating the advantages of both fields. The researchers and practitioners on AI and SE belong to a wide range of audiences from the domains of optimization, engineering, data mining, clustering, etc., who will benefit from this study and areas for potential future research. [ABSTRACT FROM AUTHOR]

Although very important for analysis of drying processes, physics-based models are limited in terms of their prediction ability and in most cases are unsuitable for real-time process control and optimization of industrial drying. In this paper, we provide an overview of the machine learning (ML) techniques and the state-of-the-art ML applications in drying of food and biomaterials. The applications include but not limited to data-driven models, nonlinear control and multi-objective optimization. The advantages of integration of ML with machine vision for real-time observation of product quality and fine-tuning control strategies are briefly discussed. Future research should focus on the integration of ML software tools with sensors to measure process and product variables. In addition, the drying research community should contribute towards building of open-source datasets, which is extremely important to leverage the power of ML algorithms. Integration of sensors, process analysis and software engineering will enable the development of "intelligent" drying systems. [ABSTRACT FROM AUTHOR]

The digital transformation taking place in all areas of life has led to a massive increase in digital data – in particular, related to the places where and the ways how we live. To facilitate an exploration of the new opportunities arising from this development the Urban Thematic Exploitation Platform (U-TEP) has been set-up. This enabling instrument represents a virtual environment that combines open access to multi-source data repositories with dedicated data processing, analysis and visualisation functionalities. Moreover, it includes mechanisms for the development and sharing of technology and knowledge. After an introduction of the underlying methodical concept, this paper introduces four selected use cases that were carried out on the basis of U-TEP: two technology-driven applications implemented by users from the remote sensing and software engineering community (generation of cloud-free mosaics, processing of drone data) and two examples related to concrete use scenarios defined by planners and decision makers (data analytics related to global urbanization, monitoring of regional land-use dynamics). The experiences from U-TEP's pre-operations phase show that the system can effectively support the derivation of new data, facts and empirical evidence that helps scientists and decision-makers to implement improved strategies for sustainable urban development. [ABSTRACT FROM AUTHOR]

This paper presents a new approach, model theory approach, to small and medium scale transaction processing system (TPS) development. A TPS of this paper is an information system designed to process day-to-day business event data at operational level of an organization. The paper is not concerned with data base construction but with transaction processing. The model theory approach is not a software engineering approach but a systems theory approach. In the approach a model of the target system, which is called a user model, is constructed in set theory using a formal system structure of a TPS. The user model is, then, compiled into an extended Prolog (extProlog) model. The extProlog is an extension of Prolog to meet requirements for management information system development. On compilation a standardized user interface (UI) called internal UI is attached. The extProlog model with the internal UI is, then, executed under control of another standardized UI called an external UI. Implementation is an integral part of the approach. Because the UIs are designed for the formalized (abstract) structure of a TPS, they can be standardized and are provided as black box components to system development. Because a systems developer is required to only build a user model in set theory based on a model theoretic structure in the approach, it is called a model theory approach. Advantages of this approach are that it provides a theoretical structure to information systems development so that systems development can be made an engineering discipline, and facilitates rapid systems development. [ABSTRACT FROM AUTHOR]

Formal verification is an important means of tackling behavioural problems such as deadlocks in multi-agent systems. This paper is concerned with the role played by formal verification in the simulation-based performance analysis of multi-agent manufacturing systems. A discrete-event simulation case study is presented to show how varying certain timing parameters of the agent negotiation protocol affects the performance of a multi-agent manufacturing system as well as the chance of getting deadlocks among the software agents. When one tries to determine the optimal values of these timing parameters based on the simulation results, formal verification can help refine the results by confirming whether deadlocks among software agents are indeed possible for particular parameter values. This involves modelling the system's real-time behaviour according to the simulation model and applying the techniques and tools of model checking. [ABSTRACT FROM AUTHOR]

The manuscript reports on the latest advancements in the field of multi-agent based industrial control systems. It is declared that this area is becoming strongly influenced by the recent massive proliferation of semantic technologies in various fields of software engineering. The application of ontologies for expressing semantics of data does not restrict any longer exclusively on semantic web or semantic web services. Ontologies are being applied for advanced handling, exchanging and reasoning about knowledge in the area of industrial automation, especially in the case of production systems based on multi-agent technology. The paper provides a comprehensive survey of the application of ontologies in agent-based control systems and discusses the common characteristics of such integration. The generic ontology designed for discrete manufacturing, which covers ordering, production planning and material handling aspects is presented. In addition, the framework for integration of this ontology in distributed, agent-based control solutions is given. A proof-of-concept demonstrating the advantages and drawbacks of such integration in a real manufacturing scenario is provided. [ABSTRACT FROM AUTHOR]

The use of ontologies for knowledge sharing and distributed collaboration has been widely recognised in the knowledge modelling community, but the lack of a systematic and constructive methodology for developing manufacturing ontologies has impeded their wide usage for knowledge reuse in distributed manufacturing environments. This paper presents a constructive, two-level knowledge modelling approach to systematically develop manufacturing ontologies using both software engineering and Semantic Web paradigms. The UML/OCL (Unified Modeling Language/Object Constraint Language)-based object modelling is used first to serve as a graphical and structured basis for conceptual communication between domain experts and knowledge engineers. The OWL/SWRL (Web Ontology Language/Semantic Web Rule Language)-based ontology modelling then extends the UML/OCL-based object models with added semantics using a progressive, semantics-oriented knowledge acquisition method. An illustrative example for manufacturing ontology development in the manufacturing industry for producing electronic connectors is used to demonstrate the practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

