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ABSTRACT Context Purpose Method Results Conclusion With the fast advancement of techniques in artificial intelligence (AI) and of the target infrastructures in the last decades, AI software is becoming an undeniable part of software system projects. As in most cases in history, however, development methods and guides follow the advancements in technology with phase differences.With an aim to elicit and integrate available evidence from AI software development practices into a process model, this study synthesizes the contributions of the validation studies reported in scientific literature.We applied a systematic literature review to retrieve, select, and analyze the primary studies. After a comprehensive and rigorous search and scoping review, we identified 82 studies that make various contributions in relation to AI software development practices. To increase the effectiveness of the synthesis and the usefulness of the outcome, for detailed analysis, we selected 14 primary studies (out of 82) that empirically validated their contributions.We carefully reviewed the selected studies that validate proposals on approaches/models, methods/techniques, tasks/phases, lessons learned/best practices, or workflows. We mapped the steps/activities in these proposals with the knowledge areas in SWEBOK, and using the evidence in this mapping and the primary studies, we synthesized a process model that integrates activities, artifacts, and roles for AI‐enabled software system development.To the best of our knowledge, this is the first study that proposes such a process model by eliciting and gathering the contributions of the validation studies in a bottom‐up manner. We expect that the output of this synthesis will be input for further research to validate or improve the process model. [ABSTRACT FROM AUTHOR]

Changes in flow rates in pressurized pipeline systems, due to power loss in a pump, opening or closing of a valve, load rejection by a turbine, etc., may lead to unsteady conditions called fluid transients or water hammer in the pipeline, which, in turn, can lead to dangerous consequences. This potential phenomenon must be checked during the design phase of pipeline systems in order to prevent such dangerous situations. For this purpose, many software programs have been developed worldwide to analyze fluid transients. In this study, a computer software was developed that analyzes this type of flow in pipeline systems using C# programming language. In addition to simulating and solving problems in transient flows in pipeline systems, this will help the purpose of having a free domestic transient flow software for education and research purposes, avoiding expensive alternatives. The method of characteristics is used to solve the nonlinear, hyperbolic partial differential equations of unsteady pipe flow. The developed software was tested using various well-known benchmark cases for validation purposes. It was shown that the computed results of the new software are very similar to those obtained in the literature, proving the accuracy and reliability of the new program. In future studies, it is hoped that the program will be more comprehensive with more boundary conditions added to the program. In this paper, the developed program and some of its important features will be introduced, and validation of the program with certain benchmark studies will be provided. [ABSTRACT FROM AUTHOR]

Most organizations have begun to adopt agile methods to pursue successful software development. However, the adoption and implementation of agile approaches are facing various challenges. The success of agile software development depends on Critical Success Factors (CSFs), which this study aims to identify and classify based on their relative importance. Through an extensive literature review, these factors are summarized, screened, and categorized into six dimensions. Their evolution is also outlined and analyzed. Then, the factors are illustrated through a bubble chart. Furthermore, this study determines the relevant CFSs that have a significant impact on how effectively can agile software development be implemented in China. The findings suggest certain recommendations to ensure that agile software projects are efficiently implemented in China, maximizing the chances of project success, providing valuable insights and practical guidance. [ABSTRACT FROM AUTHOR]

BackgroundAimMethod & ProceduresOutcomes & ResultsConclusionsAphasia therapy software: aninvestigation of the research literature and the challenges of software developmentDigital aphasia therapy has become increasingly popular over the past years. However, not all software described in the literature appears to reach clinical practice. It is currently unclear why this is the case.We had two aims. First, we aimed to create an overview of the digital aphasia therapy described and its clinical availability bysystematically searching and reviewing the research literature. Second, we aimed to investigate the experiences of researchers/developers of aphasia therapy software.We conducted a systematic search and review, screening references against our inclusion criteria. Clinical availability of the software was established through reading literature, conducting internet searches, and by contacting the researchers/developers who were associated with the software. Researchers/developers of the reported software were surveyed about their experiences with software development. Responses were the matically analysed into themes and subthemes.We identified a total of 63 unique pieces of software across 125 references. The software was mainly developed for English speakers and mainly focused on word retrieval or a combination of language skills. We established clinical availability with certainty for 35 pieces of software, with the remaining software (likely) currently clinically unavailable. From the survey data, we identified five recurring themes: 1) software development can be expensive and insufficient funding hinders their clinical availability; 2) commercialisation of software is often new and daunting to researchers but essential for making software available; 3) clinicians and people with aphasia are valuable sources of feedback; 4) working with software developers can be difficult; and 5) aphasia therapy software should combine both the evidence base and current clinical need.Aminority of aphasia therapy software described in the literature reaches clinical practice. It is clear that the development and subsequent dissemination of aphasia therapy software requires large amounts of time, energy, and funds but we conclude that this is essential for successful clinical implementation. [ABSTRACT FROM AUTHOR]

