Software Development Projects Research Articles

Expediting Time to Market: Evaluating the Effects of Change Control Board Performance in Emerging Markets

This study aims to assess how the performance of Change Control Boards (CCBs) influences the relationship between requirements uncertainty and the Time to Market (TTM) of software projects in emerging markets. We collected data through a structured questionnaire, conducting surveys in project-based IT organizations across various cities in Pakistan. This research adopts a quantitative approach, employing software project houses as the unit of analysis. We selected 38 software projects out of 50 using a multi-stage sampling method and analyzed the data using Smart PLS 4.0 and SPSS 23. The results reveal that requirements uncertainty has a significant impact on Time to Market (TTM) conditions. Our study concludes that the presence and effective performance of CCBs can substantially reduce TTM. Additionally, higher CCB performance can expedite TTM, particularly when requirements lack precision initially. The study underscores the profound influence of requirements uncertainty on TTM in software projects. It provides organizations with insights into the critical role of CCBs, the consequences of uncontrolled changes in the absence or ineffectiveness of CCBs, and how requirements uncertainty affects software project development and timelines. This research contributes to software management and product development processes by highlighting the importance of requirement engineering during the planning phase to address uncertainty issues and enhance CCB performance.

Compiling Requirements from Models for Early Phase Scope Estimation in Agile Software Development Projects

Inadequate early scope estimation is a common problem in software projects, leading to failures in meeting project requirements. Agile projects usually do not concentrate on a comprehensive requirements analysis and specification before the start of the project, making scope assessment difficult. This paper presents the methodology for facilitating a more accurate early estimation of project scope, based on requirements information gathered in various forms (requirements models and textual descriptions) during the requirements workshop. The requirements from different sources are compiled into one list and reconciled, since they are prepared by a number of participants in the requirements workshop using different notations (UML diagrams, SysML models, Story map) and may have differences in the vocabulary. Reconciliation encompasses the unification of vocabulary, as well as the identification and the removal of overlaps in requirements. The final list of requirements is used to estimate the scope of the project in story points. The estimate can be presented to the client and used as a basis for the project contract. A case study on the application of the proposed methodology is presented, using the animal shelter information system as a development project. It demonstrates that the methodology is viable and can facilitate the gathering of a more extensive set of requirements, thus ensuring a more detailed scope estimation.

Simulating the Software Development Lifecycle: The Waterfall Model

This study employs a simulation-based approach, adapting the waterfall model, to provide estimates for software project and individual phase completion times. Additionally, it pinpoints potential efficiency issues stemming from suboptimal resource levels. We implement our software development lifecycle simulation using SimPy, a Python discrete-event simulation framework. Our model is executed within the context of a software house on 100 projects of varying sizes examining two scenarios. The first provides insight based on an initial set of resources, which reveals the presence of resource bottlenecks, particularly a shortage of programmers for the implementation phase. The second scenario uses a level of resources that would achieve zero-wait time, identified using a stepwise algorithm. The findings illustrate the advantage of using simulations as a safe and effective way to experiment and plan for software development projects. Such simulations allow those managing software development projects to make accurate, evidence-based projections as to phase and project completion times as well as explore the interplay with resources.

Multicriteria Optimization of Software Development Platform Selection

The problem of multicriteria optimization of tech stack selection in a non-linear software development environment is formalized. Approaches to solving the problem based on the formation of a compromise area of local quality criteria, additive convolution of vector criteria and their scalarization are considered. An aggregate quality criterion of the software development platform is proposed. It allows taking into account the nonlinearities of the external environment in the framework of solving the problem of extremal control. The coordinates of the vector criteria are piecewise continuous functions A comparative analysis of various approaches to changing the software development tech stack in the face of significant disturbances in the development tools market has been carried out. The possibilities of boxed solutions, custom development and Open Source software development in ensuring information security of the software development environment are shown. The information stability of a software development project using Less Code tools is established and the advantages of technological solutions are shown. The analysis of the adequacy of the obtained solutions was carried out using the Open Source Less Code of the Jmix platform. The data of a comparative analysis of the budgets of the Less Code platform and custom software from vendors are given, which showed the benefits of using Open Source software development tools for long-term operation of the development platform.

