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A large number of web-based e-Health applications have been developed through time, allowing doctors to access different types of functionalities, like knowing which medication the patient has consumed or performing online consultations. Internet systems for healthcare can be improved by using artificial intelligence mechanisms for the process of detecting diseases and obtaining biological data, allowing medical professionals to have important information that facilitates the diagnosis process and the choice of the correct treatment for each particular person. The proposed research work aims to present an innovative approach when compared to traditional platforms, by providing online vital signs in real time and allowing the visualization of all historical data of a patient. It aims to defend the concept of promoting online consultations, providing complementary functionalities to the traditional methods for performing medical diagnoses through the use of software engineering practices. This investigation led to the conclusion that, in the future, many medical processes will most likely be done online, where this practice is considered extremely helpful for the analysis and treatment of contagious diseases, or cases that require constant monitoring. info:eu-repo/semantics/acceptedVersion

The inclusion of a capstone project has become a core component of many software engineering and computing related courses. There is general agreement that a substantial final year project provides an opportunity for students to demonstrate breadth and depth of acquired knowledge alongside industry-oriented skills and independent working. Traditionally, capstone projects are academic-proposed individual projects, in which students work from a project outline with one or more academic supervisors. Although useful to demonstrate the application of knowledge, such projects lack key activities that have been cited as beneficial to student experience and career-readiness, specifically working with others in a team and with external clients. In our study we provided a range of projects for students in a final year, compulsory capstone Software Engineering project module which forms a major requirement of the overall degree. The students were required to select a project which could be individual or team-based and where the origin of the project could be academic-proposed, student-proposed, community-based or industry-supported. Students then completed these projects with a mixture of academic supervision and, where appropriate, input from the community group or industrial partner who had proposed it. After completion, a mixed-method approach was used to evaluate student experience and satisfaction. The initial findings indicate that students who chose a team-based project and specifically those who took projects proposed for a real-world user (community or industry) were more satisfied with their experience and agreed to a greater extent that they had developed new skills. Within this group, those who chose the community projects expressed the highest levels of satisfaction, feeling rewarded that their contribution was to a project for social good. These initial findings validate the beneficial approach of involving external partners such as community groups in team-based capstone projects.

Building shared understanding of requirements is key to ensuring downstream software activities are efficient and effective. Non-functional requirements (NFR), which include performance, availability, and maintainability, are vitally important to overall software quality. Research has shown NFRs are, in practice, poorly defined and difficult to verify, especially in agile environments. Continuous software engineering (CSE) practices, which extend agile practices, emphasize fast paced, automated, and rapid release of software that poses additional challenges to NFRs. However, the level of shared understanding achieved across an organization is not well-understood. This dissertation will build the foundations towards a theory of the complex and intricate relationship between shared understanding of NFRs and CSE.

Improving software performance through configuration parameter tuning is a common activity during software maintenance. Beyond traditional performance metrics like latency, mobile app developers are interested in reducing app energy usage. Some mobile apps have centralized locations for parameter tuning, similar to databases and operating systems, but it is common for mobile apps to have hundreds of parameters scattered around the source code. The correlation between these "deep" parameters and app energy usage is unclear. Researchers have studied the energy effects of deep parameters in specific modules, but we lack a systematic understanding of the energy impact of mobile deep parameters. In this paper we empirically investigate this topic, combining a developer survey with systematic energy measurements. Our motivational survey of 25 Android developers suggests that developers do not understand, and largely ignore, the energy impact of deep parameters. To assess the potential implications of this practice, we propose a deep parameter energy profiling framework that can analyze the energy impact of deep parameters in an app. Our framework identifies deep parameters, mutates them based on our parameter value selection scheme, and performs reliable energy impact analysis. Applying the framework to 16 popular Android apps, we discovered that deep parameter-induced energy inefficiency is rare. We found only 2 out of 1644 deep parameters for which a different value would significantly improve its app's energy efficiency. A detailed analysis found that most deep parameters have either no energy impact, limited energy impact, or an energy impact only under extreme values. Our study suggests that it is generally safe for developers to ignore the energy impact when choosing deep parameter values in mobile apps., Comment: 12 pages, 9 figures, to be published in SANER 2022, camera-ready

With the development of blockchain technology, the fields of use of smart contracts are diversifying. Blockchain-based smart contracts are suitable in areas where integrity and transparency must be guaranteed with distributed ledger technology as the core. However, once the system is deployed, it cannot be modified, so it is important to ensure that the system works with the requirements and principles of the smart contract at the design stage. Therefore, in this paper, we aim to show that the system is accurate without contradictions/errors through formal verification using UPPAAL, a formal verification tool for the public descending auction system (Dutch Auction).