Smart security devices, such as smart locks, smart cameras, and smart intruder alarms are increasingly popular with users due to the enhanced convenience and new features that they offer. A significant part of this convenience is provided by the device's companion smartphone app. Information on whether secure and ethical development practices have been used in the creation of these applications is unavailable to the end user. As this work shows, this means that users are impacted both by potential third-party attackers that aim to compromise their device, and more subtle threats introduced by developers, who may track their use of their devices and illegally collect data that violate users' privacy. Our results suggest that users of every application tested are susceptible to at least one potential commonly found vulnerability regardless of whether their device is offered by a known brand name or a lesser-known manufacturer. We present an overview of the most common vulnerabilities found in the scanned code and discuss the shortcomings of state-of-the-art automated scanners when looking at less structured programming languages such as C and C++. Finally, we also discuss potential methods for mitigation, and provide recommendations for developers to follow with respect to secure coding practices. [ABSTRACT FROM AUTHOR]

Organisations are becoming concerned with effectively dealing with privacy-related requirements. Existing Requirements Engineering methods based on structured natural language suffer from several limitations both in eliciting and specifying privacy requirements. In our previous study, we proposed a structured natural-language approach called the "Privacy Criteria Method" (PCM), which demonstrates potential advantages over user stories. Our goal is to present a PCM evaluation that focused on the opinions of software practitioners from different companies on PCM's ability to support the specification of privacy requirements and the quality of the privacy requirements specifications produced by these software practitioners. We conducted a multiple case study to evaluate PCM in four different industrial contexts. We gathered and analysed the opinions of 21 practitioners on PCM usage regarding Coverage, Applicability, Usefulness, and Scalability. Moreover, we assessed the syntactic and semantic quality of the PCM artifacts produced by these practitioners. PCM can aid developers in elaborating requirements specifications focused on privacy with good quality. The practitioners found PCM to be useful for their companies' development processes. PCM is considered a promising method for specifying privacy requirements. Some slight extensions of PCM may be required to tailor the method to the characteristics of the company. [ABSTRACT FROM AUTHOR]

The Python Testbed for Federated Learning Algorithms (PTB-FLA) is a simple Python FL framework that is targeting edge systems and is by its design easy to use by human ML&AI developers. The original PTB-FLA development paradigm intended for humans consists of the four phases (producing the sequential code, the federated code, the federated code with callbacks, and the PTB-FLA code, respectively), and hence dubbed the four-phases (development) paradigm, was validated in the case study on the logistic regression. In this paper, we adapted the original paradigm into the two new paradigms for ChatGPT, named the adapted four-phases paradigm and the adapted two-phases paradigm, respectively. In tune with its name, the latter consists of two phases (producing the sequential and the PTB-FLA code, respectively). We successfully validated both new paradigms using the same case study on logistic regression that was used for the original paradigm. The results are positive and encouraging as the resulting program codes are of better quality than the codes solely made by humans using the original paradigm. [ABSTRACT FROM AUTHOR]

