Software Product Development Research Articles

THE METHOD OF FORMING THE CREATIVE TEAM OF IT PROJECT

The specificity of project team formation is determined by the development of project management concepts, changes in society and in production. Management processes that are related to the human factor are a constant subject of interest for scientists. For effective management of IT projects, qualified people with certain competencies are needed, who create the core of the team in order to fulfill the assigned tasks. The future of the project will depend on how efficiently and "correctly" the team will be formed. The work offers the author's vision of the team formation procedure based on competence, psychological and quantitative criteria, taking into account the features of IT projects with a high degree of innovation, which require flexible management tools and self-managed, self-organizing teams. The task of forming a minimally viable IT project team is proposed to be solved by expanding the range of competencies of each member of the project team under the condition of minimizing its quantitative composition. The minimum complete team model of Raymond M. Belbin (idea generator, critic, and executor) was adopted as the basis for the formation of the IT project team. The application of a creative approach to the management of innovative IT projects, namely the design thinking technique, requires the allocation of an additional role - an empath. The generalized method of forming an IT project team with a high degree of innovation, which will use design thinking technology as a leading technology for software product development, is presented in the form of an algorithm.

An Empirical Investigation Into the Influence of Software Communities’ Cultural and Geographical Dispersion on Productivity

Estimating and understanding software development productivity represent crucial tasks for researchers and practitioners. Although different works focused on evaluating the impact of human factors on productivity, a few explored the influence of cultural/geographical diversity in software development communities. More particularly, all previous treatise addresses cultural aspects as abstract concepts without providing a quantitative representation. Improved knowledge of these matters might help project managers to assemble more productive teams and tool vendors to design software analytics toolkits that may better estimate productivity. This paper has the goal of enlarging the existing body of knowledge on the factors affecting productivity by focusing on cultural and geographical dispersion of a development community—namely, how diverse a community is in terms of cultural attitudes and geographical collocation of the members who belong to it. To reach this goal, we performed a mixed-method empirical study. First, we built a statistical model relating dispersion metrics with the productivity of 25 open-source communities on Github. Then, we performed a confirmatory survey with 140 practitioners. The key results of our study indicate that cultural and geographical dispersion considerably impact productivity, thus encouraging managers and practitioners to consider such aspects during all the phases of the software development lifecycle. We conclude our paper by elaborating on the main insights from our analyses and instilling implications that may drive further research.

An Interview with Gail Murphy - 2023 SIGSOFT Awardee

Gail Murphy received the 2023 SIGSOFT Outstanding Research Award for pioneering contributions to recommenders for software engineering and program comprehension that have impacted both theory and practice. She received a Ph.D. in computer science from the University of Washington in 1996 (USA), and she is now a Professor in the Department of Computer Science and Vice-President of Research & Innovation at the University of British Columbia (Canada). Her research interests are in improving the productivity of software developers and knowledge workers by giving them tools to identify, manage and coordinate the information that really matters for their work.

Information needs and presentation in agile software development

Agile software companies applying the DevOps approach require collaboration and information sharing between practitioners in various roles to produce value. Adopting new development practices affects how practitioners collaborate, requiring companies to form a closer connection between business strategy and software development. However, the types of information management, sales, and development needed to plan, evaluate features, and reconcile their expectations with each other need to be clarified. To support practitioners in collaborating and realizing changes to their practices, we investigated what information is needed and how it should be represented to support different stakeholders in their tasks. Compared to earlier research, we adopted a holistic approach—by including practitioners throughout the development process—to better understand the information needs from a broader viewpoint. We conducted six workshops and 12 semi-structured interviews at three Finnish small and medium-sized enterprises from different software domains. Thematic analysis was used to identify information-related issues and information and visualization needs for daily tasks. Three themes were constructed as the result of our analysis. Visual information representation catalyzes stakeholder discussion, and supporting information exchange between stakeholder groups is vital for efficient collaboration in software product development. Additionally, user-centric data collection practices are needed to understand how software products are used and to support practitioners’ daily information needs. We also found that a passive way of representing information, such as a dashboard that would disturb practitioners only when attention is needed, was preferred for daily information needs. The software engineering community should consider reviewing the information needs of practitioners from a more holistic view to better understand how tooling support can benefit information exchange between stakeholder groups when making product development decisions and how those tools should be built to accommodate different stakeholder views.