Avionics systems software usually has the characteristics of complex structure, wide function coverage, high reliability, and high safety. These characteristics have led to the increasing scale and complexity of software systems, and the increasing variety of research & development (R&D) personnel. This further intensify the knowledge-intensive trend of software development, and make the software requirements elicitation activities more complicated. In the knowledge engineering community, an ontology is an explicit specification of a conceptualization. This paper uses the ontology method to construct a requirement knowledge framework and requirement knowledge is expressed as a clear, complete, and consistent hierarchical ontology concept and association, which is more conducive to knowledge sharing and reuse as well as reflects multiple viewpoints of stakeholders. This paper builds a requirements knowledge multi-ontology framework which is divided into GO (generalization ontology), TO (task ontology), DO (domain ontology), and AO (application ontology). And it decomposes the GO into structure ontology and action ontology in the framework. It makes up for the deficiency of undifferentiated knowledge representation of the GO. Then, this paper proposes and integrates the concept of software requirement error pattern into the multi-ontology framework in a consistent form. In addition, this paper evaluates the quality of the constructed ontology and the evaluation results show that the constructed ontology in this paper has a high quality. Finally, this paper facilitates the requirements elicitation based on the multi-ontology framework to avoid errors and improve the quality and reliability of software products.

The environments and the goals that an autonomous system needs to be able to understand and act upon are not fully known and clearly identifiable at design time, especially for those systems that interact with the physical world. Still, for applications that require a certain level of assurance, requirements, which include the definition of how a system is supposed to interact with its context, need to be defined, analyzed, refined towards an implementation that can be shown to deliver certain guarantees. We first broadly discuss the importance of the early stages of the design process where requirements are defined, and we then discuss the formalisms needed to capture requirements and refine them towards implementation for autonomous systems.

A Digital Twin of an Organization (DTO) is a mirrored representation of an organization, aiming to improve the business process of the organization by providing a transparent view over the process and automating management actions to deal with existing and potential risks. Unlike wide applications of digital twins to product design and predictive maintenance, no concrete realizations of DTOs for business process improvement have been studied. In this work, we aim to realize DTOs using action-oriented process mining, a collection of techniques to evaluate violations of constraints and produce the required actions. To this end, we suggest a digital twin interface model as a transparent representation of an organization describing the current state of business processes and possible configurations in underlying information systems. By interacting with the representation, process analysts can elicit constraints and actions that will be continuously monitored and triggered by an action engine to improve business processes. We have implemented a web service to support it and evaluated the feasibility of the proposed approach by conducting a case study using an artificial information system supporting an order handling process.

Digitalization of manufacturing is led by the notion of a digital thread, a framework that allows for integrating authoritative and trustable data of a product throughout its lifecycle. Under the model-based enterprise (MBE) vision, digital three-dimensional (3D) model of a product serve as this authoritative source of information across the product lifecycle. A class of systems called knowledge-based engineering (KBE) systems represents the evolution of knowledge-based systems towards designing these models and this study presents a case for using such systems to realize the digital thread in a model-based enterprise. The paper proposes four directions and potential enabling technologies at the disposal of KBE systems for this purpose are identified. Further, a case study that demonstrates such use of a KBE system to realize the digital thread for a manufacturing assembly process is presented. publishedVersion

This work presents a prototype and preliminary evaluation experiments of a management conversational assistant for software engineering teams. Such teams commonly rely on text chat for communications using specialized collaboration platforms such as Slack or Microsoft Teams. A conversational assistant integrated into these platforms can help in several tasks related to project and team management, thus benefiting both managers and software developers. The proposed design of the conversational assistant is described in terms of its architectural design and interaction design, and the important design decisions are explained. Preliminary evaluation shows that the proposed chatbot can be used effectively to interact with users reactively and proactively over public and private channels. However, for better results, a specific intent classifier should be used for each combination of user roles and channel types. In addition, interacting to messages with unspecified target over public channels is affected by the relatively limited intent classifier accuracy and still requires improvement.

