Effective Software Development Research Articles

The Impact of Teamwork Quality (TWQ) on Agile Software Development Team Performance

Purpose: The study examined the extent to which teamwork quality (TWQ) impacts team performance in the Agile software development space in the U.S. and how the TWQ factors (Communication, coordination of expertise, cohesion, trust, mutual support & value sharing) are ranked in terms of importance to team performance Materials and Methods: The study used correlation and regression analysis to determine the degree of the relationship and the effect of the extended TWQ factors on Agile software team performance. Additionally, the study assessed the relative importance of the TWQ factors to team performance. Participants in the study included IT workers from the software development team in U.S. companies with in-house teams using the Agile methodology. Data was collected using an online survey through survey monkey. The data was presented through descriptive statistics and analyzed using regression analysis. Findings: The study found all the extended TWQ factors were strongly correlated to the team performance. The analysis showed that a statistically significance predictive relationship exists between the extended TWQ factors and Agile software development team performance. However, only mutual support and value sharing contributed statistically significantly to the model. Among these factors, mutual support was ranked as the most important TWQ factor in relation to team performance, while trust was ranked as the least. Implications to Theory, Practice and Policy: This empirical study tested and extended the TWQ model on team performance in the Agile software development space in the U.S. for software development teams and how these TWQ factors are ranked in terms of importance to team performance. The findings provide insight to project teams and team leaders, product owners, scrum masters, and project managers about the TWQ model from the perspective of agile software development teams. The findings also address the critical TWQ factors that are needed for building effective and efficient Agile software development teams.

Software Testing of eHealth Interventions: Existing Practices and the Future of an Iterative Strategy.

eHealth interventions are becoming a part of standard care, with software solutions increasingly created for patients and health care providers. Testing of eHealth software is important to ensure that the software realizes its goals. Software testing, which is comprised of alpha and beta testing, is critical to establish the effectiveness and usability of the software. In this viewpoint, we explore existing practices for testing software in health care settings. We scanned the literature using search terms related to eHealth software testing (eg, "health alpha testing," "eHealth testing," and "health app usability") to identify practices for testing eHealth software. We could not identify a single standard framework for software testing in health care settings; some articles reported frameworks, while others reported none. In addition, some authors misidentified alpha testing as beta testing and vice versa. There were several different objectives (ie, testing for safety, reliability, or usability) and methods of testing (eg, questionnaires, interviews) reported. Implementation of an iterative strategy in testing can introduce flexible and rapid changes when developing eHealth software. Further investigation into the best approach for software testing in health care settings would aid the development of effective and useful eHealth software, particularly for novice eHealth software developers.

Ensemble Learning Approach for Effective Software Development Effort Estimation with Future Ranking

To provide a client with a high-quality product, software development requires a significant amount of time and effort. Accurate estimates and on-time delivery are requirements for the software industry. The proper effort, resources, time, and schedule needed to complete a software project on a tight budget are estimated by software development effort estimation. To achieve high levels of accuracy and effectiveness while using fewer resources, project managers are improving their use of a model created to evaluate software development efforts properly as a decision-support system. As a result, this paper proposed that a novel model capable of determining precise accuracy of global and large-scale software products be developed with practical efforts. The primary goal of this paper is to develop and apply a practical ensemble approach for predicting software development effort. There are two parts to this study: the first phase uses machine learning models to extract the most useful features from previous studies. The development effort is calculated in the second phase using an advanced ensemble method based on the components of the first phase. The performance of the developed model outperformed the existing models after a controlled experiment was conducted to develop an ensemble model, evaluate it, and tune its parameters.

