Software Development Research Articles

Catálogo de directrices de sostenibilidad para soportar el desarrollo y operación de software sostenible desde la ingeniería de requisitos

Sustainability constitutes one of the major challenges of today's society, in particular the sustainability of ICTs and more specifically of software. Requirements engineers need guidelines to successfully address sustainability in software projects. With this goal in mind, the CRETS4DevOps method has been designed to manage requirements in DevOps environments while promoting sustainability, especially technical sustainability. CRETS4DevOps encompasses a catalog of sustainability requirements, which helps in the reuse of expert knowledge in order to address the management of software quality attributes that result in sustainability, namely: modularity, scalability, flexibility, reusability, maintainability, reliability, security, interoperability and efficiency. This catalog is intended to assist practitioners both in software development and operation as well as in a sustainability audit. A tool to support CRETS4DevOps is currently being developed as a plug in for Microsoft Azure DevOps.

Lack of Eye Gaze and its Effects on Spoken Interaction in Synchronous Online Communication

The importance of oral interaction in language learning is well recognised, and this paper examines the factors that hinder English as a Foreign Language (EFL) learners’ active participation in online discussions during Synchronous Online Communication. Using focus groups with 51 Cypriot Greek-speaking students from three tertiary institutions in Cyprus, thematic analysis revealed that the perceived prominent factor inhibiting oral interaction in the online environment was the absence of eye gaze and its associated social functions. Specifically, eye gaze was identified as a signal for turn-taking, turn-yielding, and turn-denying, whose absence hindered learners’ ability to interpret their peers’ and teachers’ intentions and expectations. The paper concludes with pedagogical implications for technologists, software developers, students, language teachers, and language teacher educators.

Optimizing development and operations from the project success perspective using the analytic hierarchy process

By merging development and operation disciplines, the approach known as development and operations (DevOps) can significantly improve the efficiency and effectiveness of software development. Despite its potential benefits, successfully implementing DevOps within traditional project management frameworks presents significant challenges. This study explores the critical factors influencing the implementation of DevOps practices from the project management perspective, specifically focusing on software development projects in the Ministry of Finance. This study utilizes the analytic hierarchy process (AHP) to prioritize the critical elements of project success criteria and DevOps factors necessary for effective implementation. The findings indicate that stakeholder satisfaction, quality, and value creation are the primary criteria for project success. Moreover, knowledge and skills, collaboration and communication, and robust infrastructure are pivotal factors for facilitating DevOps within project management. The study provides actionable insights for organizations aiming to improve their project outcomes by incorporating DevOps and offers a systematic approach to decision-making using AHP. This study recognizes limitations due to its focus on specific contexts and emphasizes the need for future research in diverse organizational environments to validate and expand these findings.

Have You Done Any Interactive Work Today?: An Empirical Study on the Relationship Between Customer Interaction and Psychological Stress in German Software Developers

Have You Done Any Interactive Work Today?: An Empirical Study on the Relationship Between Customer Interaction and Psychological Stress in German Software Developers

Editorial para el número especial de la 12a Conferencia Internacional sobre Investigación e Innovación en Ingeniería de Software

Software Engineering is responsible for analyzing, designing, implementing, testing and maintaining software developments. It is currently a very important area since software is found everywhere in our lives, we are immersed in technological advances. Given the importance of Software Engineering, this special issue presents the research articles in Spanish from the 12th International Conference on Software Engineering Research and Innovation.

Migración de serverbox hacia un sistema de microservicios aplicando arquitectura vertical

Efficient data management is essential in public administration for the effective operation of municipal cadastral systems. In 2010, the Multifinality Cadastral Modernization Program was implemented, a partnership between the Puebla municipality government and Sistemas de Información Geográfica S.A. de C.V. (SIGSA), which included the ServerBox platform. Over time, the monolithic architecture of ServerBox showed limitations in maintenance, updates, and change deployment. This project hypothesizes that migrating ServerBox to a distributed microservices architecture, using a vertical approach, can overcome these challenges and improve operational areas of the system. The proposed design establishes a modular and scalable structure that facilitates system maintenance and evolution. The implementation includes the development of TagHelpers in ASP.NET Core to simplify HTML element creation and the use of snippets to streamline coding. Additionally, a JSON configuration file is defined to manage multiple deployment environments. This strategic approach to migrating ServerBox to a distributed and vertical architecture offers significant advantages in terms of scalability, maintenance, and software development efficiency, and can serve as a guide for similar projects in public administration.