Although large language models (LLMs) have demonstrated remarkable code-generation ability, they still struggle with complex tasks. In real-world software development, humans usually tackle complex tasks through collaborative teamwork, a strategy that significantly controls development complexity and enhances software quality. Inspired by this, we present a self-collaboration framework for code generation employing LLMs, exemplified by ChatGPT. Specifically, through role instructions, (1) Multiple LLM agents act as distinct "experts," each responsible for a specific subtask within a complex task; (2) Specify the way to collaborate and interact, so that different roles form a virtual team to facilitate each other's work, ultimately the virtual team addresses code generation tasks collaboratively without the need for human intervention. To effectively organize and manage this virtual team, we incorporate software-development methodology into the framework. Thus, we assemble an elementary team consisting of three LLM roles (i.e., analyst, coder, and tester) responsible for software development's analysis, coding, and testing stages. We conduct comprehensive experiments on various code-generation benchmarks. Experimental results indicate that self-collaboration code generation relatively improves 29.9–47.1% Pass@1 compared to the base LLM agent. Moreover, we showcase that self-collaboration could potentially enable LLMs to efficiently handle complex repository-level tasks that are not readily solved by the single LLM agent. [ABSTRACT FROM AUTHOR]

In order to study the characteristics of the wake magnetic anomaly when multiple ships are sailing at the same time, based on the basic theoretical knowledge of ship wake, the waveform, velocity, and distribution of the induced magnetic field of the ship wake were studied, and the variation characteristics and distribution patterns of the induced magnetic field of the multi-ship wake were obtained. By taking the formation of three ships as an example, the distribution of the induced magnetic field and the distribution of the magnetic field in the directions of x and y during the movement of the ships were analyzed. The magnetic field distribution characteristics of the wake formed when the three ships sail at the same time were solved, and the abnormal induced magnetic field generated during various ship combination operations was analyzed. The experimental results obtained from the simulation were consistent with the existing measurement results. APP Design tools were used for magnetic anomaly simulation system software development of multi-ship wake. The system not only could accurately, intuitively, and quickly simulate and set the magnetic induction intensity and variation patterns of the wake of three ships in any direction but also had the advantages of simple operation and cost saving, which provided a theoretical reference and a more effective simulation platform for ship wake experiment.

Multi-core shared memory architectures have become ubiquitous in computing hardware nowadays. As a result, there is a growing need to fully utilize these architectures by introducing appropriate parallelization schemes, such as OpenMP worksharing-loop constructs, to applications. However, most developers find introducing OpenMP directives to their code hard due to pervasive pitfalls in managing parallel shared memory. To assist developers in this process, many compilers, as well as source-to-source (S2S) translation tools, have been developed over the years, tasked with inserting OpenMP directives into code automatically. In addition to having limited robustness to their input format, these compilers still do not achieve satisfactory coverage and precision in locating parallelizable code and generating appropriate directives. Recently, many data-driven AI-based code completion (CC) tools, such as GitHub CoPilot, have been developed to ease and improve programming productivity. Leveraging the insights from existing AI-based programming-assistance tools, this work presents a novel AI model that can serve as a parallel-programming assistant. Specifically, our model, named PragFormer, is tasked with identifying for loops that can benefit from conversion to parallel worksharing-loop construct (OpenMP directive) and even predict the need for specific data-sharing attributes clauses on the fly. We created a unique database, named Open-OMP, specifically for this goal. Open-OMP contains over 32,000 unique code snippets from different domains, half of which contain OpenMP directives, while the other half do not. We experimented with different model design parameters for these tasks and showed that our best-performing model outperforms a statistically-trained baseline as well as a state-of-the-art S2S compiler. In fact, it even outperforms the popular generative AI model of ChatGPT. In the spirit of advancing research on this topic, we have already released source code for PragFormer as well as Open-OMP dataset to public. Moreover, an interactive demo of our tool, as well as a Hugging Face webpage to experiment with our tool, are already available. [ABSTRACT FROM AUTHOR]

Developing empathy skills is crucial for software developers to create user-centric solutions and design exceptional user experiences addressing the diverse needs of customers. This paper presents the findings of a quasi-experimental study that aimed to enhance empathy among computer science students through the exposure of two interventions utilizing teaching accessibility design. The study included 15 participants from a computer science course. Qualitative data analysis of participants' reflections highlighted the transformative impact of the interventions, as participants expressed changes in their views towards people with impairments and reported the development of technical and soft skills, as well as enhanced empathy. The interventions also motivated participants to make changes to their team website designs, prioritize accessibility, and apply their learnings in their professional lives. A second measure assessed in this study was an expert website review which provided valuable feedback for improvement and yielded a high average score for screen reader accessibility. By equipping future computer scientists with these skills, we can ensure that technology meets the diverse needs of all users, promoting inclusivity and enhancing user experiences. [ABSTRACT FROM AUTHOR]