ChatGPT API: Brief overview and integration in Software Development

Powerful natural language processing tools have been developed and since the end of 2022 and so far in 2023 ChatGPT has become the most successful, in this sense this paper provides an overview of the ChatGPT API, addresses how this API can be used effectively in the field of software development, highlighting its key applications and advantages. The results highlight the potential of the ChatGPT API as a valuable tool in software development, offering intelligent and efficient solutions for a variety of applications. It emphasizes the importance of understanding how to integrate and leverage this API effectively, and concludes that its proper implementation can significantly improve the quality and efficiency of software development projects.

Methodology for collective location fixing of observed emergencies by intersection/resection based on mobile telecomunication application with cartographic interface

In modern higher education, it is required not only to prepare students to perform work on finished tasks in the subject area they have studied. It is also necessary to prepare students for independent activities, in which students do not work on ready-made tasks, but, on the contrary, are looking for niches in business, in which they themselves can offer in the subject area they have mastered, business-demanded solutions. This is another area of activity, which also requires development while studying at a university. It can be defined as "entrepreneurial competencies of a student." In recent years, the direction "Startup as a Diploma" has been developing, in which a university graduate protects not conditional academic work, but a real technological project with business prospects, to which the students developing it have ownership rights. The creation and maintenance of such projects changes the relationship between student and teacher, for this activity it is necessary to change the traditional teaching methodology. As a task of teachers, we decided to do the following: Find a subject area related to IT development, in which, due to recent achievements, there are opportunities for fast, technically not very complex technological solutions available to students, with the help of which you can create popular solutions. The work proposes an open source software development project, within which students can, performing tasks that are feasible for themselves, create software applications that are in demand in practice, as well as develop development strategies for related business projects. The project is dedicated to solving the problem of determining the coordinates of observed objects and phenomena based on data entered simultaneously by several users in different places using household mobile devices without using special technological equipment such as theodolites or tacheometers. The authors developed a mobile application, the value of which lies in the fact that in the public field allows you to realize the monitoring potential of the population interested in preventing unwanted or dangerous events and preventing emergency situations; professional allows you to assess the quality of the navigation signal in conditions of possible targeted interference; in the educational aspect organize training in the methods of joint fixation of objects and target designation on educational geopolygons. Currently, the project is being developed by students of the Department of Data Analysis and Machine Learning of the Financial University under the Government of the Russian Federation and the Moscow State University of Geodesy and Cartography. This paper presents a description of the project, the proposed solution architecture. References to source code repositories are given. The results of the pilot versions of the software are given.

Use Case Point Methods For Analysis of Software Development Cost In Information Communication Technology Units of Khairun University

The Information and Communication Technology Unit (ICTU) is a technical implementation unit in the field of information and communication technology development and management. Currently, Khairun University's ICTU is undertaking a software development project, one of which involves creating an application called "Permata". In the process of developing this application, one of the common challenges faced is estimating the project costs for software development, as the developers do not yet have a standard method to determine the costs of software development. The objective of this research is to produce a Use Case Point application for estimating the costs of software development at ICTU, Khairun University. The Use Case Point (UCP) method is derived from the Function Point Analysis (FPA) method and aims to provide a simple estimation method oriented toward software project objects. The software objects involved in this method are Actor Types (UAW), Use Case Weight (UUCW), Technical System Development Complexity (TF), and Development Environment Complexity (EF). The estimated time value for developing the Permata application is 1,389.844855 man-hours, equivalent to approximately 1.904 months. The estimated cost for the Permata application is Rp129,099,127.

Numerical Simulation and Design of Ensemble Learning Based Improved Software Development Effort Estimation System

This research paper proposes a novel approach to improving software development effort estimation by integrating ensemble learning algorithms with numerical simulation techniques. The objective of this study is to design an ensemble learning-based software development effort estimation system that leverages the strengths of multiple algorithms to enhance accuracy and reliability. The proposed system combines the power of ensemble learning, which involves aggregating predictions from multiple models, with numerical simulation techniques that enable the modelling and analysis of complex software development processes. A diverse set of software development projects is collected, encompassing various domains, sizes, and complexities. Ensemble learning algorithms such as Random Forest, Gradient Boosting, Bagging, and AdaBoost are selected for their ability to capture different aspects of the data and produce robust predictions. The proposed system architecture is presented, illustrating the flow of data and components. A model training and evaluation pipeline is developed, enabling the integration of ensemble learning and numerical simulation modules. The system combines the predictions generated by the ensemble models with the simulation results to produce more accurate and reliable effort estimates. The experimental setup involves a comprehensive evaluation of the proposed system. A real-world dataset comprising historical project data is utilized, and various performance metrics, including Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), are employed to assess the effectiveness of the system. The results and analysis demonstrate that the ensemble learning-based effort estimation system outperforms traditional techniques, showcasing its potential to enhance project planning and resource allocation.