This study is concerned with an integrated approach to the management of change. The approach described combines a process improvement approach derived from the Capability Maturity Model with a model of competency derived from Benner's work in health care. The paper describes the original models and how they have been adapted for use. It then describes how they have been integrated and encapsulated within a software tool. A case study application is described together with some of the initial findings from its deployment. The paper concludes with some comments about future developments. [ABSTRACT FROM AUTHOR]

Students in two offerings of a software engineering course were asked to write opinion papers regarding the use of Extreme Programming (XP) in an undergraduate computer science curriculum. The majority opposed the use of XP as the preferred life-cycle model for the project in that course, but they did support introducing some of the practices of XP in selected courses. They felt that unit testing and coding standards should become part of the introductory programming courses, but other practices should be deferred to specific project-oriented courses, or not introduced at all. Two pilot studies provided additional insights that are consistent with the students' opinions. [ABSTRACT FROM AUTHOR]

The development and maintenance of semantic web (SW) means that collaborative manufacturing systems are faced with increasing challenges caused by the growing difficulty in managing distributed manufacturing knowledge. This paper presents a multi-perspective modelling approach to systematically manage distributed manufacturing knowledge on the SW. Considering knowledge engineering as a cyclic and constructive modelling process, a multi-perspective knowledge modelling process is proposed to evolve along knowledge elicitation, engineering modelling, UML-based object modelling, OWL-based ontology modelling, knowledge formalisation and OWL-QL assisted knowledge verification activities. The proposed approach is viewed as a promising knowledge management method that facilitates the implementation of computer supported cooperative work (CSCW) in distributed manufacturing for SW applications by integrating the industrial, UML enabled software engineering techniques into recent ontology-based knowledge engineering process. The feasibility of knowledge management through multi-perspective modelling is manifested using the manufacturing ontology for manufacturing electronic connectors. [ABSTRACT FROM AUTHOR]

Many software reliability growth models (SRGMs) based on a non-homogenous Poisson process (NHPP) have been developed with the assumption of a constant fault detection rate (FDR) and a fault detection process dependent only on the residual fault content. In this paper we develop a SRGM based on NHPP using a different approach for model development. Here, the fault detection process is dependent not only on the residual fault content, but also on the testing time. It incorporates a realistic situation encountered in software development where the fault detection rate is not constant over the entire testing process, but changes due to variations in resource allocation, defect density, running environment and testing strategy (called the change-point). Here, the FDR is defined as a function of testing time. The proposed model also incorporates the testing effort with the change-point concept which is useful in solving the problems of runaway software projects and provides the testing effort control technique and flexibility to project managers to obtain the desired reliability level. It utilizes failure data collected from software development projects to show its applicability and effectiveness. The statistical package for social sciences (SPSS) based on the least-squares method has been used to estimate unknown parameters. The mean squared error (MSE), relative predictive error (RPE), average mean squared error (AMSE) and the average relative predictive error (ARPE) have been used to validate the model. It is observed that the proposed model results are accurate, highly predictive and incorporate industrial software project concepts. [ABSTRACT FROM AUTHOR]

Abstract. A number of authors and multi-national organizations have suggested that providing information services, and in particular software engineering and programming services, for export afford an important economic opportunity for poor countries. Throughout the world, developing countries have acted on this advice. This paper will argue that the opport unities for software engineering services in particular are limited, at least for small developing economies. The main argument is that software engineering and programming are labor-intensive activities and that small developing countries simply do not have the required resources to acquire or train a sufficient number of software engineers and programmers. Any development policy that blindly follows the tenet that small developing countries can improve their economic position through the provision of information services for export is therefore bound to fail. Hence, more sophisticated policies are called for. This paper will also examine a number of such policy options, including an innovative human resource development policy being developed in Jamaica. [ABSTRACT FROM AUTHOR]

Today's manufacturing companies have strived to develop a large variety of customer-specified products in an effort to survive and stay competitive. Process platforms have been well recognized as a means for companies to obtain a stable production and thus the economy of scale. A process platform assists companies in configuring similar production processes for producing families of customized products at low costs through managing product and process variety coherently. Within a process platform, all data related to the product and process families are unified as a common generic structure. To shed light on the various constituent elements and complex relationships inherent in a process platform, this paper emphasizes the structural representation of a process platform. A formalism of process platform representation is developed based on the Unified Modelling Language. It consists of a generic product structure, a generic process structure and an integrated generic routing structure. Also reported is a case study of vibration motors for hand phones. [ABSTRACT FROM AUTHOR]

High electricity and water expenditure constitute a significant issue, as recent statistics demonstrate the continuous increase in energy consumption in the European Union (EU). This results in environmental, financial, and social issues. One such major issue is energy poverty. Software tools can influence users' behavior, enabling them to improve certain situations and enhance their awareness and education around important topics. Such tools must also be usable and offer a positive user experience. In this context, a set of 15 innovative ICT tools were created under the Erasmus+ EU-funded project IDEA: "Innovative Direction in Energy Advising," aiming, on the one hand, to assist individuals in decreasing their households' electricity and water consumption through the development of energy awareness, and on the other hand, to help energy experts in their fight against energy poverty. Our previous work presented an overall brief view of the 15 ICT tools. In this work, we focus on the two core sets of tools. We present (i) the software engineering process we followed toward developing the tools, including a detailed needs analysis and important design and development aspects of the tools, as well as the final product; and (ii) a user evaluation from the perspectives of usability and user experience, during which quantitative and qualitative data were collected and analyzed, followed by a presentation of the analysis conducted and discussion of the results. We concluded that energy experts felt that the IDEA toolkit appears very useful in comparison to what they are currently using. In regards to the wider audience, participants' experience satisfaction (Water Tool (WT) (93%), Lighting Tool (LT) (86%), and Heating Tool (HT) (81%)), and usefulness of the tools (WT (86%), LT (83%), HT (76%)) were highly rated. [ABSTRACT FROM AUTHOR]