The growing and unmet demand for coding skills is becoming critical in a world that is ever-more driven by digital technologies, embedded algorithms and artificial intelligence systems. However, sustainability of the profession is threatened because of the failure to attract and retain women developers, which has been an ongoing and corrosive problem for decades and remains unresolved. While many previous studies attribute 'toxic' workplace cultures in the software development industry, as a major contributing factor, few examine their root causes and almost none offer practical solutions. To address this lack of both knowledge and effective response, we propose a novel approach building on psychoanalytical Transactional Analysis (TA) theory that is little used in the field of management and organisation studies. TA theory provides a framework using common and simplified language to better understand why communications in the workplace fail, and how occupying incompatible ego states might lead to ' negative ', ' problematic' and, in the worst cases, ' toxic' behaviours and workplaces. We propose a TA-based model (OCTAPos) that helps explain how crossed communications at work can result in a lack of acceptance of women in the workplace and attrition among female software developers and the resultant dearth of diverse coders. We further propose a theoretically informed HRM Structured TA Response (STAR) to help increase self-awareness, emotional intelligence, empathy and mutual understanding, with the ultimate aim of positively impacting prevailing attitudes, behaviours and organisational culture to achieve more inclusive and sustainable recruitment and retention in the longer term. [ABSTRACT FROM AUTHOR]

【Objective】 Improving efficiency and water flow rate is a criterion in designing pumping stations. This paper presents a software we developed to optimize the combination of running pumps and blade angles for drainage pumping stations that are equipped with fully adjustable axial (mixed) flow pumps. 【Method】 The software was developed using Java in the integrated environment IntelliJ IDE, with a universal visualization interface. It calculated water flow rate and flow resistance parameters of each pump, based on measured operating parameters, which include head and motor input powers, and performance curve of each pump. The software generated curves illustrating how the device efficiency changes with the blade angle. A dynamic programming model was established to optimize the operation and scheduling of the station, with the optimization objective to maximize the average device efficiency or total flow rate. This enables us to obtain an optimal combination of running pumps and blade angle for each running pump. 【Result】 The software was applied to some drainage pumping stations to graphically analyze the variation in device efficiency with blade angle (or flow rate). It provides optimized operation plans under different required flow rates when Hsy=5.3 m. When the required flow rate was 32 m3/s, the optimal scheme provided by the software improves the efficiency of the device by 0.76%, compared to the simple decision scheme for each running pump with a blade angle of +1.0°. 【Conclusion】 The software we developed is accurate and user - friendly. Practical applications showed that its performance is stable and can improve the operation and management of drainage pumping stations.

Over the last thirty years, In the field of digital philology, several generic IT tools have been developed to produce digital scholarly editions (DSE). However, the majority of DSEs continue to be produced using custom-developed tools. This trend is unsustainable, but it is because generic tools are often less usable, difficult to customize, and unsuitable for the scientific objectives of scholars. The scientific community has been exploring how to create flexible and effective tools for digital philology. Two main responses have emerged in the literature: the need for shared editorial models that represent philologists’ desiderata, and the adoption of software engineering practices to produce more robust, durable, and easily maintainable tools. This article presents a modeling strategy that considers both perspectives and is based on the creation of a network of editorial models, each one theoretically framed within the philological approach in which it has emerged. The editorial models, formalized as ontologies, can be applied as conceptual models to determine the logical organization and functioning of a tool for digital philology, thanks to the principles of domain-driven design.

Historically, activities related to software development have been led by men, with weak participation from women. Currently, initiatives have been promoted to increasingly integrate women into this discipline. However, despite the known benefits of gender diversity in innovation and team performance, the visibility of women in this field remains weak. The primary objective of this article is to analyze strategies to attract female talent to the software development industry, aiming to reduce the gender gaps that women face. The methodology used in this work is based on several steps of systematic literature mapping, which seeks to provide a comprehensive overview of the literature on this topic, classify the findings, and offer a framework for future research in this area. The main findings highlight the need for organizational policies and work practices that promote gender equality, as well as the importance of early education and training in retaining female talent in the software industry. This study not only contributes to academic discourse but also suggests practical measures for industry professionals to foster a more inclusive and equitable work environment. [ABSTRACT FROM AUTHOR]