Effectiveness of Video-based Training for Face-to-face Communication Skills of Software Engineers: Evidence from a Three-year Study

Objectives. Communication skills are crucial for effective software development teams, but those skills are difficult to teach. The goal of our project is to evaluate the effectiveness of teaching face-to-face communication skills using AVW-Space, a platform for video-based learning that provides personalized nudges to support student's engagement during video watching. Participants. The participants in our study are second-year software engineering students. The study was conducted over three years, with students enrolled in a semester-long project course. Study Method. We performed a quasi-experimental study over three years to teach face-to-face communication using AVW-Space, a video-based learning platform. We present the instance of AVW-Space we developed to teach face-to-face communication. Participants watched and commented on 10 videos and later commented on the recording of their own team meeting. In 2020, the participants ( n = 50) did not receive nudges, and we use the data collected that year as control. In 2021 ( n = 49) and 2022 ( n = 48), nudges were provided adaptively to encourage students to write more and higher-quality comments. Findings. The findings from the study show the effectiveness of nudges. We found significant differences in engagement when nudges were provided. Furthermore, there is a causal effect of nudges on the interaction time, the total number of comments written, and the number of high-quality comments, as well as on learning. Finally, participants exposed to nudges reported higher perceived learning. Conclusions. Our research shows the effect of nudges on student engagement and learning while using the instance of AVW-Space for teaching face-to-face communication skills. Future work will explore other soft skills, as well as providing explanations for the decisions made by AVW-Space.

Model-based development of software for network control of automotive vehicles’ equipment

BACKGROUND: Various devices and systems connected via onboard network with electronic control unit are the part of automotive vehicles’ equipment. Such devices and systems, which ensure the operability of a vehicle or are the elements of technological units, having microprocessor control, are based on various physical principles. Designers of such devices and systems may not have sufficient knowledge and experience to develop the software independently, which applies to the development of software for the network control.
 AIM: The development of software for information subsystem of a technical device that interacts with an electronic control unit via onboard network as part of automotive vehicles’ equipment, as well as the demonstration of application of model-based programming tools in this development.
 METHODS: A comprehensive description of technical solutions developed to achieve the listed aims using methods of system analysis and methods for developing and debugging of software is given. According to these methods, model-based programming tools are used as handlers for built-in interface modules of microcontroller and elements of software layout. Software elements for processing received messages, performing actions with the data received in them, as well as generation of response messages have been developed in the C language.
 RESULTS: Software that processes messages received by a device subordinated to an electronic control unit via the CAN network, generates response messages addressed to this unit, and sends them has been developed. The method of access to the receiving buffer of the network interface and priority of software execution are taken into account.
 CONCLUSION: It is shown that model-based programming in combination with programming tools based on structured text is an effective software development technology that is convenient for designers of technical devices and systems based on various physical principles and requiring microprocessor control. In particular, the abovementioned should be attributed to specialists in the field of electrical engineering who develop equipment for automotive vehicles.

Redesigning Graphical User Interface of Open-Source Geospatial Software in a Community-Driven Way: A Case Study of GRASS GIS

Learning to use geographic information system (GIS) software effectively may be intimidating due to the extensive range of features it offers. The GRASS GIS software, in particular, presents additional challenges for first-time users in terms of its complex startup procedure and unique terminology associated with its data structure. On the other hand, a substantial part of the GRASS user community including us as developers recognized and embraced the advantages of the current approach. Given the controversial nature of the whole issue, we decided to actively involve regular users by conducting several formal surveys and by performing usability testing. Throughout this process, we discovered that resolving specific software issues through pure user-centered design is not always feasible, particularly in the context of open-source scientific software where the boundary between users and developers is very fuzzy. To address this challenge, we adopted the user-centered methodology tailored to the requirements of open-source scientific software development, which we refer to as community-driven design. This paper describes the community-driven redesigning process on the GRASS GIS case study and sets a foundation for applying community-driven design in other open-source scientific projects by providing insights into effective software development practices driven by the needs and input of the project’s community.