Enhancing software engineering practices with generative AI: A framework for automated code synthesis and refactoring

This paper is based on how software development has been revolutionized using AI in automation, mainly dealing with code synthesis and rewrite frameworks. While there is no focused definition for software development with AI technologies, their application in development processes is unlikely to remain marginal as they mature and provide higher productivity, improved code quality, and enhanced ability for automating repetitive tasks in development. Automating coding means that predefined tools can bring code suggestions, show and apply refactoring features, and enforce coding standards so developers can devote their efforts to other aspects of software development. The following paper describes the practical systems that should be adopted before AI can be incorporated into software development. It also covers essential factors such as ethical, security, and quality aspects regarding the proper use of artificial intelligence. Lastly, the paper focuses on the direction and innovations in the future, including domain-specific AI models, better explainability of the AI solutions, and collaborative tools that can work according to improved and modified development practices. The framework is intended to balance machine learning with human experience to help developers utilize the benefits that an AI-Based Software Development Framework can render.

Integrating Generative AI into the Software Development Lifecycle: Impacts on Code Quality and Maintenance

Recent advances in generative AI have depicted it as a revolutionary approach in the software development technologies pioneered to improve the codes' reliability and sustain their quality and performance. Generative AI tools can help develop code independently, suggest intelligent solutions and ideas, and enhance several development procedures thanks to superior algorithms and machine learning features. This paper discusses how generative AI can/has been applied within software development to achieve the following three goals: First, to increase the code quality using automated code generation/review. Second, the code maintainability should be improved through standards and documentation. Third, to increase the up-to-speed development productivity due to AI-based automation, namely the automation of repetitive tasks and fast prototyping. The paper also considers issues and difficulties that can be tied to AI in this context: problems of dependence on AI, ethical and security issues, and technical imperfections. Finally, the implications of generative AI in software development in the future are presented, which can open a new direction in the development of software products while primarily pointing to the processes of managing the introduction of generative AI. Using the evaluation of the current possibilities and future perspectives of generative AI presented in this paper, one can conclude its impact on the future of software engineering.

Integrating AI into DevOps pipelines: Continuous integration, continuous delivery, and automation in infrastructural management: Projections for future

This paper explores the transformative role of Artificial Intelligence (AI) in enhancing DevOps pipelines, focusing on Continuous Integration (CI), Continuous Delivery (CD), and automation in infrastructural management. As organizations increasingly adopt DevOps methodologies to streamline software development and delivery processes, the integration of AI technologies offers significant potential for improving efficiency, quality, and responsiveness. This study reviews current practices in CI/CD and examines how AI-driven tools can automate repetitive tasks, optimize resource allocation, and facilitate predictive analytics for proactive decision-making. Additionally, the paper discusses the challenges and considerations associated with AI integration in DevOps, including cultural shifts, data governance, and the need for skilled personnel. Projections for future developments highlight the potential for AI to create smarter, more adaptive DevOps environments that align with evolving industry demands. By identifying key trends and innovations, this research provides a comprehensive overview of the future landscape of DevOps, positioning AI as a critical enabler of agility and performance.

A research paper on software design patterns

This article affords another exhaustive examination of software design patterns, discussing their importance, the classification system, and the influence on software architecture and design. It looks at how existing practices handle predictable problems, make things more easily serviceable, and increase developer collaboration. The article goes further and explains the use of design patterns and elaborates on real-life examples of design patterns and the difficulties and drawbacks of using them. Further, it expands on future possibilities, such as applying design patterns for cloud-new architectures, AI incorporation, serverless, and Agile/DevOps. From these trends, the article lays down the argument that design patterns are not insulated from change but are continually being adapted to fit into the software development processes of today's complex and sophisticated world and that to be relevant in the designing of today's complex, large and intelligent software-based systems, developers should be familiar with both the recognized and emergent design patterns.