The goal of this research study was to identify and prioritize the significant cybersecurity challenges that vendor firms encounter during software development. Using Systematic Literature Reviews (SLRs), 13 significant challenges were found, including “Security issues/Access of Cyberattacks”, “Lack of Right Knowledge”, “Cost Security Issues”, and “Lack of Confidentiality and Trust” among others. To address these concerns, a multifaceted strategy that prioritizes continuing education, training, and investment in cybersecurity measures, as well as cross‐industry cooperation and coordination with government entities, is required. These challenges were ranked using the Fuzzy Analytic Hierarchy Process (F‐AHP). We obtained the following results after applying the Fuzzy Analytic Hierarchy Process: CSC1 (Cyber Security Challenge‐1) “Security Issues/Access of Cyber Attacks”, CSC2 “Lack of Right Knowledge”, and CSC3 “Framework” are the top most critical cyber security challenges, with weightages of 0.1687, 0.1672, and 0.1194, respectively. This study lays the groundwork for future research and assists vendor organizations in addressing the cybersecurity concerns they face during software development. The study also emphasizes the significance of addressing cybersecurity during the software development process in order to avoid the financial and reputational losses associated with cyber intrusions. [ABSTRACT FROM AUTHOR]

Quantum computing is tipped to lead the future of global technological progress. However, the obstacles related to quantum software development are an actual challenge to overcome. In this scenario, this work presents an implementation of the quantum search algorithm in Atos Quantum Assembly Language (AQASM) using the quantum software stack my Quantum Learning Machine (myQLM) and the programming development platform Quantum Learning Machine (QLM). We present the creation of a virtual quantum processor whose configurable architecture allows the analysis of induced quantum noise effects on the quantum algorithms. The codes are available throughout the manuscript so that readers can replicate them and apply the methods discussed in this article to solve their own quantum computing projects. The presented results are consistent with theoretical predictions and demonstrate that AQASM and QLM are powerful tools for building, implementing, and simulating quantum hardware. [ABSTRACT FROM AUTHOR]

Copyright of ABI Technik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The responsibility for creating accessible software within the development of digital services is important for multiple reasons, mainly equity and inclusion. However, adopting and sustaining the development of accessible digital solutions has always been challenging, more so in countries that are relatively new to the concept of universal design, and physical and digital accessibility, and where legal sanctions are not yet established. This work investigates the technology scene in the State of Kuwait and analyses the responses of computing professionals with regard to their skills, best practices and procurement of accessible tech and to their level of awareness toward people with disabilities. The findings reveal a low level of awareness among tech professionals with regard to disabilities and digital accessibility-related standards. The findings also highlight a lack of available guidance for developing inclusive design and accessibility. Additionally, time constraints, lack of training, legal enforcement and fundamentals concepts during undergraduate and higher education contributed to observed weaknesses. Participants were keen to learn more and benefited from flyers and free professional development courses offered as incentives for survey completion. [ABSTRACT FROM AUTHOR]

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During scrum iterations, it is possible to apply cost forecasting for software testing and operation, if the data from previous iterations are known. Since the data for estimating the scope of work and the deadline within one sprint are accumulated during the project execution, it is possible to use such data to build a forecasting algorithm for the estimated parameters of the subsequent sprints. The approach is based on refining the assessment provided by the development team and the scrum master in a specific metric. The main parameters for evaluation are the execution time and the amount of work performed. As a result of forecasting, it is possible to obtain clarifications for the team’s assessment regarding the scope of work for the next sprint. This estimate is based on planned and actual data from the previous sprints. The article discusses the method of least squares and the proposed code for a machine learning model based on this method. An example and graphs for iterations in scrum and corresponding forecasting for the next sprints are presented. The use of the least squares method allows creating a mathematical model that can be adapted to different project conditions, providing flexibility and accuracy in forecasting. For example, the study uses the real data from the previous sprints, which includes the team’s resource assessment and actual expenditures. Based on these data, a model was built that demonstrates a high correlation between predicted and actual costs, confirming the effectiveness of using the least squares method. So, the least squares method is an effective tool for forecasting software development costs in scrum iterations. This method allows development teams to better plan their resources and timelines, contributing to the overall efficiency of the project [ABSTRACT FROM AUTHOR]