Comparative Analysis of Software Development Lifecycle Methods in Software Development: A Systematic Literature Review

In the last decades, various Software Development Lifecycle (SDLC) models have been developed to meet the different needs and challenges in the software industry. The purpose of this research is to analyze and compare some of the most common SDLC methods. After the selection and evaluation process is complete, a literature review is carried out by collecting articles, books, and other sources related to the SDLC method. Several main SDLC methods were selected for thorough analysis. Waterfall, Agile and Scrum are some of the methods. Important factors such as flexibility, speed of development, ability to adapt to changing requirements, and project risk are evaluated. The results of the analysis show that each SDLC method has strengths and weaknesses, and that they are appropriate for a variety of situations. While Agile and Scrum methods emphasize flexibility and teamwork, the Waterfall method provides greater structure and clarity to plans. This study aims to determine the best process method for software development. This literature review provides an in-depth understanding of the features, strengths, and weaknesses of various existing SDLC methods. With a better understanding of these methods, organizations can choose the SDLC method that best suits their project needs, thereby increasing the efficiency and effectiveness of software development. This research resulted in a process method that is widely used in software development, namely the Agile method.

$H$-$\phi$ Formulation in Sparselizard Combined With Domain Decomposition Methods for Modeling Superconducting Tapes, Stacks, and Twisted Wires

The growing interest in the modeling of superconductors has led to the development of effective numerical methods and software. One of the most utilized approaches for magnetoquasistatic simulations in applied superconductivity is the $H$ formulation. However, due to the large number of degrees of freedom (DOFs) present when modeling large and complex systems (e.g. large coils for fusion applications, electrical machines, and medical applications) using the standard $H$ formulation on a desktop machine becomes infeasible. The $H$ formulation solves the Faraday's law formulated in terms of the magnetic field intensity $\mathbf{H}$ using edge elements in the whole modeling domain. For this reason, a very high resistivity is assumed for the non-conducting domains, leading to an ill-conditioned system matrix and therefore long computation times. In contrast, the $H$-$\phi$ formulation uses the $H$ formulation in the conducting region, and the $\phi$ formulation (magnetic scalar potential) in the surrounding non-conducting domains, drastically reducing DOFs and computation time. In this work, we use the $H$-$\phi$ formulation in 2D for the magnetothermal (AC losses and quench) analysis of stacks of REBCO tapes. The same approach is extended to a 3D case for the AC loss analysis of a twisted superconducting wire. All the results obtained by simulations in Sparselizard are compared with results obtained with COMSOL. Our custom tool allows us to distribute the simulations over hundreds of CPUs using domain decomposition methods, considerably reducing the simulation times without compromising accuracy.

Reliable machine learning models for estimating effective software development efforts: A comparative analysis

Effort estimation in the software industry is recognized as one of the most critical activities for the success of the overall solution delivery in the software development process. Software Development Effort Estimation (SDEE) predicts the efforts to develop any software project in terms of persons-month or person-hours. Effort prediction in the early stages of the software development life cycle (SDLC) is always been a challenge. The primary objective of this paper is to analyse different machine learning models and to identify a stable and accurate estimation model for efficient effort estimation. The paper performs a comparative analysis, to analyze the performance of eight different machine learning models, with commonly used datasets in the domain of Software Development Effort Estimation, in terms of eight metrics. On performing experiments and comparing metrics, the analysis showed that the various machine learning estimation models outperformed some particular datasets, hence it can be concluded that machine learning boost-up the performance in the domain of SDEE. Moreover, to conclude, the paper also compared the models based upon the first three choices of models and identified Random Forest has comprehensive superiority and stability in terms of accuracy in estimation, followed by other models.