The key factors contribute to time pressure in software development projects: A review

The success of software development projects is often hindered by time pressure (TP), leading to decreased productivity, compromised quality, and increased risk of failure. To address this issue, it is crucial to understand the key factors contributing to TP in software development projects. In line with the study's objectives, the review methodology followed the Kitchenham and Charters criteria, and a search strategy encompassed four primary digital databases, namely IEEE, ACM Digital Library, Science Direct, and Springers, resulting in 4,500 relevant sources. After applying inclusion and exclusion criteria, a total of 128 papers were selected for analysis. This paper offers a comprehensive overview of the factors contributing to TP in software development. This study synthesizes the findings from multiple studies to guide practitioners in improving their project management approaches and highlights the significance of enhancing various aspects of the development process. The findings highlight the importance of improving project management, estimation techniques, knowledge, and skills to effectively manage TP. Additionally, managing requirements volatility, setting clear goals and objectives, and reducing distractions and interruptions emerge as crucial strategies for mitigating TP and enhancing project success. Furthermore, selecting software developers based on their personality traits is recommended to foster a work environment conducive to reduced TP and improved software development outcomes. By understanding and addressing these factors, software development teams can alleviate TP and increase the likelihood of successful software products. Implementing these recommendations can contribute to reduced TP, improved project outcomes, and enhanced overall success in software development.

Risk Mitigation and Monitoring Challenges in Software Organizations: A Morphological Analysis

Context: The present body of research on risk mitigation focuses mostly on sparse and dispersed research using various approaches during project development.
 Objectives: This paper's goals are to conceptualize and construct a morphological analysis (MA) framework, examine the literature that has already been published on these risks and how to mitigate them in software development, and identify research gaps that suggest areas for further study.
 Methods: Based on a survey of 102 works, we provide an MA framework. The MA framework, which is composed of five dimensions and 17 variants, identifies 33 distinct research gaps as the maximum number of potential areas for future study. The implications for future research are covered in the paper's conclusion. Risk reduction during the project development process is extremely beneficial for project managers at an organization in delivering high-quality goods on time and within budget.
 Results: Based on a review of the literature, it was discovered that the development of software projects used a very low percentage of official risk mitigation and elimination methods. Research also revealed the significance of people-related risks in the risk mitigation process for the benefit of the organization. Some key research demonstrated experimentation, case studies, and empirical approaches for evaluation. Future work may include examining project managers' perceptions and knowledge of risk management. Managers of software development teams require greater risk-mitigation strategies.
 Conclusion: Scholars and researchers need to put more effort into developing quantitative and intelligent risk models. It is crucial to identify major risks so that they won't compromise the project's future success. In our future work, we can employ more models that are helpful for combining quantitative and intelligent risk models using various AI strategies to reduce hazards.

Process Mining Applied in a Software Project Development with SCRUM and ProM

The software product is high used by the society in general and its development complexity are inputs of this research that gears into the software development processes. The mapping and modelling of software processes, as well as their standardization are not trivial tasks in the industry of software. Therefore, process mining practices can be useful for discovering or validating processes. This article presents a hypothetical software development project that uses the agile SCRUM method, Jira software, Jenkins pipeline and a process mining tool called ProM. As the project team generates many records using the software development tools, these records are considered event logs and it is be used during process mining activities. ProM allows users to identify processes from the event logs and is used with the records generated by Jira and Jenkins. The visualization of a possible process derived from the use of these event logs is presented when using the ProM tool and the Flexible Heuristics Miner algorithm. In conclusion, process mining can be useful to discover or validate existing software processes during the execution of a software project, also allowing these processes to be standardized to be used in future projects.