Exploring the synergy between generative AI and software engineering: Automating code optimization and bug fixing

As applied to software engineering, generative AI is quickly transitioning from a zero-sum industry game changer into the primary automation tool for code optimization, bug identification, and problem-solving. This technology takes advantage of artificial intelligence algorithms within machine learning models to analyze and write code, resulting in improved quality and speed of an application development process. The generative AI replenishes productivity in development work and enhances centralization between development work teams through code handling and intelligent suggestions for essential codes. However, the integration of AI in software engineering poses the following problems and ethical questions: the question of accuracy, bias, and data. This paper will review the existing knowledge on generative AI in software engineering regarding its current use, future evolutions and advancements, issues and limitations, and ethical factors in using this technology. This paper considers these aspects to give a global outlook on how generative AI will transform software development in the future and how responsible AI should be employed.

Use of Artificial Intelligence in Fashion Sales Techniques

This article discusses the prominent elements of artificial intelligence innovation in fashion sales techniques and details artificial intelligence-supported sales strategies such as virtual reality, augmented reality, virtual try-on rooms, smart mirrors, artificial intelligence-supported style consultants, visual search technologies and chatbot. This study was written with the compilation method. The compilation method is written with the aim of collecting the literature written so far on the research subjects from a scientific perspective and making a collective contribution to the literature. While virtual reality and augmented reality offer customers interactive shopping experiences and the opportunity to try products in their own environment without going to the store, virtual trial rooms and smart mirrors; Studies have shown that it has the potential to make online and face-to-face shopping easier, faster and more interactive. It has been stated that visual search technologies enable customers to easily find the products in the style they want, and artificial intelligence-supported style consultants and chatbots play an important role in optimizing the shopping experience by making personalized suggestions to customers. New and innovative solutions can be produced by conducting studies that encourage interdisciplinary collaboration between fashion designers, software developers and academicians. In this period when we live intertwined with technology, artificial intelligence-focused modules can be added to academic curricula for students studying in the field of design, and these modules will provide benefits for students to gain knowledge and skills on how to integrate artificial intelligence technologies into fashion design. The effective use of artificial intelligence in fashion sales techniques will provide a competitive advantage against competitors in the industry.

Assessing the Effectiveness of MoSCoW Prioritization in Software Development: A Holistic Analysis across Methodologies

Effective software Requirement Prioritization plays a pivotal role in the success of the Software Development process, ultimately contributing to the successful delivery of high-quality products. Among the various methods for Requirement Prioritization, the MoSCoW method has gained widespread adoption due to its ease of use. However, its overall effectiveness remains a subject of inquiry. This paper presents a rigorous assessment of the MoSCoW Requirement Prioritization technique, drawing insights from software developers who engage in the Prioritization process. Our evaluation encompasses a distinct perspective: that of the developers tasked with Prioritization. The feedback solicited from developers encapsulates a diverse set of criteria, shedding light on the method's efficacy. Additionally, we perform sentiment analysis on the user experience of the Prioritization task to corroborate the method's accuracy and efficiency. Our study unfolds through a practical exercise involving the Prioritization of a predefined set of requirements using MoSCoW principles. A mixed method approach is employed for the purpose of assessing the effectiveness of MoSCoW. The findings of our quantitative research underscore the method's limitations, indicating that it may not be as effective and precise as previously believed. Furthermore, through qualitative analysis, we are able to highlight the complexities and challenges associated with MoSCoW-based Prioritization. The insights gained from this analysis prompt contemplation regarding the potential introduction of an evolved Requirement Prioritization method, while leveraging MoSCoW as a foundational framework. This research aims to inform the ongoing evolution of Requirement Prioritization methodologies, ultimately enhancing the efficiency and accuracy of Software Development processes.

Building credibility for human systems integration in model‐based systems engineering

AbstractRobust and trusted digital human representations are necessary to successfully account for human considerations in model‐based systems engineering (MBSE). Multiple domains and modeling frameworks leverage verification, validation, and accreditation (VV&A) processes to characterize when and under what conditions a model is valid to establish credibility. A literature review was completed on mathematical, physics‐based, software development, discrete event simulation, agent‐based, system dynamics, and MBSE models with the goal of proposing a process for performing VV&A on digital engineering (DE) and MBSE models for sociotechnical systems. However, this research also revealed the need for a broader framework to characterize the risk associated with using these models for making high‐consequence decisions. While accomplishing the literature review, another approach to building credibility was identified that is used heavily in the financial industry, namely model risk management (MRM). This process is extended by leveraging MRM approaches from within the financial community to propose a framework for sociotechnical model users to characterize the risk of using MBSE models to make programmatic decisions. The primary contribution of this work is to document a meta‐analysis of model VV&A while proposing an alternative approach to characterizing and communicating credibility that was discovered during this analysis. This approach could be a viable option for ensuring the credibility of human systems integration in MBSE models.