An empirical study of the systemic and technical migration towards microservices

ContextAs many organizations modernize their software architecture and transition to the cloud, migrations towards microservices become more popular. Even though such migrations help to achieve organizational agility and effectiveness in software development, they are also highly complex, long-running, and multi-faceted.ObjectiveIn this study we aim to comprehensively map the journey towards microservices and describe in detail what such a migration entails. In particular, we aim to discuss not only the technical migration, but also the long-term journey of change, on a systemic level.MethodOur research method is an inductive, qualitative study on two data sources. Two main methodological steps take place – interviews and analysis of discussions from StackOverflow. The analysis of both, the 19 interviews and 215 StackOverflow discussions, is based on techniques found in grounded theory.ResultsOur results depict the migration journey, as it materializes within the migrating organization, from structural changes to specific technical changes that take place in the work of engineers. We provide an overview of how microservices migrations take place as well as a deconstruction of high level modes of change to specific solution outcomes. Our theory contains 2 modes of change taking place in migration iterations, 14 activities and 53 solution outcomes of engineers. One of our findings is on the architectural change that is iterative and needs both a long and short term perspective, including both business and technical understanding. In addition, we found that a big proportion of the technical migration has to do with setting up supporting artifacts and changing the paradigm that software is developed.

Heterogeneous Ensemble Model to Optimize Software Effort Estimation Accuracy

The software industry has rapidly expanded, and software development is now essential to the success of many multinational corporations. The demand for complex software systems has also dramatically increased. Effective software development is essential, given the limitations of resources such as money, time, and labor. The cost and effort calculations affect the development process and client needs. Project failure was usually caused by errors in job estimating. Underestimating could have severe repercussions, if the project’s budget ends up being more than anticipated. Project overruns, on the other hand, can also have a detrimental impact on how successfully software projects are finished. Researchers and experts in the field of software are investigating ways to keep management and development productivity at high levels. However, a stand-alone estimation has not produced any noteworthy research results. Over the last decade, the standalone estimating models have revealed inadequacies. Literature suggests opting ensemble models, would yield better results as compared to standalone models. We have proposed a heterogeneous ensemble effort estimation (EEE) model in this research. The proposed model is comprises of standalone estimating models such as 1) Use Case Point, 2) Expert Judgment (EJ) and 3)Artificial neural network (ANN). Finally, using linear combination rules, the effort of each unique base model is combined. We applied our ensemble model on the benchmark dataset i.e. ISBSG using three different variations to avoid biasness. Furthermore, trained models were applied on industry use-cases for cross-validation. The findings of this study demonstrated that, in comparison to stand-alone estimate strategies, the ensemble technique gave better estimation results.

IMPROVING EXISTING HOUSING STOCKS A MODEL WITH ARTIFICIAL SMART SUPPORT

Habitable housing and a healthy environment are a fundamental human right. In ensuring that existing housing stocks are re-acquired with artificial intelligence support, in making them healthy and sustainable, the development of a support intelligent system is the main topic of this study. The improvement of what is present provides a holistic benefit that has a return in economic, social, cultural and environmental contexts. It is increasingly important to take advantage of technology to make predictions and assessments with effective policies as well as effective strategies, algorithms, software development, and simulation in improvement projects. The goal is to preserve the resources and energy we have, reduce waste production to zero, reduce carbon footprint, and use the smart model supported by artificial intelligence in this study. Demolition and rebuilding should only be considered as the last resort, as the growth of environmental, cultural, waste areas, and waste resources and energy waste. Improving robust and functional buildings without demolishing them, adapting structures with cultural value to current technology, ensuring sustainability with a smart system can be achieved. In this study, it is aimed at achieving a ‘Smart Model’, which is supported by artificial intelligence, which is designed in light of examples around the world to evolve existing housing stocks with high environmental impact and resource utilization, into buildings with technology-appropriate equipment that have sustainable properties for resource use.

The Impact of Agile Methodology on Project Success, with a Moderating Role of Person’s Job Fit in the IT Industry of Pakistan

Computing software plays an essential role in almost every sector of the digital age, but the process of efficient software development still faces several challenges. Effective software development methodology can be the difference between the success and failure of a software project. This research aims to evaluate the overall impact of Agile Software Development (ASD) on the individual, organizational, software development, and project management dimensions. For this purpose, we surveyed several software development professionals from a variety of backgrounds (experience, location, and job ranks) to explore the impact of ASD on the IT industry of Pakistan. Our analysis of the collected information is two folds. First, we summarized the findings from our surveys graphically clearly show the opinions of our survey respondents regarding the effectiveness of the Agile methodology for software development. Secondly, we utilized quantitative measures to analyze the same data statistically. A comparison is drawn between the graphical and statistical analysis to verify the reliability of our findings. Our findings suggest the existence of a strong relationship between effective software development and the use of Agile processes. Our analysis shows that the job fit of software development professionals and ASD are critical factors for software development project success in terms of cost, quality, stakeholders satisfaction, and time. Although the study focuses on the IT industry of Pakistan, the findings can be generalized easily to other developing IT industries worldwide.