Искусственный интеллект в системе здравоохранения арктических регионов Российской Федерации

Currently, in the Russian Federation, much attention is paid to the introduction of artificial intelligence technologies into the healthcare system in order to improve the quality of medical care provided. The AI methods support the medical decision-making, it becomes possible to obtain a second opinion for a doctor when determining a diagnosis, which leads to a reduced risk of determining erroneous diagnoses (including missed pathologies). The development of high-tech medical care is a particularly relevant issue for medical institutions in the Arctic regions, which are geographically distributed and remote territories with hard natural and climatic conditions. The solution of this issue is designed to ensure natural sustaina-ble population growth in these regions and increase the life expectancy of the population of the Russian Arctic, including the indigenous peoples of the North. The article considers the positive experience of cooperation between Russian research centers, medical companies and higher educational institutions in the development and implementation of medical software products based on technologies and methods of artificial intelligence on the example of such Arctic territories of Russia as the Yamalo-Nenets Autonomous Okrug, the Republic of Sakha (Yakutia), the Murmansk Oblast, the Republic of Karelia and the Arkhangelsk Oblast.

DEVELOPMENT OF SOFTWARE TO AUTOMATE THE PREPARATION OF THE CLIENT BASE FOR THE FORMATION OF THE EXECUTION ENVIRONMENT UPDATE

The development of software products for process automation is becoming more and more in demand. One of the main directions is the creation of software to automate the preparation of the client base to form the execution environment update, which allows the business to significantly simplify and optimize this process.
 Purpose: describe the development of a program in C# using MS Visual Studio 2019 to automate writing data to a MySQL database and adding them to an HTML page, including receiving data from the user and creating a convenient and intuitive interface.
 Method and methodology of the work: description of the development of a program in C# using MS Visual Studio 2019 to automate writing data to a MySQL database and adding them to an HTML page with a user-friendly interface.
 Results: program with a UI interface has been developed to automate the preparation of the client base for the formation of an update.
 Scope of the results: programming, automation of writing data to a MySQL database and adding it to an HTML page.

Using social media and personality traits to assess software developers' emotional polarity.

Although human factors (e.g., cognitive functions, behaviors and skills, human error models, etc.) are key elements to improve software development productivity and quality, the role of software developers' emotions and their personality traits in software engineering still needs to be studied. A major difficulty is in assessing developers' emotions, leading to the classic problem of having difficulties understanding what cannot be easily measured. Existing approaches to infer emotions, such as facial expressions, self-assessed surveys, and biometric sensors, imply considerable intrusiveness on developers and tend to be used only during normal working periods. This article proposes to assess the feasibility of using social media posts (e.g., developers' posts on Twitter) to accurately determine the polarity of emotions of software developers over extended periods in a non-intrusive manner, allowing the identification of potentially abnormal periods of negative or positive sentiments of developers that may affect software development productivity or software quality. Our results suggested that Twitter data can serve as a valid source for accurately inferring the polarity of emotions. We evaluated 31 combinations of unsupervised lexicon-based techniques using a dataset with 79,029 public posts from Twitter from sixteen software developers, achieving a macro F1-Score of 0.745 and 76.8% of accuracy with the ensemble comprised of SentiStrength, Sentilex-PT, and LIWC2015_PT lexicons. Among other results, we found a statistically significant difference in tweets' polarities posted during working and non-working periods for 31.25% of the participants, suggesting that emotional polarity monitoring outside working hours could also be relevant. We also assessed the Big Five personality traits of the developers and preliminarily used them to ponder the polarities inferences. In this context, Openness, Conscientiousness, and Extraversion were frequently related to neutral and positive posts, while Neuroticism is associated with negative posts. Our results show that the proposed approach is accurate enough to constitute a simple and non-intrusive alternative to existing methods. Tools using this approach can be applied in real software development environments to support software team workers in making decisions to improve the software development process.

An Innovative Approach for Predicting Software Defects by Handling Class Imbalance Problem

From last decade unbalanced data has gained attention as a major challenge for enhancing software quality and reliability. Due to evolution in advanced software development tools and processes, today’s developed software product is much larger and complicated in nature. The software business faces a major issue in maintaining software performance and efficiency as well as cost of handling software issues after deployment of software product. The effectiveness of defect prediction model has been hampered by unbalanced data in terms of data analysis, biased result, model accuracy and decision making. Predicting defects before they affect your software product is one way to cut costs required to maintain software quality. In this study we are proposing model using two level approach for class imbalance problem which will enhance accuracy of prediction model. In the first level, model will balance predictive class at data level by applying sampling method. Second level we will use Random Forest machine learning approach which will create strong classifier for software defect. Hence, we can enhance software defect prediction model accuracy by handling class imbalance issue at data and algorithm level.