Deployment on different platforms has been a great issue for mobile companies that aim to maximize the return on investments by making their mobile applications available on different mobile platforms. Consequently, the app may be developed several times to match different platforms. Therefore, there is a need to have solutions that enable the developers to develop the app once, and run it everywhere to reduce the cost of development and reach out to maximum users across several platforms. In this paper a tool is provided with the most popular languages /frameworks (native, cross platform) based on their market share to select the desired framework among them to code with, get the developed application written in the target language that meets their business requirements, and give the ability to convert native application to cross platform one. A trans-compiler based solution is introduced to convert the UI and UI-related backend code of application from a set of languages to any other language in the set and ability of adding more languages and frameworks in the future to achieve the concept of generalization of code conversion.

Building a one hundred percent robust, error-prone Android application is a hard thing to sustain considering all the assumptions of the foreign environment differences that the developers of the mobile applications must consider. However, there are some known mechanisms that help the developers get a closer step toward making precautions and calculating the assumption of different errors and scenarios to achieve the application robustness, such as the exception handling mechanism- ‘EHM’. EHM is a mandatory step in Java development which indeed is the core of the Android application platform. In this research, we analyzed an Android representative sample of 24 applications that consists of 6 major categories, 4 applications for each. The static analysis was done to the under-test sample applications using a Java exception parser automation tool developed specifically for this research. Our study contributes directly to creating the Java exception parser tool to parse the total source code of the application so that it extracts the exception handling code blocks from it, then to automate its static analysis to indicate the types and classes percentages and types of exception handling mechanisms used in the targeted applications. The overall result that we can conclude is that in general, although error handling techniques was reported to be misused before, by being overly generic and simple handlers aimed to log or are left empty in most of the researchers results that we came across while doing this research, now the android developers of our representative sample at least are moving forward to write a more robust application that can be significant in the competitive new technological world and this is proven by the logic handlers exceptions percentage of 49% of the total LOC from all the 24 analyzed applications. As per our knowledge, this is the first research that aims to study how the programmers use the EHM inside android application development.

The software world is in the midst of a computing paradigm shift, transitioning on-premise software to the efficiency and almost endless scalability offered by cloud solutions. While some simulation models are by design better prepared than others for this transition, relatively little progress has been done on the architectural side of software to fully harness the new possibilities offered by cloud computing. This paper aims to review the various simulation models with emphasis on agent-based ones, highlighting their advantages and present a short review of state-of-art software implementing those models. Finally, this paper will focus on an innovative way of applying an agent-based model to a variety of emergency simulations, while showcasing a lightweight and flexible software architecture capable of distributing workload in a cloud-based environment.

With the development of cloud computing, the advantages of micro service architecture have gradually made it a software architecture commonly adopted by cloud service providers, and it is being used by more and more people. However, the loose coupling characteristics of micro services also determine the characteristics of its multiple service interfaces and intricate application problems. Therefore, higher requirements are put forward for the testing of micro service applications. Based on the basic framework of automated testing of micro service applications, this paper introduces a decision tree algorithm to automatically classify and screen different types of test cases. This method liberates labor costs and improves test efficiency through automated testing. In addition, through the advantages of the decision tree algorithm, comprehensive test cases can be screened, and the effectiveness of the method is verified through experiments.

Fuzz testing is an important means of vulnerability discovery, but now fuzz testing technology is most for application software on traditional computer platforms, which can be not used on embedded software. We propose a fuzzing method for embedded software, which can solve the two technical difficulties: abnormal monitoring and automation. Also, we independent research and develop embedded fuzzy testing tool called Efuzzer. Experiments prove that the tool has very good practicality and is effective for discover buffer overflow vulnerabilities which can cause a system crash. Now the tool is tried in several software testing institutions, a few vulnerabilities were discovered.

With the development of business, there always exists a large demand for application software in electric power industry. From a technical point of view, there has been no revolutionary changes in the technical architecture of such software in recent years. On the other hand, application softwares are required to meet the electric power industry standard like the security standard, and pass the security tests. Theoretically, the above two features make the development works of various electric application softwares have a high similarity. But in the practice, the amount of time and personnel spent on software development does not show a significant decrease. To simplify the development of electric application software and improve the efficiency, in this paper, an approach is introduced. First, the requirements specification of an application and its expression are clarified, with the reusable part in the development work separated out based on softwares’ similarities. Then a general application server is implemented, which can be instantiated with business requirements for various application softwares. At last, we build two application servers to see the effectiveness.