Object Oriented Programming Approach: A Panacea for Effective Software Development

Object Oriented Programming Approach: A Panacea for Effective Software Development

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.

ПОРІВНЯЛЬНА ОЦІНКА ІСНУЮЧИХ МЕТОДІВ НАВІГАЦІЙНОГО ЗАБЕЗПЕЧЕННЯ ТА ВДОСКОНАЛЕНОГО КОМБІНОВАНОГО МЕТОДУ З ФІЛЬТРОМ ЧАСТИН РАО-БЛЕКВЕЛЛА

The analysis of the research showed that the most effective development of modern autonomous navigation software is the modernization of complexes and systems, improvement of methods and algorithms of software and hardware implementation, which will ensure the efficiency of existing equipment, relevance and reduce financial burden on weapons and military equipment. The development of a modern autonomous navigation system using modern positioning methods and algorithms is one of the priorities, because the existing systems used today, although effective, but in the future may lead to a number of problems and difficulties that will not be solved in a short time. The new solution of the scientific and applied problem, which consists in improving the mathematical and software subsystems for determining the current location of combat reconnaissance vehicles with existing information and control systems, is generalized and substantiated. The paper presents the results of an improved method of determining the current value of coordinates with a filter of Rao-Blackwell parts, which allows to determine the current coordinates of the machine with the required accuracy and conservation of the calculated resource of combat information control system. A comparative evaluation of existing navigation systems and a combined method for determining the current value of coordinates with a filter of Rao-Blackwell parts integrated into the onboard information and control system of the machine. The exact characteristics of the system for determining the current coordinates of the machine that do not exceed half the linear dimensions of the combat vehicle are established. In addition, the estimated power of the processor to perform complex arithmetic tasks in the onboard information and control system. This indicates that by reducing the cumulative error as a result of arithmetic operations in existing algorithms and in the improved method increases the accuracy of the system and reduces the estimated resource of the entire subsystem in the BICS. Keywords: on-board information and control systems, Rao-Blackwell part filter, positioning, autonomous moving object, Kalman filter.

ROLE OF ARTIFICIAL INTELLIGENCE (AI) TOOLS FOR ASSURING QUALITY IN SOFTWARE

Artificial intelligence (AI) plays a significant role in multiple aspects of human life. AI computational and simulation tools have been implemented and tested for computational study and data analysis. In computer science and software engineering, effective and intelligent analysis of the results is necessary. Since AI-based tools are designed for business needs, software engineering organizations use them for software quality assurance (SQA) purposes. A cost-effective and rapid analysis gives a better market-oriented approach for professionals in the software development industry. According to the international report of quality, 64 percent of organizations use AI to optimize business processes within QA strategies. This study highlights software-industry and IT-based approaches in software houses. The software houses in Pakistan selected for investigation are related to SQA. Modern machine learning models have been a part of SQA for the last few years. Furthermore, the study also investigates the AI tools which have been used for SQA. The latest trends and techniques are investigated for better quality assurance. We propose an approach for SQA by applying an AI-based tools survey. AI-based tools provide an effective software development and quality assurance solution. The results show that 70 percent of software houses in Pakistan are not applying AI-based tools to maximize SQA. The comprehensive approaches have been studied to identify basic issues and challenges with adopting AI-based tools for SQA. The future trends and current models of machine learning (ML) are also discussed to verify quality assurance. In addition, machine learning models that are already implemented are used in this work to verify the topic’s authenticity.