Component-Based Test Case Generation and Prioritization Using an Improved Genetic Algorithm

Developing test cases is the most challenging and crucial step in the software testing process. The initial test data must be optimized using a strong optimization technique due to many testing scenarios and poor testing effectiveness. Test prioritization is essential for testing the developed software products in a production line with a restricted budget in terms of time and money. A good understanding of the trade-off between costs (e.g. time and resources needed) and efficiency (e.g. component coverage) is necessary to prioritize test case scenarios for one or more software products. So, this paper proposes an efficient Multi-objective Test Case Generation and Prioritization using an Improved Genetic Algorithm (MTCGP-IGA) in Component-based Software Development (CSD). A random search-based method for creating and prioritizing multi-objective tests has been employed utilizing numerous cost and efficacy criteria. Specifically, the multi-objective optimization comprises maximizing the Prioritized Range of test cases (PR), Pairwise Coverage of Characteristics (PCC), Fault-Finding Capability (FFC), and minimizing Total Implementation Cost (TIC). For this test prioritizing problem, a unique fitness function is constructed with cost-effectiveness metrics. IGA is a robust search technique that exhibits excellent benefits and significant efficacy in resolving challenging issues, including ample space, multiple-peak, stochastic, and universal optimization. Relying on the use of IGA, this paper classifies, computes the objective function, introduces the Nondominated Sorting Genetic Algorithm-II (NSGA-II) method, evaluates each branch’s proximity on the handling route, and arranges the path set to get the best answer. The outcomes demonstrate that the proposed MTCGP-IGA with NSGA-II performed the best than other baseline algorithms in terms of prioritizing the test cases (mean value of 195.2), PCC (mean score of 0.7828), and FFC (mean score of 0.8136).

Development of complex systems of automation of information functions of management of activities of agricultural organizations

The tendencies of deepening automation in solving managerial tasks are shown. The features of the use of ERP systems in various regions of the country, including in agriculture, are considered. Special attention is paid to the most popular software products in the field of integrated control automation. Dynamics and prospects of development of software products of complex automation of management in modern conditions are reflected. The main problems of the transition from foreign automation systems to domestic programs based on the 1C platform are highlighted. Further directions of development of information technologies in enterprise management are shown.

Selection and justification of drilling and blasting parameters using genetic algorithms

Purpose. Using experimental and theoretical studies to justify the rational location of charges of various types and their technological parameters in the fan, taking into account the physical and mechanical properties and structural features of the rocks in the mountain massif. Methodology. In the experiments, an improved method of geostructural analysis of rocks was used to obtain detailed data on their properties, the block structure of the massif, and the type and direction of development of crack systems. Identification of crack systems, their density, intensity, and direction of development of crack systems is carried out on petrographic sections using microscopic analysis, these are used to calculate the average indicator of the cracking coefficient, while the funneling method – the anisotropy coefficient. The justification of the rational location and the number of charges in each fan was performed using the methods of genetic algorithms and the developed software product. Findings. The coefficient of cracking and anisotropy of physical and mechanical properties of uranium ores was calculated, which was 78 cr/sm2 and 1.4, respectively. According to the developed mathematical models and the software product, the optimization problem was solved using genetic algorithms, which determined the main priorities: the location of the charge in the fan according to the structure of the massif and the rational diameter of the well, which helps to limit the number of oversized blocks of reflected ore. Originality. The regularities are established of the change in the anisotropy coefficient from the cracking coefficient, the nature of the distribution and the number of microcracks (cr/sm2) in the quartz grains, which is present in uranium ore according to a linear law, and the output (in %) of oversized blocks during the destruction of uranium ore from the cracking coefficient – according to the polynomial law. For the first time, the optimal location and the number of charges in each fan, the diameter of the wells, taking into account the type of rock, its strength and fissure, and the geometric parameters of the ore deposit, were determined based on the constructed mathematical models and the developed software product. Practical value. The indicated results of the experimental and theoretical studies will form the basis for the development and substantiation of rational parameters of resource-saving and seismically safe methods for breaking strong rocks of complex structure during the extraction of uranium and iron ores by the energy of the explosion in mines.

Application of modified genetic algorithms for solving evolutionary problems of the theory of schedules

Objective. The article proposes ways to modify genetic algorithms used to automate the process of scheduling.Method. The methods of evolutionary calculations, the theory of schedules, genetic algorithms, the developed software product are used in the work.Result. It is established that the construction of the initial GA population for solving the problem is an extremely important criterion for the convergence of the result. It has been established that the two-stage mutation also allows individuals to be adjusted in the right direction, thereby reducing the time required to perform GA work.Conclusion. Studies show that the developed methods of GA modification can greatly affect the performance of software in the automated scheduling of educational institutions, a scheme of GA operation has been developed, methods of GA modification have been presented and tested.