Aiming at the design and evaluation of antimissile early warning and detection plan. The design link of antimissile early warning and detection plan is put forward with the idea of combat planning, the software STK is used to design the anti-missile early warning and detection plan, a scientific evaluation index system is established, and an improved fuzzy analytic hierarchy process model is put forward. Five sets of anti-missile early warning and detection plans are designed for example, and the correctness and rationality of the proposed model are proved by simulation experiments, which provides a new method and way for the evaluation of anti-missile early warning and detection plans.

Integration test is an important security guarantee for high-speed railway operation. Aiming at the problem of chimney construction of more than 20 professional systems, which are scattered and lack of linkage, key technologies such as BIM+GIS multi-source heterogeneous data fusion, dynamic loading and rendering and lightweight model are put forward, and the virtual-reality mapping and interaction in physical railway and virtual twin railway scenes are realized based on "One Screen, One Picture" in BIM+GIS vehicle-mounted integration platform. The platform further explores the data value, and provides reference and guidance for lossless transmission of full life circle data of multi-professional and multi-participant railway based on BIM+GIS model, collaborative linkage, visual expression, immersive experience and intelligent decision-making, and further improves the intelligent management level of overall research and judgment of integration test, collaborative command and scientific decision-making and promotes the development of intelligent joint debugging.

In order to adapt to the rapid iteration of business applications brought about by the construction of power grids, it is necessary to establish an information system DevOps system that adapts to the characteristics of the company, standardize R&D standards, and build an automated tool chain covering the entire process, shorten the cycle from R&D to production deployment, and deploy at high frequency Ensure the reliability, stability and safety of the production environment, and realize the automation, digitization and visualization of the whole process. From a business perspective, break through the barriers of business, development, testing, and operation and maintenance teams, realize the accurate transmission of information in each link, formulate unified research and development standards, establish continuous integration, continuous delivery, and continuous deployment mechanisms to achieve the shortest time from demand to rapid Deliver product prototypes, then pass tests and collect user feedback, quickly iterate, and continuously revise products to meet business needs.

Today’s mechatronic systems are becoming more and more complex as the development and design processes require collaboration across multiple engineering disciplines. The high complexity between loosely connected models results in a disconnect between these inter-disciplinary models, which may cause delays and costly rework in the long run. There is a need for an effective method to show the dependencies and risks across models for various stakeholder groups. Currently, the discussion about such methods is limited. This paper proposes and evaluates a user-friendly Decision Graph and Matrix Visualization method that combines network-based and matrix-based techniques to assist stakeholders in tracking dependencies and risks across models. The method is applied and demonstrated with a design and engineering case of a lab-scale production system, whose usability was tested formatively with experts.

As an important part of Industry 4.0, industrial software development must be highly flexible and reconfigurable to deal with a large number of requirements and random failures during the manufacturing process. Requirements understanding errors that occur in the early stages of software development often cannot be discovered prior to the testing phase. Therefore, the analysis and understanding of requirements are particularly crucial in the software development process. In this paper, a knowledge-driven functional-oriented requirements elicitation and analysis method are proposed to extract both functional and non-functional requirements from design documents. Nonfunctional requirements which are implicit in the documents will be elicited according to the domain knowledge graphs and predefined rules. A domain glossary is also constructed for the elicitation process, especially from unstructured sources. Domain knowledge graphs are modified periodically according to the feedback information to form a closed loop from requirements to code. The feasibility of the proposed method is demonstrated under an automobile welding line.

Publisher Copyright: © 2021 IEEE. The need of manufacturing industries to adapt to the demand from customers and the volatile market drives the need for digitalization to realize the so-called smart factory. Smart factory, Compared to traditional factories, smart factory needs to possess high flexibility and stability and often has to employ digital twin. Compared to IEC 61131-3 standard used in traditional industrial production, IEC 61499 standard can bring more advantages to meet the realization of Smart Factory, such as flexibility, distribution and event-driven execution. In this paper, we propose a new Virtual Commissioning (VC) architecture for IEC 61499-based control applications. We build an online collaborative VC platform with the help of cloud computing and containerization technologies. Furthermore, we discuss and propose the utilization of soft-PLC containers from different vendors to meet users' commissioning requirements for different hardware configurations. Compared with the traditional offline single-person debugging method,our proposed architecture can improve the flexibility, collaboration and efficiency of control software debugging in a more interactive and collaborative style via the online platform we implemented.