In this study, we explore the future of work by examining differences in productivity when teams are composed of only humans or both humans and machine agents. Our objective was to characterize the similarities and differences between human and human–machine teams as they work to coordinate across their specialized roles. This form of research is increasingly important given that machine agents are becoming commonplace in sociotechnical systems and playing a more active role in collaborative work. One particular class of machine agents, bots, is being introduced to these systems to facilitate both taskwork and teamwork. We investigated the association between bots and productivity outcomes in open source software development through an analysis of hundreds of project teams. The presence of bots in teams was associated with higher levels of productivity and higher work centralization in addition to greater amounts of observed communication. The adoption of bots in software teams may have tradeoffs, in that doing so may increase productivity, but could also increase workload. We discuss the theoretical and practical implications of these findings for advancing human–machine teaming research. This research characterizes the changing landscape of collaborative work brought on by the increasing presence of autonomous machine agents in teams. We report on a multidimensional analysis of work in software development projects examining differences between human‐only and human‐bot teams. [ABSTRACT FROM AUTHOR]

Copyright of Revista Espacios is the property of Talleres de Impresos Oma and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Software development projects face significant risks of going over budget, over schedule, and of failing to deliver expected benefits. These risks have endured despite methodological changes within the industry, such as the rise in popularity of Agile. This research looks outside of the software industry and seeks inspiration from film production, which has developed different management strategies to address challenges similar to those faced by software development projects. First, an analysis of film production project management reveals four principles, each evidenced by a set of practices used throughout the industry. Next, we identify sets of practices that would enable software development projects to also align to those same four principles. The synthesis of each principle from its set of supporting film production practices is then validated through structured interviews with veteran film producers. Lastly, the derivation of each principle to a parallel set of supporting practices within the context of software development is validated in a second series of interviews with experienced software development project managers. In total, this research identifies a set of software development project management practices that mirror film production practices. These practices offer a framework for software development project managers to consider when seeking to tailor existing methodologies, particularly in scenarios that present challenges similar to those encountered in film production. [ABSTRACT FROM AUTHOR]

Copyright of Revista Facultad de Ingeniería - UPTC is the property of Universidad Pedagogica y Tecnologica de Colombia, Facultad de Ingenieria and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The residual subsidence caused by mining has a long stabilization time and great potential harm. It is necessary to accurately predict the residual subsidence value of the ground of the mining area. In view of the large modeling error and weak applicability of the traditional residual subsidence Verhulst model, the first data of the data sequence was kept unchanged in the modeling process, which leads to the poor prediction effect. Based on the direct discrete Verhulst model, the PSO (particle swarm optimization) algorithm was introduced to find the optimal solution of the initial value of the model iteration, and the direct discrete Verhulst model of mining residual subsidence based on PSO was established. The surface residual subsidence monitoring data sets of two time scales in Yangquan, Shanxi and Yanzhou, Shandong were used for example verification. Finally, the visualization of the model algorithm was realized by using Matlab App Designer tool. The results show that the prediction accuracy and stability gain of residual subsidence in mining area based on direct discrete Verhulst model optimized by particle swarm optimization are obvious, and the developed calculation tool is correct and effective. [ABSTRACT FROM AUTHOR]

The article discusses the application of model-based systems engineering in software development. MBSE offers a new model-based approach to viewing complex systems, allowing data and information to be effectively shared across different product life cycle stages. The paper examines the model-based systems engineering methodology, its benefits, and its impact on requirements, design, analysis, and verification within the product life cycle. The study highlights the relevance of using model-based systems engineering to modern systems engineering practices, especially in the context of software engineering. The study results demonstrate the benefits of model-based systems engineering and its ability to optimize development processes, improve product quality, and reduce delivery times. The scientific novelty of the article lies in the application and research of the model-based systems engineering in the context of software development, which represents a significant contribution to the development of modern systems engineering practices and development technologies. [ABSTRACT FROM AUTHOR]