The Impact of the Web Data Access Object (WebDAO) Design Pattern on Productivity

In contemporary software development, it is crucial to adhere to design patterns because well-organized and readily maintainable source code facilitates bug fixes and the development of new features. A carefully selected set of design patterns can have a significant impact on the productivity of software development. Data Access Object (DAO) is a frequently used design pattern that provides an abstraction layer between the application and the database and is present in the back-end. As serverless development arises, more and more applications are using the DAO design pattern, but it has been moved to the front-end. We refer to this pattern as WebDAO. It is evident that the DAO pattern improves development productivity, but it has never been demonstrated for WebDAO. Here, we evaluated the open source Angular projects to determine whether they use WebDAO. For automatic evaluation, we trained a Natural Language Processing (NLP) model that can recognize the WebDAO design pattern with 92% accuracy. On the basis of the results, we analyzed the entire history of the projects and presented how the WebDAO design pattern impacts productivity, taking into account the number of commits, changes, and issues.

Overview of the economic activity of cloud providers and research on the theoretical foundations of cloud computing

Introduction. Cloud services have become an integral part of all modern companies, contributing to business development, providing flexibility and scalability and accelerating business operations, the need to use cloud services will only grow in an environment where everything is constantly changing. With services such as data storage, computing power, and application hosting on the Internet, companies of all sizes can gain a competitive advantage.Providers that provide cloud services offer enterprises several advantages over the traditional approach in the organization of IT infrastructure. For example, one of the main types of cloud services is SaaS, or Software-as-a-Service, this model allows companies to pay only for what they use. This gives certain advantages over the use of its own iron, which requires a significant initial investment and ongoing costs to maintain the system in working order. The flexibility that can be provided by using the services of cloud providers is the ability to scale as needed both vertically, improving cloud hardware configurations, and horizontally, increasing the number of computing machines, it is obvious that such scaling attempts in companies that use their own architecture await significant investments and costs.The purpose of the study is to review the economic activities of cloud service providers, research and study the main aspects of cloud services and describe the basic definitions of cloud computing.Methods are based on the system-logical generalization of the content essence of theoretical aspects regarding the use of cloud services.Results. As a result of the study, definitions and recommendations for using the services of cloud providers were provided. The impact of cloud technologies on business and key performance metrics of software product development were analyzed. The practice of using the services of cloud providers by companies from the IT sector and other industries was studied. In addition, an example of the practical use of a cloud database was developed, using the example of database initialization, which demonstrates the practicality and speed of the process.Prospects. Further research will be aimed at the practical development of an application that uses cloud computing and services of cloud functions, such as authorization and authentication of system and database users.

Vulnerability diffusions in software product networks

AbstractDuring software product development, the combination of digital resources (such as application programming interfaces and software development kits) establishes loose and tight edges between nodes, which form a software product network (SPN). These edges serve as observable conduits that may help practitioners and researchers better understand how vulnerabilities diffuse through SPNs. We apply network theory to analyze data from over 12 years of records extracted from the National Vulnerability Database. We contribute novel measures established using machine learning to gauge the properties influencing vulnerability diffusion within an SPN. We observed an SPN having a discernable shape that changed over time via network updates. We propose hypotheses and find empirical evidence that vulnerability diffusion is influenced by edge dynamics, developer responses, and their interaction. Implications for practice are that increased developer responses reduce software vulnerability diffusion attributed to edge dynamics.

Prioritization of technology commercialization success factors using fuzzy best worst method

The existence of intense competition in the global market has pressurized organizations to increasingly survive. Many universities strive to create technologies because of their enormous influence on the universities’ development and values. However, the success of achieving this task is arduous due to several commercialization-related difficulties assessing the potential of technology commercialization (TC) in universities. The purpose of this study is to identify and prioritize the factors that influence the development and commercialization of software products in universities. The criteria were identified via a literature review and Delphi study. Fuzzy best worst method (BWM) was applied to prioritize the criteria. The outcomes of fuzzy BWM were validated with fuzzy analytic hierarchy process via comparative analysis. The results of the fuzzy BWM revealed the orders of priority of the criteria from the most important to the least important as entrepreneurial capability, funding, R&D capability, networking, marketing, distinctive features, intellectual property protection, motivational aids, and knowledge-sharing culture. However, the comparative analysis of the outcomes for the 2 multi-criteria decision-making methods indicated that the rankings of the criteria are the same except for the changes between the sixth and seventh criteria. The difference in subjectivities among the experts based on their diverse backgrounds could be a factor contributing to this disparity. This research contributes to existing research by identifying and prioritizing the criteria that influence the performance of TC which have not been previously addressed by using fuzzy BWM. Fuzzy BWM was established to be more consistent and efficient in the decision-making process.

