Software Development Industry Research Articles

Mastering scrum with a focus on team maturity and key components of scrum

Several studies contribute with valuable insights into agile teamwork performance. Currently, Scrum is dominating the industrial agile software development practices. Yet, there is a lack of studies that directly explores the role of team maturity and key components of the Scrum framework on being successful at Scrum. We investigate the impact of team maturity and four categories of the Scrum framework (team composition, Scrum values, Scrum roles, and Scrum events) on the perception of being successful at Scrum. Hence, we uncover and provide deeper insights into the characteristics and practices of what makes a team successful at Scrum. We carry out a large-scale and cross-sectional survey. We conduct Pearson's chi-square test of independence and logistic regression analysis for team maturity and the remaining variables on being successful. After surveying 182 Scrum team members, the results show that being successful at Scrum depends on the team maturity level. Team composition variables (fully allocated, low turnover rates, required skills and expertise, and self-management) and directing work in accordance with Scrum values (openness and courage) have an impact. All three Scrum roles are important. Particularly impactful are the developers’ ability to adapt their plans, the product owners’ mandate to prioritize, and the Scrum masters’ ability to ensure that all events take place. Following all Scrum events has an effect on the perception of being successful at Scrum. This work constitutes a valuable contribution to agile practitioners and organizations who are already involved in agile development or plan to pursue agility. Organizations can influence Scrum teams’ journey towards becoming successful at Scrum by ensuring the stability required to allow team maturation and decision-making relevant to team composition variables. This work also provides reflections that are useful for Scrum teams’ practices and internal dynamics related to values, roles, and events.

Review of ways to apply machine learning methods in software engineering

This article reviews the integration of machine learning (ML) techniques into Software Engineering (SE) across various phases of the software development life cycle (SDLC). The purpose is to investigate the applications of ML in SE, analyze its methodologies, present findings, and draw conclusions regarding its impact. The study categorized ML applications in SE and assessed the performance of various ML algorithms. Authors identified ML applications in SDLC phases, including requirements analysis, design, implementation, testing, and maintenance. ML algorithms, such as supervised and unsupervised learning, are employed for tasks like software requirement identification, design pattern recognition, code generation, and automated testing. In summary, we find that ML-based techniques are experiencing a substantial surge in adoption within the field of software engineering. Nevertheless, it is evident that substantial endeavors are needed to establish thorough comparisons and synergies among these approaches, perform meaningful evaluations grounded in detailed real-world implementations that are applicable to industrial software development. Therefore, our key takeaway is the necessity for a shift in focus towards reproducible research, prioritizing this over isolated novel concepts. Failure to do so may result in the limited practical implementation of these promising applications.

A Literature Review on Agile Methodologies Quality, eXtreme Programming and SCRUM

Agile methodologies have become one of the most applied methods in the software development industry. However, agile methodologies face some challenges such as less documentation and wasting time considering changes. This review presents how the previous studies attempted to cover issues of agile methodologies and the modifications in the performance of agile methodologies. The paper also highlights unresolved issues to get the attention of developers, researchers, and software practitioners

Software Defect Prediction Framework Using Hybrid Software Metric

Software fault prediction is widely used in the software development industry. Moreover, software development has accelerated significantly during this epidemic. However, the main problem is that most fault prediction models disregard object-oriented metrics, and even academician researcher concentrate on predicting software problems early in the development process. This research highlights a procedure that includes an object-oriented metric to predict the software fault at the class level and feature selection techniques to assess the effectiveness of the machine learning algorithm to predict the software fault. This research aims to assess the effectiveness of software fault prediction using feature selection techniques. In the present work, software metric has been used in defect prediction. Feature selection techniques were included for selecting the best feature from the dataset. The results show that process metric had slightly better accuracy than the code metric.

Machine Learning Based Approach for Evaluating Agile Based Methods to Enhance Software Quality

Developing a quality software product is an essential need of the software industry. Software quality comprises of various factors. Therefore, it cannot be measured on the basis of a single variable. Several agile software development methods have evolved all around the world with the passage of time that contribute towards the development of new and improved software methods. The agile processes have started invading the software development industry to provide good quality software in minimal time. As the changes have occurred in the modern day evaluation metrics, the changes have been observed in the agile oriented quality evaluation methods as well. This paper presents a machine learning based approach for evaluating agile based methods for enhancing software quality. This advanced mechanism of processing the data attributes is inspired by SWARA and FDD. The validation and evaluation has been done using statistical and the quantitative parameters.

Low/No-code development platforms and the future of software developers

Low/No-code is a trend in the software development industry that seeks to provide those without specific computer training with easy-to-use tools to create applications or programs to meet a particular business need. In the market, multiple platforms allow users to develop software solutions withsome code or, in some cases, no need for coding. This paper explores the origins of this trend and how it has evolved, and its adoption in software development. The investigation also analyzed the implications of this trend for software professionals over the near future.