Digitalization of data into electronic formats can transform the efficiency of an organization. Advances in software programming have enabled seamless conversion of manual workflows into electronic processes. We have described our experiences in the development of reliable and robust inter-connected electronic systems. In this article we have addressed the challenges in the development of electronic laboratory notebook software that follows a workflow in a biological laboratory. These challenges include: (i) linguistics: translation of ‘language of the scientist’ to the ‘language of the software designer’ and to the ‘language of the programmer’, (ii) limited knowledge of capabilities and limitations of technologies on either side (scientific and software) and (iii) lack of communication and documentation practices for capturing the requirements. Data integrity is the central regulatory requirement to a quality management system. Digitalization can address this challenge by addressing three major advantages – standardization of processes, increased compliance and enhanced efficiency. The observations made during the development processes of the present study can be applied to scientific software development and increasing requirements for collaboration of diverse cross-functional teams. [ABSTRACT FROM AUTHOR]

This paper provides a concise overview of Agile and DevOps methodologies in software engineering. It aims to introduce readers to the fundamental principles of Agile and DevOps, accompanied by brief descriptions and practical examples. The advantages and disadvantages of each methodology are discussed, followed by a comparative analysis highlighting key differences. Understanding these methodologies is crucial in today’s IT landscape, as they are commonly employed in various organizations, impacting project management, team collaboration, and product delivery. This paper serves as a valuable resource for individuals seeking a basic understanding of Agile and DevOps methodologies in software engineering. [ABSTRACT FROM AUTHOR]

Microservices are a software development approach where an application is structured as a collection of loosely coupled, independently deployable services, each focusing on executing a specific purpose. The development of microservices could have a significant impact on radiology workflows, allowing routine tasks to be automated and improving the efficiency and accuracy of radiologic tasks. This technical report describes the development of several microservices that have been successfully deployed in a tertiary cancer center, resulting in substantial time savings for radiologists and other staff involved in radiology workflows. These microservices include the automatic generation of shift emails, notifying administrative staff and faculty about fellows on rotation, notifying referring physicians about outside examinations, and populating report templates with information from PACS and RIS. The report outlines the common thought process behind developing these microservices, including identifying a problem, connecting various APIs, collecting data in a database, writing a prototype and deploying it, gathering feedback and refining the service, putting it in production, and identifying staff who are in charge of maintaining the service. The report concludes by discussing the benefits and challenges of microservices in radiology workflows, highlighting the importance of multidisciplinary collaboration, interoperability, security, and privacy. [ABSTRACT FROM AUTHOR]

Copyright of China Petroleum Machinery is the property of China Petroleum Machinery Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Issue Tracking System (ITS) repositories are rich sources of software development documentation that are useful in assessing the status and quality of software projects. An original model is proposed for tracing issue handling activities and their impact on project progress. As opposed to classical data mining of software repositories, we consider fine-grained features of issues which provide a better insight into project evolution. A thorough analysis of repository contents allows us to define useful metrics for characterizing issue handling schemes. These metrics are derived from the introduced graph model and developed original data mining algorithms targeting timing, issue flow progress and project actor activity aspects. This study is associated with issue processing states and their sequences (handling paths), leading to problem resolution. The introduced taxonomy of issue processing schemes facilitates the creation of a pertinent knowledge database and the identification of both bad (anomalies) and good practices. The proposed approach is illustrated with experimental results related to a representative set of ITS project repositories. These results enhance experts' knowledge of the project and can be used for correct decision-making actions. They reveal weak points in project development and possible directions for improvement. [ABSTRACT FROM AUTHOR]