Автоматизация и цифровизация ультразвуковых технологических процессов

Having analyzed the literature sources, it is revealed that digital production includes not only full automation of production processes, but also the creation of a multi-level infrastructure for their control on the basis of information technologies. Technical solutions based on this approach will significantly intensify production processes. The possibilities of automation and digitalization of ultrasonic technological processes are viewed through the creation of a hardware and software com-plex that includes technological and measuring equipment, as well as software to select the most effective technical solu-tions. Some general principles of creating ultrasonic technologies are substantiated, their stages of development include setting the task, analysis of the processing object, selection of the processing scheme and equipment, process control and quality monitoring. Methodological approaches to the implementation of production processes with a multi-level process control infrastructure based on information technologies are proposed. Examples of developed software products are given, with the help of which search engine optimization methods are used to select equipment and rational processing modes. It shows not only the possibility of using automated technology, but also the creation of a self-learning technological system based on it. The development and creation of equipment for the implementation of the proposed technical solutions has in its basis general principles of using numerical control software. The proposed algorithm can be used for a wide range of ultra-sonic technologies: cleaning, surface plastic deformation, coating, cutting, etc. In addition, the combination of the choice of technical and information solutions makes quick switch from one type of processing to another possible. Recommendations on the implementation of the proposed technical and information solutions are given.

USING THE BEHAVIOR ANTAGONISM AND THE BIMATRIX GAME THEORY IN THE IT PROJECT MANAGEMENT

Context. The article proposes a method of analyzing the proposals of team members in order to avoid conflict situations at the stage of team formation.
 Objective. The object of the study is the method of analyzing the proposals of team members while solving project tasks.
 The purpose of the work is to analyze the developed method of analysis of proposals of team members to avoid or resolve conflict situations at the stage of team activation
 Method. The developed method is based on the theory of matrix games. Conflicts between individual team members mainly arise at the stage of team formation. For the project manager, it is important to identify the conflict situation in time and find a way out of it to satisfy both team members and without harming the teamwork as a whole. A team created to implement an IT project is often faced with a situation where two of its members have different visions of approaches to creating the final product. At the same time, each of them has experience in the development of similar software products or services by different teams. To effectively solve this situation, we suggest using approaches typical of bimatrix games, when each of these team members is considered as a player. This takes into account the fact that the bimatrix theory of games is based on a conflict between two players whose interests are opposite – an antagonistic zero-sum game is precisely the basis of the developed approach.
 Results. The proposed method of analysis of proposals of team members contributes to the avoidance or resolution of conflict situations at the stage of their closer interaction. For efficient solution of the said situation, we propose to use approaches being typical for bimatrix games when each of these team members is treated as a player. At the same time, account is taken of the fact that the bimatrix game theory is based on a conflict of two players whose interests are opposite – an antagonistic game with a zero sum being that very element to constitute the basis of the approach developed.
 Conclusions. The given calculation of the model example shows that the use of the proposed method allows the project manager to give a reasonable preference to another team member, since the expected average profit of this player is greater than that of the first player. In this case, the manager has an opportunity to simulate situations for the players (for the team) and promptly respond to probable deviations of their behavioral strategies from the optimal ones, establish healthy relationships between team members and choose the best proposals for solving project tasks.

Characteristics and generative mechanisms of software development productivity distributions

Characteristics and generative mechanisms of software development productivity distributions

Estimated Value of Software Developer Productivity at the Software Implementation Stage Using Function Points

Most Software Development Processes (SDP) project failures occur due to errors in estimating cost, time, and effort during the planning phase. This happened because the planning carried out still relied on the intuition and experience of the programmer. One approach that can be taken to plan the right SDP is to know the value of SDP productivity. The focus of this research is to determine the value of productivity based on the differences in programmers’ skills. The case study is conducted to determine the productivity value of the web-based software that has been built, namely McDelivery. The productivity value is calculated based on the ratio of software size to the effort. Software size is obtained through the calculation of the Application Function Point Count (APFC). Meanwhile, the effort is obtained through expert judgment to determine the time needed by the development team at the junior, middle, and senior software developers to implement software functionality in person-day to the form of program code. The result shows that the productivity value of SDP is directly proportional to the level of ability of the programmers. These productivity values ​​can be used as a solution option to calculate the estimated time, cost, and even the availability of programmers that are adjusted to the conditions faced in planning software development