A method framework for identifying digital resource clusters in software ecosystems

A popular form of modern software development involves co-creation and sharing of digital resources (e.g., API and SDK) by third-party developers in software ecosystems. In doing so, digital resources, software development projects, and developer organizations are networked together and form digital resource clusters (DRCs), which can be closely or loosely related. Management science and innovation research has focused on how organizations use DRCs to innovate their software products and services. However, the network structures of software ecosystems are spatiotemporally complex since digital resources are transitively, heterogeneously, and temporally related. In existing literature, the extent of spatiotemporal complexity has impeded the empirical identification of DRCs. Our research devises a method framework consisting of two steps toward identifying DRCs using machine learning, which we found to be well suited to representing the spatiotemporal characteristics of networked digital resources. First, we devise a spatiotemporal network embedding method that learns and represents temporal, transitive, and heterogeneous networks of software ecosystems. Second, we devise a clustering method that identifies DRCs using the output of our embedding method as input. The performance test experiment results show that our devised method framework is superior to existing conventional methods at identifying DRCs.

Studying the association between Gitcoin’s issues and resolving outcomes

The development of open-source software (OSS) projects usually have been driven through collaborations among contributors and strongly relies on volunteering. Thus, allocating software practitioners (e.g., contributors) to a particular task is non-trivial and draws attention away from the development. Therefore, a number of bug bounty platforms have emerged to address this problem through bounty rewards. Especially, Gitcoin, a new bounty platform, introduces a bounty reward mechanism that allows individual issue owners (backers) to define a reward value using cryptocurrencies rather than using crowdfunding mechanisms. Although a number of studies have investigated the phenomenon on bounty platforms, those rely on different bounty reward systems. Our study thus investigates the association between the Gitcoin bounties and their outcomes (i.e., success and non-success). We empirically study over 4,000 issues with Gitcoin bounties using statistical analysis and machine learning techniques. We also conducted a comparative study with the Bountysource platform to gain insights into the usage of both platforms. Our study highlights the importance of factors such as the length of the project, issue description, type of bounty issue, and the bounty value, which are found to be highly correlated with the outcome of bounty issues. These findings can provide useful guidance to practitioners.Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

Enhancing Software Project Monitoring with Multidimensional Data Repository Mining

Software project development and maintenance activities have been reported in various repositories. The data contained in these repositories have been widely used in various studies on specific problems, e.g., predicting bug appearance, allocating issues to developers, and identifying duplicated issues. Developed analysis schemes are usually based on simplified data models while issue report details are neglected. Confronting this problem requires a deep and wide-ranging exploration of software repository contents adapted to their specificities, which differs significantly from classical data mining. This paper is targeted at three aspects: the structural and semantic exploration of repositories, deriving characteristic features in value and time perspectives, and defining the space of project monitoring goals. The considerations presented demonstrate a holistic image of the project development process, which is useful in the assessment of its efficiency and identification of imperfections. The original analysis introduced in this work was verified using open source and some commercial software project repositories.

Software Engineering: New Methodologies, Tools, and Best Practices in Software Development

Software engineering is a dynamic field that is always evolving to meet the demands of difficult software development projects. This journal article investigates contemporary software engineering methodologies, tools, and best practices in order to enhance the efficiency, quality, and dependability of software development processes. We discuss the most recent advancements in quality assurance, DevOps, agile software development, and automated testing. We also look at the role that cooperation, communication, and project management have in efficient software engineering methods. By highlighting these advances, this article aims to promote the delivery of high-quality software products and improve software development processes.

Incorporating statistical and machine learning techniques into the optimization of correction factors for software development effort estimation

AbstractAccurate effort estimation is necessary for efficient management of software development projects, as it relates to human resource management. Ensemble methods, which employ multiple statistical and machine learning techniques, are more robust, reliable, and accurate effort estimation techniques. This study develops a stacking ensemble model based on optimization correction factors by integrating seven statistical and machine learning techniques (K‐nearest neighbor, random forest, support vector regression, multilayer perception, gradient boosting, linear regression, and decision tree). The grid search optimization method is used to obtain valid search ranges and optimal configuration values, allowing more accurate estimation. We conducted experiments to compare the proposed method with related methods, such as use case points‐based single methods, optimization correction factors‐based single methods, and ensemble methods. The estimation accuracies of the methods were evaluated using statistical tests and unbiased performance measures on a total of four datasets, thus demonstrating the effectiveness of the proposed method more clearly. The proposed method successfully maintained its estimation accuracy across the four experimental datasets and gave the best results in terms of the sum of squares errors, mean absolute error, root mean square error, mean balance relative error, mean inverted balance relative error, median of magnitude of relative error, and percentage of prediction (0.25). The p‐value for the t‐test showed that the proposed method is statistically superior to other methods in terms of estimation accuracy. The results show that the proposed method is a comprehensive approach for improving estimation accuracy and minimizing project risks in the early stages of software development.