The use of ontologies for models of machines and their capabilities and skills provides advantages for manufacturers that want to quickly adapt to changing customer requirements or fluctuating demands. Unfortunately, creating such models requires a high level of expertise in semantic technologies. In typical automation engineering workflows, there is neither the personnel nor the time to create such models manually.In this contribution, we describe an approach to automatically create skill models from IEC 61131-3 code. This approach consists of a dedicated PLC programming library and an automatic transformation of PLC code to a skill ontology. After implementing a skill as a PLC program using the presented library, this program can be exported as PLCopen XML which in turn is automatically transformed into an ontology. Additional efforts for PLC developers are thereby kept at a minimum. The presented approach has been evaluated using a modular laboratory plant. For two different modules, skills were implemented on separate PLCs. After transforming these skills to our skill ontology, this ontology was used to register the skills at a skill-based control platform. Using this platform, the skills were used together in order to perform one section of a production process.

In this article, we will focus on creating a Domain-Specific Language (DSL) that can be used to streamline the demanding process of creating security documentation for classified systems. The article is mainly focused on the work of the language designer, so you will not find a detailed description of the domain for which the language is designed. More importantly, the article provides an example of the possible use of our DSL.

Formal verification by means of model checking avails in discovering design issues of safety systems at the early stages. However, a significant amount of time and effort is required to decipher its results and localize the failure, especially in complex logic. This work continues our previous study on the visual explanation of failure traces and introduces change-based causes. Additionally, inspired by the types of properties that revealed model failures in projects of VTT in the Finnish nuclear industry, we define a new form of explanation – a hybrid influence graph. The new approach was implemented in a tool called Oeritte and evaluated using two practical examples of failures in nuclear instrumentation and control systems.

This article describes the architecture of a Blockchain subsystem to manage access through Digital Identity to the Electronic Medical Record of patients. During this work, the agile programming methodology focused on Blockchain by Marchesi et al. [1], was followed. Therefore, the development of the work was divided into a section for the programming of the Blockchain network and another section for the development of the part of user interfaces. The Hyperledger Fabric framework was used to set up the Blockchain network due to its focus on Digital Identity management. In addition, the graphical interface in React was developed to allow communication with users. The whole development had a modular approach, where three modules are worked in both sections of the project: Identity Management, Authority, and Consortium of Health Service Providers. This architecture has managed to be developed and its process and functioning are presented in this work.

The collaborative approach which are born OER (Open Educational Resource) is the joint search for pedagogical and technological challenges to achieve improved quality reconstruction. It is necessary to demonstrate defined metrics that support processes and provide guidelines or instructions related to design for all. The open feature of the OERs must demonstrate accessibility, guaranteeing their interoperability. The incorporation of intelligent systems based on the efficient publication of accessibility information, contributes to the evaluation of accessible resources, knowledge modeling and future trends based on the feedback of profiles, and personalization from the user experience through. This paper presents the proposal for an expert system based on the ISO 40500, ISO 24751 and UDL standards.

Developer productivity is a highly valued research topic for academics and industry professionals alike. Reducing the amount of time spent on tasks like foraging for information, navigating code, and debugging can provide substantial benefits to developers of all skill levels. There are many works that explore this topic in-depth (e.g., [1]–[3]). One of these studies, for example, showed that 50% of programmers' time was spent searching for information [2]. Additionally, there are numerous tools that have been built to address these pain points and boost software developer productivity. These tools often provide improved code editor interfaces (e.g., Patchworks [4]) or debugging tools for high-level languages (e.g., Gzoltar [5]).

Linear programming is a mathematical optimization technique used in numerous fields including mathematics, economics, and computer science, with numerous industrial contexts, including solving optimization problems such as planning routes, allocating resources, and creating schedules. As a result of its wide breadth of applications, a considerable amount of its user base is lacking in terms of programming knowledge and experience and thus often resorts to using graphical software such as Microsoft Excel. However, despite its popularity amongst less technical users, the methodologies used by these tools are often ad-hoc and prone to errors. To counteract this problem we propose creating a block-based language that allows users to create linear programming models using data contained inside spreadsheets. This language will guide the users to write syntactically and semantically correct programs and thus aid them in a way that current languages do not.