Student Behavior Analysis and Research Model Based on Clustering Technology

Now, entering the 21st century, with the continuous improvement of my country’s higher education level, the enrollment rate of all colleges and universities across the country is increasing year by year. Faced with the information management of a large number of students, the workload and work pressure of consultants at various universities have doubled. The rapid and effective development of modern computer software and hardware has also initiated and effectively developed the informatization process of universities. The student management system is the core and foundation of the entire school education management system. This study mainly introduces the application of student behavior analysis and research models based on clustering technology. This paper uses the application research of student behavior analysis and research model based on clustering technology, uses clustering technology to analyze student behavior, and reasonably analyzes the feasibility of KMEANS algorithm and campus data mining. The cluster analysis algorithm is used to divide students into different groups according to the characteristics of the students, and then, data analysis and data association rules’ mining are performed on each group of students. At the same time, the decision tree algorithm is used to predict the future of students based on the historical data of the students and the current data of the students. The development status of the school helps the school to understand the situation of the students in real time, make predictions and warnings for possible situations, provide personalized applications for teachers and students, and provide decision-making support for the management. It can be seen from the experimental analysis that the application of student behavior analysis and research models based on clustering technology has increased the efficiency of student education by 17%. The limitations of student behavior analysis and research on clustering technology provide good applications for the KMEANS algorithm. Analysis, discussion, and summary of the methods and approaches are obtained to enrich the academic research results.

Software Architecture for Planning Educational Scenarios by Applying an Agile Methodology

This paper focuses on research related to the difficulties introduced by academic re-sources management in institutions of Higher Education and specifically in the Fundación Universitaria de Popayán, a private university, where the planning of aca-demic scenarios is performed manually at the beginning of each academic period for an average of 1,776 subjects and suitable location for an average of 8,000 students, which leads to determine the importance of considering a software architecture that theoretically supports software development, physically and logically, allowing de-velopment in a successful and reliable way that reduces errors, costs, and time in the results, specifically for the case study at the Fundación Universitaria de Popayán. Therefore, the research has made it possible to find the need for an architectural vision and a base for the effective development of software, supported by the different views of authors with years of research on the subject. The research itself is supported by the agile design thinking methodology, the basis for meeting the needs of the end user, and where the quality attributes workshop method is included in the prototyping phase, which guarantees to involve stakeholders in advance for the control of quality attributes in the project. This article shows the flaws that arise in the academic scenar-io management process and the importance of establishing, from the architecture and agile methodology, a process that remedies the difficulties of the process performed.

METHOD OF THE IT PROJECT TEAM CREATION BASED ON MAXIMIZING IT’S COMPETENCIES

The use of agile approaches in software development requires the project team to be multifunctional and self‑organized in order to respond effectively to changing project requirements. Therefore information technology project team creation requires a special method. The purpose of the work is to develop a method of IT-project team creation by maximizing it’s competencies taking into account the features of agile approaches to project management. The paper proposes the issue of team creation based on maximizing team competencies under conditions of budget and laboriousness constraints. A method of a project team creation is proposed, which takes into account the requirements of the project, the characteristics of individual candidates, and the general competencies of the team as a whole, as well as the project's limitations on the budget and laboriousness of the project. The proposed approach consists of three stages. At the first stage, a set of candidates is determined, whose competency assessments meet the requirements of the project. In the second stage, team options are formed in accordance with the requirements of the project. The project team creation can take place in several statements. The first statement is to solve the problem of minimizing the distance between the vector of team competencies and the vector of requirements. The second statement of the problem is to solve the problem of maximizing competencies in terms of time and project budget constraints.The third solves the issue of choosing a team according to the chosen setting. Two possible objective functions of the issue are offered. One target function is to create a team that will include candidates with maximum competencies. Such a team will best cope with the requirements that are known at the start of the project. The second target function maximizes the total competencies of the team that exceed a given threshold. As a result, the team will be able to better cope with the changing requirements of the project. The proposed method makes it possible to create an effective software development team that meets the requirements of the project, the values and principles of agile approaches.