A new approach to developing software projects by assigning teams to projects with interval-valued neutrosophic Z numbers

Software development projects are becoming increasingly important to achieve successful results in the global digitalization trend that has spread throughout the world at the time of the pandemic. The main software development methodologies (SDM) are waterfall and agile. This study investigates the achievement of success methodology through the evaluation of software development projects, personnel under the scope of SDM's. Software projects require strong human resources to be successful in terms of on-time completion and success. For software projects that include the human component, it is important to make project team SDM assignments more meaningful and accurate. The power of linguistic variables and the use of expert ratings in such assignments have been the focus of this paper. The reason for the strong representativeness is the conversion of linguistic variables to mathematical fuzzification, Interval Valued Neutrosophic Z-Numbers (NZN) are used to determine which SDM should be used first in projects. The results of the NZN are then incorporated into the NZN-Area model. This replaces the distance measurement equation used to rank alternatives with an area calculation. The NZN-Area Model is the new proposed form of the model. The NZN-Area model produced 22% better results in terms of defect numbers and 25% better results in terms of defect resolution time compared to the NZN method. Additionally, a sensitivity analysis was performed by comparing the NZN method and NZN-Area method with real data. The proposed NZN-Area method was found to be more consistent under variable conditions.

An Empirical Study on Impact of Project Management Constraints in Agile Software Development

Goal: The Study aims to investigate the impact of project management constraints in fixed-cost and fixed-scheduled Agile software development contracts using multigroup analysis (MGA) to perform repeated comparisons of parameters across groups of Scrum or Kanban methodologies using structural equation modelling (SEM) Design/Methodology/Approach: A web-based survey is used to collect responses to a questionnaire based on project management constraints for Kanban and Scrum method-based Agile software development projects from people working on projects fixed-cost and fixed-schedule contracts and then analyzed with the help of multi-group analysis using SmartPLS 4.0 Results: Risk management has a mediating effect between project scope, resources, and delivery quality. MGA implied that the Kanban method is better at managing resources and will have a higher impact on the quality of deliverables than the Scrum method. Limitations of the investigation: Evaluating the suitability of various multi-group analysis approaches requires more than just our empirical example using satisfactory data and other project management constraints. Practical implications: The findings of the study suggest that hypothesis testing should be carried out for a distinct model parameter between study groups, whenever they are comparing more than two group. Originality/Value: This study helps in contributing to exploring PLS route modelling by the introduction of the original non-parametric confidence set approach based on a comparison of parameter estimations and bootstrap confidence intervals. The study investigates the impact of several project management constraints on to fixed-cost Agile software development projects.

Open-Source Software Development in Cheminformatics: A Qualitative Analysis of Rationales

This qualitative research explored the rationales of open-source development in cheminformatics. The objective was to promote open science by mapping out and categorizing the reasons why open-source development is being carried out. This topic is important because cheminformatics has an industrial background and open-source is the key solution in promoting the growth of cheminformatics as an independent academic field. The data consisted of 87 research articles that were analyzed using qualitative content analysis. The analysis produced six rationale categories: (1) Develop New Software, (2) Update Current Features, Tools, or Processes, (3) Improve Usability, (4) Support Open-source Development and Open Science, (5) Fulfill Chemical Information Needs, and (6) Support Chemistry Learning and Teaching. This classification can be used in designing rationales for future software development projects, which is one of the largest research areas in cheminformatics. In particular, there is a need to develop cheminformatics education for which software development can serve as an interesting multidisciplinary framework.

Design and Development of Web-Based Information System Order Monitoring System

PT. Sanityasa Anjaya Daniswara is a technology company operating as a software house in Solo. Efficient monitoring of project progress is essential for improving efficiency. Thus, a monitoring system that allocates programmers, details work, and summarizes progress is urgently required. This study applies the RAD (Rapid Application Development) method to design a monitoring system that meets the company's needs. The result is a development progress monitoring system that provides an overview of work status, ensuring credibility of information, and enhancing productivity and success in software development projects