Code smells are indicators of some design flaws in the software code. The evolutionary property of an object-oriented software product increases the number of code smells with every release of a version of the product. These code smells like to hamper the quality of the software system. During software maintenance, it becomes cost and effort-intensive to eliminate such a large number of smells due to time and budget constraints. This demands the prioritization of code smells where the developers are with top severe smells to save time and effort. Before proposing any prioritization approach, it becomes important to Figure out the need for code smell elimination using different refactoring activities. Following this, it is imperative to understand the role of different relevant elements in code smell prioritization. To address this need, this paper highlights the drawbacks of code smells as well as provides an overview of several prioritization-related elements such as factors, subject programs, performance metrics, and detection tools. This would help the researchers in getting a preliminary understanding of various parameters that are crucial for proposing and validating code smell prioritization approaches.

The paper deals with an implementation concept for the architecture model of CPS-based automation. Based on the key issues of execution environment, data interface, device and service components, a decentralized and flexible concept is proposed in which any web browser as a “rich” client plays an essential role in the execution of automation functions. Evaluation results are discussed using an example solution for a processing station, designed via an IoT portal.

In this paper, a Graphical User Interface (GUI) is designed and developed using Python programming language for detection of forest fires at early stages, which is efficient, cost-effective, flexible, secure and uses open-source technologies. The user-friendly Graphical User Interface is interfaced directly with the computer port to fetch the data with the help of Python modules, performs an analysis on the data and predict whether there is a situation of fire or not and displays the status on the Graphical User Interface. Data is also stored in an Excel file for further analysis. The possibility to detect forest fire situation at its early stages makes this GUI a valuable software in environmental disasters and research applications. Numerical results along with future work have been discussed in this paper.

Even experts struggle with the decision which processes should be automated and which not. The best solution these days is the so-called Automation Potential Analyses (APA). However, the APA can just be applied to already existing manual assembly processes. In this work, a new approach was developed to define the automation potential already in the product development process with the help of a 3D CAD model. For this purpose, an expert system was developed, which automatically evaluates the automation potentials by accessing the CAD system SolidWorks and using evaluation criteria of the already existing APA of the Fraunhofer IPA.

Software engineering education requires training in project management techniques in combination with intercultural communication skills to cooperate effectively in today's software development landscape. This poses a challenge to teach software engineering effectively in undergraduate courses for industry needs. International engineering study programs provide a unique opportunity to experience a software development process with participants from different cultures. For most students, English is not their native language, which reflects many distributed software engineering projects. This study surveyed 28 students from an international undergraduate engineering course in Japan on their perceived importance of software engineering factors and freeform text comments on their success, struggle, and critique within this course. A language model is trained using Word2Vec on the textual data to support the results of the perceived importance of software engineering factors.

When inquiring about a new computer, the deciding factor is usually which computer is the best for a user's specific needs. It all comes down to the operating system and system specifications and what the computer can and cannot support. It is also important to highlight what features each Operating System must suit the user's specific computing needs. These results will demonstrate the pros and cons of each major Operating System and will provide information that will help the user decide which Operating System fits their criteria the closest.

Modern software is more dominant of software components in the process of software development. Reuse is the primary benefit of a software component improving productivity and decreasing time, cost of implementation. The high demand of reusable software components leads to need of a mechanism to effectively store and retrieve components whenever similar functionality is required. Several researchers have proposed different mechanisms to build these storage spaces of components called as Repositories. This work intends to survey different effective retrieval methods and repositories built earlier. Also, this paper discusses various stochastic and statistical models for code reusability in software engineering. This survey will be a base to develop a user friendly and well-organized repository for retrieval of code components.

User needs inform designers and developers of essential functionalities for requirements engineering. In this work, we summarize key concepts and challenges relating to manual and automatic user needs detection methods. We discuss six challenges with manual and eight challenges with automated methods. Despite the promise of automated methods, the challenges imply that artificial intelligence and machine learning are not yet mature enough to replace manual methods, such as interviews and focus groups, for discovering user needs in requirements engineering.