Technological trends & software engineering education: a systematic review study

The quality of software engineering education is influenced by the consideration of modern industrial trends, IT trends and software development methodologies. The transition to a new level of industry - “Industry 4.0”, characterized by robotics and cyber-socialization, brings a wave of new, never-before-seen challenges to the field of IT and programming. Under such conditions, it is impos- sible to achieve the desired synergistic effect without the formation of an appropriate informational and educational environment in institutions of higher education. One of the sources of the content of such an environment can be the publications of the world scientific community registered in international scientometric databases. On this basis, it becomes possible not only to provide effective digital educational content, but also to choose and use the latest technological means of learning support. A targeted review of primary sources in the Web of Science Core Collection database made it possible to identify, select, synthesize and evaluate research evidence relevant to the research questions: (i) what technological trends are analyzed in research, (ii) what information technolo- gies are considered in research, (iii) what strategies are reflected in publications to overcome the above challenges of SE teaching and learning. According to the results of the study, we offer to improve the educational and methodological support of software engineering education based on ontological modeling of the integration of the requirements of modern trends in the development of the industry and the IT sector, international recommendations and the capabilities of technological teaching aids. This approach is a good basis for the processes of intellectualization of information systems of the educational environment and the construction of appropriate technological educational tools on their basis.

On business adoption and use of reproducible builds for open and closed source software

Reproducible builds (R-Bs) are software engineering practices that reliably create bit-for-bit identical binary executable files from specified source code. R-Bs are applied in some open source software (OSS) projects and distributions to allow verification that the distributed binary has been built from the released source code. The use of R-Bs has been advocated in software maintenance and R-Bs are applied in the development of some OSS security applications. Nonetheless, industry application of R-Bs appears limited, and we seek to understand whether awareness is low or if significant technical and business reasons prevent wider adoption. Through interviews with software practitioners and business managers, this study explores the utility of applying R-Bs in businesses in the primary and secondary software sectors and the business and technical reasons supporting their adoption. We find businesses use R-Bs in the safety-critical and security domains, and R-Bs are valuable for traceability and support collaborative software development. We also found that R-Bs are valued as engineering processes and are seen as a badge of software quality, but without a tangible value proposition. There are good engineering reasons to use R-Bs in industrial software development, and the principle of establishing correspondence between source code and binary offers opportunities for the development of further applications.

Teaching Guide for Beginnings in DevOps and Continuous Delivery in AWS Focused on the Society 5.0 Skillset

The speed at which technologies evolve means that society needs to increase the adaptability of its production processes, increasing their agility and effectiveness. Japan, as a pioneer of this proposal, launched Society 5.0, focused on the use of technologies to solve social and economic problems. One of the largest sectors with influence on the economy and that stands out for its constant changes, is the software development industry. This article presents a didactic guide that allows the adoption of good development practices, strengthening soft and technical skills through a process of continuous evaluation in students within systems engineering programs. The guide consists of the definition of an architectural model for the construction of a REST API, the definition of a preventive quality model based on DevOps, the configuration of the model and evaluation of application of the model in a course. The implementation of this guide improves the competitiveness of students in relation to their professional profile, providing the industry with better trained people with the potential to improve current software development processes.

The emergence of smart service ecosystems—The role of socio‐technical antecedents and affordances

AbstractAs physical products are increasingly augmented with digital technology, manufacturing firms have become part of the development of so‐called smart products and smart services. As such, manufacturing firms are challenged by new market participants and ecosystem partners, particularly from the software development industry, and by the dynamic nature of business relationships. While the academic literature on the distinctive characteristics of ecosystems, particularly digital ecosystems, is rich, the effect of smart service ecosystems' emergence on the foundation of smart products remains uncertain. This study reports on case study research based on 47 semi‐structured interviews with four companies that participate in an industrial smart service ecosystem. Taking an affordance‐theoretic perspective, we uncover the antecedents of and the process of emergent smart service ecosystems. We find that smart service ecosystems have three socio‐technical antecedents: a shared worldview, structural flexibility and integrity, and architecture of participation. We explain the emergence of smart service ecosystems as the result of specialisation in shared affordances and integration of idiosyncratic affordances into collective affordances. We derive seven propositions regarding the emergence of smart services, outline opportunities for further research, and present practical guidelines for manufacturing firms.

Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method.

In recent years, numerous studies have successfully implemented machine learning strategies in a wide range of application areas. Therefore, several different deep learning models exist, each one tailored to a certain software task. Using deep learning models provides numerous advantages for the software development industry. Testing and maintaining software is a critical concern today. Software engineers have many responsibilities while developing a software system, including coding, testing, and delivering the software to users via the cloud. From this list, it is easy to see that each task calls for extensive organization and preparation, as well as access to a variety of resources. A developer may consult other code repositories, websites with related programming content, and even colleagues for information before attempting to build and test a solution to the problem at hand. In this investigation, we aim to identify the factors that led to developing the recommender. This system analyzes the recommender's performance and provides suggestions for improving the software based on users' opinions.