Reasonable sensor placement is the premise of station structure health monitoring and the key to obtaining accurate response information. Aiming at the issues such as the fuzzy positioning of the existing sensor strain monitoring points and the lack of placement method, a Python-based optimal sensor placement program for railway station roofs is compiled and developed based on the regulations and model analysis results. The purpose of this program is to assist engineers in more efficiently screening and optimizing the placement of dynamic and static sensors through customized screening limits and intelligent optimization algorithms, thereby avoiding signal interference and cost wastage caused by redundant sensor arrangements and maximizing the coverage and sensitivity of structural response. The results indicate that this program can display the strain monitoring points visually, and clearly show the position of the measuring point along the member direction and its specific coordinates on the member cross section. The issue of fuzzy strain monitoring points in the traditional placement method is effectively solved. Secondly, the program improves the rationality and science of measuring placement and makes up for the shortage of acceleration sensor placement based on experience by using the particle swarm optimization algorithm and minimize modal assurance criterion. Thirdly, the program with a simple operation interface improves the efficiency of sensor screening optimization, meeting the requirements of engineers for the placement of monitoring points. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) student lending platforms have emerged as an alternative source of funding for students who are unable to obtain loans from traditional lenders. Traditional loan systems have become less accessible and affordable for all students, and information asymmetry is a significant challenge that can have serious consequences for lenders and borrowers. The rising cost of higher education in many countries has made it challenging for some students to access the funds they need to finance their education. This study aims to design and implement a P2P student lending system that addresses these challenges. The research conducted enables the production of a P2P loan framework using PHP, Mysql, and Javascript that incorporates essential features gleaned from literature and existing P2P applications. The study improves the payback rate by reducing information asymmetry in the P2P lending system using the following methods; detailed applicant profiles, robust credit scoring models, income verification, transparent loan terms, and peer reviews and ratings. The prototype software development model was used to develop the P2P framework. The system is evaluated against industry-relevant metrics, such as loan characteristics, credit risk, and loan performance. The software was developed using HTML, JavaScript, PHP, and CSS, with the Operating System being Microsoft Windows 11. The result of the research is a more accessible and transparent lending system that supports students who require funds to complete their education after a thorough verifiction process by the system. The system was evaluated based on the reviews and ratings gotten from the clients and users. The implementation of this system can significantly impact the education sector by increasing access to funding for students. [ABSTRACT FROM AUTHOR]

Building and testing software for embedded systems can be challenging with an impact on delivery time, design reproducibility, and collaboration among project contributors. To accelerate project development, presented here is an automated build flow that utilizes Xilinx PetaLinux, and field programmable gate array (FPGA) hardware description and integrates with the GitLab continuous integration and continuous deployment (CI/CD) framework for embedded targets. This build flow automates the complete process of FPGA implementation, PetaLinux configuration, and cross-compilation of software essentials for the target system-on-chip (SoC). The system has been successfully deployed in cross-compiling the control and command toolset for the Positron Emission Tomography scanner (PhenoPET) and the implementation of the message queuing telemetry transport (MQTT) service on a Xilinx Zynq Ultrascale MPSoC. This approach can be easily adapted to other projects with specific requirements. [ABSTRACT FROM AUTHOR]

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A bug tracking system (BTS) is a comprehensive data source for data-driven decision-making. Its various bug attributes can identify a BTS with ease. It results in unlabeled, fuzzy, and noisy bug reporting because some of these parameters, including severity and priority, are subjective and are instead chosen by the user’s or developer’s intuition rather than by adhering to a formal framework. This article proposes a hybrid, multi-criteria fuzzy-based, and multi-objective evolutionary algorithm to automate the bug management approach. The proposed approach, in a novel way, addresses the trade-offs of supporting multi-criteria decision-making to (a) gather decisive and explicit knowledge about bug reports, the developer’s current workload and bug priority, (b) build metrics for computing the developer’s capability score using expertise, performance, and availability (c) build metrics for relative bug importance score. Results of the experiment on five open-source projects (Mozilla, Eclipse, Net Beans, Jira, and Free desktop) demonstrate that with the proposed approach, roughly 20% of improvement can be achieved over existing approaches with the harmonic mean of precision, recall, f-measure, and accuracy of 92.05%, 89.04%, 90.05%, and 91.25%, respectively. The maximization of the throughput of the bug can be achieved effectively with the lowest cost when the number of developers or the number of bugs changes. The proposed solution addresses the following three goals: (i) improve triage accuracy for bug reports, (ii) differentiate between active and inactive developers, and (iii) identify the availability of developers according to their current workload. [ABSTRACT FROM AUTHOR]

In this paper, Virtual Reality Shopping Insights (VRSI) is presented, a framework that aids the development of Virtual Reality (VR) shopping applications as well as collecting data and analysing it. VRSI aims to help software developers and researchers by abstracting the layers needed to setup VR technology on applications developed with Unity. Moreover, it provides data registration tools that monitors user activity from non invasive data sources. This data can be useful for marketing analysts to understand user behaviour inside V-commerce applications, helping them to improve the setup and layout of such environments with data-driven decisions. Furthermore, we present an example of VR shopping application developed with VRSI.