A Systematic Mapping of Configuration Management Activities in Software Product Line

In the software product line (SPL), configuration management (CM) is a multidimensional problem that is taking great attention in software development.  Although much research has been developed on this topic, there is no clear view of the current state of it. In this study, we used a systematic method to develop a map of configuration management across product lines to classify relevant literature. The resulting map provides an overview of this research through the identification of the main activities of the CM, the types and trends of research as well as the maturity of existing contributions. Because the CM in SPL is still in its formative stage, we believe that this work will contribute to the process of providing a more common and coherent conceptual basis for its understanding. In addition, it can help to detect important research problems and gaps.

Microservices Patterns Recommendation based on Information Retrieval

Software developers encounter recurring problems during software development, which can be solved using proven solutions known as design patterns. Microservices architecture, a Service-Oriented Architecture (SOA) variant, presents common communication, deployment, and service definition challenges. However, selecting the appropriate design pattern from a vast pool of patterns to solve a problem is difficult for novice and experienced developers. This paper proposes a recommendation tool based on Information Retrieval (IR) to assist developers in choosing the suitable microservices pattern to solve a given problem. The tool leverages textual descriptions given by developers to provide relevant indications of microservices patterns. It has been evaluated using both toy and industrial problems, demonstrating promising results. The results showed that the tool was able to solve 60% of toy design problems, indicating that it can provide valuable and accurate recommendations. Furthermore, tests with industrial problems revealed that over 70% of the recommended patterns helped to address the problems at hand. Interviews with developers who work in the software industry corroborated the recommendation tool’s effectiveness and practicality.

Cybersecurity Maintenance in the Automotive Industry Challenges and Solutions: A Technology Adoption Approach

Numerous attempts have been made to create a secure system that meets the criteria and requirements of the automotive vehicle development life cycle. However, a critical gap exists in the secure development lifecycle, particularly concerning the development and maintenance of software after the vehicle has been sold by the manufacturer. This step is often overlooked by original equipment manufacturers (OEMs), especially after the expiration of the vehicle warranty period, given the cost that it will require to update and test the software in their vehicles. This paper addresses the issues that affect current and future vehicle cybersecurity, during the maintenance of cybersecurity, and how the neglect of it could end up creating hazards for the vehicle owner or other road users. To accomplish this, we will employ the technology adoption model (TAM) as a theoretical framework, which is used to understand and predict how organizations adopt technology. Thus, through qualitative and quantitative research, including text mining, we identify the challenges in the adoption and diffusion of cybersecurity maintenance in the automotive sector and its supply chain. In addition, we propose possible solutions on how to maintain a level of security that will benefit road users, OEMs and regulators, covering the cybersecurity needs for the vehicle’s usable life, taking into account the vehicle’s heterogeneity of components and technology, connectivity, environmental impact and cost of production and maintenance of a vehicle.