Export Management Information System: Evidence from Willbes Global Purwadadi Inc.

The case study in this research is the export goods data report at Willbess Global Inc. The purpose of this research is to design an information system for managing data on export goods based on a website at Willbess Global Inc.. This can help the process of inputting export goods data. Willbess Global Inc. always strives to improve its business process services, especially in the field of exporting goods with more systematic data processing. The research method used is the Rational Unified Process (RUP) which is a software engineering method developed by collecting various best practices in the software development industry. RUP uses an object oriented concept, with activities that focus on model development using the Unified Model Language (UML). This research has produced information system functions contained in each process of functional requirements such as managing, deleting, and changing information data on export goods data, data on types of transportation equipment used and data for export goods travel documents.

Factor Prioritization for Effectively Implementing DevOps in Software Development Organizations: A SWOT-AHP Approach

DevOps (development and operations) is a collective and multidisciplinary organizational effort used by many software development organizations to build high-quality software on schedule and within budget. Implementing DevOps is challenging to implement in software organizations. The DevOps literature is far away from providing a guideline for effectively implementing DevOps in software organizations. This study is conducted with the aim to develop a readiness model by investigating the DevOps-related factors that could positively or negatively impact DevOps activities in the software industry. The identified factors are further categorized based on the internal and external aspects of the organization, using the SWOT (strengths, weaknesses, opportunities, threats) framework. This research work is conducted in three different phases: (1) investigating the factors, (2) categorizing the factors using the SWOT framework, and finally, (3) developing an analytic hierarchy process (AHP)-based readiness model of DevOps factors for use in software organizations. The findings would provide a readiness model based on the SWOT framework. The proposed framework could provide a roadmap for organizations in the software development industry to evaluate and improve their implementation approaches to implement a DevOps process.

Challenges of Agile–Crowd Software Development: A Systematic Literature Review

Crowdsourcing is an emerging approach in software development, where software is developed by unknown, heterogeneous people around the globe, via an open call by the employer. Crowdsourcing, when used with agile, faces challenges because of the different development methodologies. Agile development methodology has practices that involve face-to-face frequent interaction, whereas crowdsourcing is a distributed development with no or limited face-to-face interaction. Both concepts are actively being used in the software development industry due to their benefits. However, there is a need to explore the integration of both methodologies for an effective and efficient software development. In this regard, the first step is to identify the challenges of integrating crowdsourcing and agile. In this paper, we intend to identify the possible challenges that may be faced while executing agile along with crowdsourcing. For this, we have conducted a Systematic Literature Review. Five main categories of challenges are presented which are: team issues, coordination and communication issues, organizational issues, project-related issues and task-related issues. A list of possible challenges of Agile–Crowd Software Development (ACSD) is presented in this study.

OntoSuSD: Software engineering approaches integration ontology for sustainable software development

AbstractDifferent software development approaches (SDAs) are developed with broad portfolios of development processes. Each of the approaches has certain exclusive principles, practices, thinking, and values, which are informally represented, implemented, and improperly institutionalized. Ontologies are developed for the representation, assessment, and adaptation of SDAs separately without having a shared terminology which may lead to terminological conflict and confusion affecting the simultaneous representation and implementation in software development industry and academia. The software engineering approaches does not consider and support sustainability as priority concern. However, the approaches have capabilities of supporting sustainable software development in different sustainability aspects. This research article aims for the designing and development of an integrated ontology of software engineering approaches (i.e., agile, lean, and green) named OntoSuSD (ontology for sustainable software development) to support sustainable software development knowledge, awareness, and implementation. The goal of OntoSuSD is to propose, design and develop a formal, generic, consistent, and shared knowledge base containing semantic terminology and description of concepts and relationships generated around the representation and implementation of lean, agile, and green approaches in software development processes, which will facilitate their simultaneous implementation and assessment for sustainable software development. The OntoSuSD is developed using practical ontology engineering methodology by reusing relevant ontologies and explicit concepts and properties are defined to fulfill knowledge requirements and representations of the domain. The OntoSuSD is evaluated, and results infer OntoSuSD has high ontological design, good domain coverage, potential applications and achieves purpose of the ontology development.

Optimization of a stochastic model having erratic server with immediate or delayed repair.

The thought to put forward a queuing model proposed in this work was its pertinence in everyday life wherever we can see the uses of computing and networking systems. Industrial software developers and system managers can consider the results of the model to evolve their system for better results. Here we present a novel queueing model having erratic server with delayed repair and balking. Two distinct breakdowns i.e. active and passive breakdown for the system are also considered with their respective amendments. This model is closely related with the smooth functioning of the system during some internal faults (virus attack, electricity failures etc.). The performance indicators which are utilized in enhancing the service standards are obtained using supplementary variable technique. Using ANFIS soft computing technique we have compared the analytical results with those of neuro fuzzy results. Furthermore single and bi-objective minimization problems are considered and minima is obtained using particle swarm optimization and multi objective genetic algorithm respectively. Also, the minimization problems are shown as a convex programming problem to ensure the global optimality of the result. The proposed approach makes it conceivable to accomplish a relevant harmony between operational expenses and administration quality.

Blockchain-based cyber physical systems: Comprehensive model for challenge assessment

Blockchain as the trust‐enabling technology has supported and transformed cyber-physical systems in recent years. Therefore, many organizations have adopted blockchain-based technology to develop industrial software-product-service systems. However, the implementation of blockchain at the organizational levels can be related with several technical, organizational, legal, financial, and environmental challenges (intra-organizational and inter-organizational). Analysis of these challenges will play a significant role in organizational performance. This study has investigated an extensive list of challenges of software blockchain-based implementation in cyber-physical systems. The proposed comprehensive model is applied to the software development industry in Iran as a case study. Based on the experts’ opinions, challenge identification was conducted via the two-phase fuzzy Delphi method for medium and large organizations. Extensive quantitative and qualitative challenges are evaluated via the efficient best-worst fuzzy method. Obtained results indicate that smart contracts vulnerabilities and deterministic execution of the technical challenge group have the most critical importance and governance of the legal challenge group has the least vital importance. It is mentionable that most technical challenges have higher priority than other considered challenges.

Boundary Value Analysis and Decision Table Testing Methods in Software Testing

Product quality is very important in the software development industry. The quality of the resulting product is strongly influenced by software testing before a software is deployed to customers. If a software has passed the test, it will be able to minimized the occurrence of obstacles when the software is used or operated. There are many software testing methods that can be used, from the black type to box testing and types of white box testing. in this study, a method of the black box testing type is used, namely boundary value analysis and decision table testing. The sample form being tested is part of the software used for the management of pension funds for a pension fund management institution employee. The sample form being tested is the periodic pension benefit claim submission form. then the test is carried out using the boundary value method analysis and decision table testing. Based on the business process rules of entry and form validation, a test scenario and data are created to be used for testing. After going through the testing process, the results showed that there were still things that needed to be improved on the sample form.

Items and Constructs of Blockchain Adoption in Software Development Industry: Experts Perspective

The use of Blockchain is becoming a matter of increasing importance, yet the software development industry has not given Blockchain adoption enough consideration. As a result of their inability to modify their software process within the project life cycle, many software development companies struggle to [adopt Blockchain technology. This is because Blockchain Oriented Software (BOS) and its projects have distinctive characteristics that are distinct from traditional software and projects. The constructs and their items to adopt Blockchain in Software development industry have not been identified or investigated. This study aimed to identify technological, organizational, and environmental constructs and their items to adopt Blockchain. Utilizing a quantitative validation approach, 10 interviews and 25 assessment questionnaires were analyzed. The results reveal the identified technological, organizational, and environmental constructs and their items to adopt Blockchain. Experts unanimously agreed with Content Validity Ratio (CVR) results. According to most evaluation questionnaire forms and interview transcripts, the top technological construct was “Trialability” and the top organizational construct was “Cost” while the top environmental construct was “Market Dynamics.” All other constructs and their items were applicable, as indicated by most evaluation questionnaire forms and interview transcripts. This research gives a comprehensive list of technological, organizational, and environmental constructs and their items that demand the attention of Blockchain adoption researchers and industry players in the software development sector.

A Conceptual Model of Factors Influencing Customer Relationship Management in Global Software Development: A Client Perspective

The software development industry or organizations increasingly emerging day by day have adopted global software development (GSD) practices due to the large significance of outsourcing. These industries face many challenges due to a lack of understanding customer perspective in the GSD environment. For any organization, the customer is the major stakeholder, and customer relationship management (CRM) plays a vital role in customer satisfaction with software development projects. These challenges create serious risks for any software development project’s success. Thus, CRM is a crucial challenge in the success of software projects in the GSD environment. This research study aims to address the factors that negatively influence CRM implementation in the global context and proposes a conceptual model based on the identified factors for enhancing software product quality. The systematic literature review (SLR) phase investigates the potential barriers to CRM implementation in GSD. Based on identified barriers, an initial conceptual model is developed. The proposed conceptual model is validated using a questionnaire survey of the GSD industry and CRM practitioners of Pakistan. Statistical analysis and several suitable tests are also performed to develop the final conceptual model for CRM implementation in the GSD environment. This research is performed from the client’s perspective. The results are promising and accommodating to avoid any software project failure due to customer-related issues in a GSD environment.