Right chambers deformation after tricuspid edge-to-edge percutaneous repair

Abstract Background The development of new analysis software has allowed to broaden myocardial deformation study to right chambers. There are already reference values for right ventricle (RV) and more recently for right atrium (RA). Tricuspid edge-to-edge repair (TEER) potentially causes changes in right chambers mechanics. Purpose Our aim is to evaluate the impact of TEER in the myocardial deformation of RV and RA. Methods Observational retrospective study including all the consecutive patients undergoing TEER in our tertiary centre. Additionally, a control group of healthy volunteers was included. Baseline and 3 months postprocedural echocardiograms were analyzed with a dedicated software to obtain RV, free wall (FW-) and 4 chambers (4C-) global longitudinal strain (GLS), and RA, reservoir (SrRA), conduit (ScdRA) and centrality (SctRA) strains , deformation values. Interobserver variability was evaluated in the control group with the intraclass correlation coefficient (ICC). Differences in baseline values between cases and control group were evaluated with Mann-Whitney U test. Evolutive changes in deformation parameters were studied using paired Wilcoxon W test. Results 15 healthy controls and 29 patients undergoing TEER (79.3% female, 79 [75-82] years-old) were included. Baseline tricuspid regurgitation (TR) was severe in 21 (72.4%), whereas the others were massive or torrential, and the most frequent mechanism was functional (22, 75,9%). Interobserver agreement in the control group was excellent for FW-GLS (0.88; p <0.001), SrRA (0.99; p <0.001) y ScdRA (0.93; p <0.001), good for SctRA (0.68; p= 0.019) and insufficient for 4C-SGL (0.36; p= 0.20). RV deformation values were significantly worse in patients than in controls (Table). However, solely FW-GLS showed improvement 3 months after the procedure (-15.7 vs -20.5 %; p= 0.022). Conclusions Right chamber deformation analysis is feasible and significantly reduced in patients undergoing TEER. Nevertheless, percutaneous treatment of TR has scarce effect in mechanics at early phases. Longer follow up may be required to evaluate the impact in right strain parameters. Table. Right chambers myocardial deformation values in healthy controls and patients undergoing TEER.Figure

Mastering Microservices Architecture and Cloud Computing : In-Depth Strategies for Domain-Specific Optimization

This comprehensive article explores the intricate landscape of microservices architecture and cloud computing, specifically focusing on domain-specific optimization strategies. It delves into the foundational principles of microservices, examining their synergistic relationship with cloud technologies and their transformative impact on modern software development. The article addresses critical aspects such as service-to-service communication, API management, and data security in distributed environments. It also investigates the role of cloud-native services, including serverless computing and container orchestration, in enhancing microservices performance. Analyzing real-world case studies and emerging trends, the article highlights how organizations can leverage these technologies to drive innovation and maintain a competitive edge. Key challenges in implementing and managing microservices architectures and strategies for overcoming them are discussed. The research emphasizes the importance of tailoring microservices to specific business needs and provides insights into performance tuning for high-traffic systems. This article offers a forward-looking perspective on the evolution of microservices and cloud computing by exploring future trends and considerations, including the potential impact of emerging technologies like edge computing and artificial intelligence. It serves as a valuable resource for IT professionals, architects, and decision-makers seeking to master these technologies and implement domain-specific optimizations effectively in their organizations.

Enhancing integration testing efficiency through AI-driven combined structural and textual class coupling metric

Integration testing, a critical and resource-intensive phase in the software development lifecycle, can account for up to a high percentage of the total testing cost. Identifying classes with high coupling is crucial for efficient integration testing, as these classes are more susceptible to the impact of maintenance-related changes. This research introduces a novel metric called <i>combined structural and textual class coupling</i> (CSTCC), which harnesses the power of artificial intelligence (AI) techniques to predict and rank the most critical classes in an object-oriented software system. CSTCC integrates structural coupling metrics with <i>latent semantic indexing</i> (LSI)-based textual coupling, providing a comprehensive measure of class coupling. LSI, an information retrieval technique, analyses the semantic relationships between classes based on their textual content, enabling CSTCC to capture both structural and conceptual dependencies, resulting in a more accurate identification of high-risk classes. The effectiveness of the proposed approach is rigorously evaluated using mutation testing on four Java open-source projects, and the results demonstrate that test cases developed based on CSTCC achieve high mutation scores, indicating their ability to detect a significant percentage of integration faults. By focusing testing efforts on high-coupling classes identified by CSTCC, developers can potentially save time and cost during integration testing. The results demonstrate that test cases developed based on CSTCC achieve high mutation scores, ranging from 98% to 100%, indicating their ability to detect a significant percentage of integration faults. Additionally, the approach results in substantial efficiency gains, with a notable reduction in the number of test cases needed, saving up to 33.3% of the testing effort in some cases. By focusing testing efforts on high-coupling classes identified by CSTCC, developers can potentially save time and cost during integration testing. The CSTCC metric provides a novel and effective approach to prioritize testing resources and improve the efficiency of integration testing in object-oriented software systems.