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The majority of organizations use an agile software development methodology. Standard analysis and design processes are abandoned due to the enormous demand of generating the product within time and budget. This may result in a lack of high-quality software while components are not constructively reused. The components are identified at a later stage in the majority of component approaches. To address such challenges, a methodology for extracting demand-based domain-specific software components from the repository was developed. The process for reusing current components is described in depth with various domain-specific components, and the suggested framework is for extracting demand-based reusable domain-specific software components. [ABSTRACT FROM AUTHOR]

This article emphasizes the importance of training scientists in software development skills, specifically in the field of computational biology. It highlights the need for open access and accurate implementation of software in scientific research. The article provides guidelines for teaching software engineering skills to researchers, including the emphasis on coding practices and the support for students to develop these practices. It also discusses the benefits of incorporating software engineering into scientific education and provides examples of successful software packages developed by students. The authors encourage graduate training programs to prioritize software development skills and promote sustainable software practices. [Extracted from the article]

The importance of incorporating an agile approach into creating sustainable products has been widely discussed. This approach can enhance innovation integration, improve adaptability to changing development circumstances, and increase the efficiency and quality of the product development process. While many agile methods have originated in the software development context and have been formulated based on successful software projects, they often fail due to incorrect procedures and a lack of acceptance, preventing deep integration into the process. Additionally, decision-making for market evaluation is often hindered by unclear and subjective information. Therefore, this study introduces an extended TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method for sustainable product development. This method leverages the benefits of cloud model theory to address randomness and uncertainty (intrapersonal uncertainty) and the advantages of rough set theory to flexibly handle market demand uncertainty without requiring extra information. The study proposes an integrated weighting method that considers both subjective and objective weights to determine comprehensive criteria weights. It also presents a new framework, named Sustainable Agility of Product Development (SAPD), which aims to evaluate criteria for assessing sustainable product development. To validate the effectiveness of this proposed method, a case study is conducted on small and medium enterprises in China. The obtained results show that the company needs to conduct product structure research and development to realize new product functions. [ABSTRACT FROM AUTHOR]

In this study, we evaluate predictive modelling techniques within project management, employing diverse architectures such as the LSTM, CNN, CNN-LSTM, GRU, MLP, and RNN models. The primary focus is on assessing the precision and consistency of predictions for crucial project parameters, including completion time, required personnel, and estimated costs. Our analysis utilises a comprehensive dataset that encapsulates the complexities inherent in real-world projects, providing a robust basis for evaluating model performance. The findings, presented through detailed tables and comparative charts, underscore the collective success of the models. The LSTM model stands out for its exceptional performance in consistently predicting completion time, personnel requirements, and estimated costs. Quantitative evaluation metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE), corroborate the efficacy of the models. This study offers insights into the success observed, reflecting the potential for further refinement and continuous exploration to enhance the accuracy of predictive models in the ever-evolving landscape of project management. [ABSTRACT FROM AUTHOR]

Advances in software engineering, particularly in Agile software development (ASD), demand innovative approaches to effort estimation due to the volatility in Agile environments. Recent trends have made the automation of story point (SP) estimation increasingly relevant, with significant potential for enhancing accuracy. This study introduces a novel model for software effort estimation (SEE) utilizing a deep learning (DL)-based sentence-BERT (SBERT) model for feature extraction combined with advanced gradient-boosted tree (GBT) algorithms. A comprehensive evaluation shows that the proposed model outperforms standard SEE and state-of-the-art models, demonstrating a mean absolute error (MAE) of 2.15 and a median absolute error (MdAE) of 1.85, representing a 12% improvement over the baseline model and an 18% improvement over the best-performing state-of-the-art model. The standardized accuracy (SA) is 93%, which is 7% higher than the next best model, across a dataset of 31,960 issues from 26 open-source Agile projects. This study contributes to software engineering by offering a more accurate and reliable decision support system for estimating project efforts. [ABSTRACT FROM AUTHOR]

Requirements Agile approaches have transformed engineering. This paper shows how RE in Agile software development has evolved from documentation-heavy to collaborative, adaptable, and customer-focused. Agile was born in the mid-1990s when the industry realized it needed to respond to changing client needs and market volatility. This evolution includes iterative development, client interaction, and emphasizing communication above documentation, as discussed in the paper. By comparing conventional and Agile RE approaches, we demonstrate the benefits of adapting to change, working with customers, and delivering functional software faster. This analysis provides a persuasive description of Agile RE implementation methodologies and resources through a detailed literature review and real-world experiences. User stories and backlog refinement are notable techniques. The research finishes by exploring how these techniques affect team dynamics, project success, and customer satisfaction. RE's Agile difficulties and opportunities are also examined. The findings illuminate RE methods' successful adaptation to Agile projects' dynamic character. Software development is more responsive and effective due to this adaptation.

Contemporary Information systems development (ISD) involves not only implementing a predefined set of requirements but also managing changes that emerge during the development process due to unanticipated business and technical needs. ISD project requirements increasingly become both planned and emergent. ISD teams need delivery capabilities to routinely execute what has been planned, and agile capabilities to sense and respond to changes that emerge during the development project. In other words, ISD teams must effectively manage their abilities to not only routinely deliver software applications that meet defined requirements but also sense and respond to changes emerging during the project. The extant literature has not studied the distinction and relationship between ISD team delivery capability and agility. This study empirically examines the differential effects of ISD team delivery capability and agility on ISD project outcomes. Survey data collected from professionals working on 160 software development projects were used to test the research model and hypotheses. The results suggest that ISD delivery capability positively affects agility, agility positively impacts change-response outcome, and agility mediates the relationship between delivery capability and change-response outcome. [ABSTRACT FROM AUTHOR]

Vehicle-to-grid (V2G) systems play a key role in the integration of electric vehicles (EVs) into smart grids by enabling bidirectional energy flows between EVs and the grid. Optimizing V2G operations poses significant challenges due to the dynamic nature of energy demand, grid constraints, and user preferences. This paper addresses the optimization challenges in V2G systems and explores the use of artificial intelligence (AI) methods to tackle these challenges. The paper provides a comprehensive analysis of existing work on optimization in V2G systems and identifies gaps where AI-driven algorithms, machine learning, metaheuristic extensions, and agile optimization concepts can be applied. Case studies and examples demonstrate the efficacy of AI-driven algorithms in optimizing V2G operations, leading to improved grid stability, cost optimization, and user satisfaction. Furthermore, agile optimization concepts are introduced to enhance flexibility and responsiveness in V2G optimization. The paper concludes with a discussion on the challenges and future directions for integrating AI-driven methods into V2G systems, highlighting the potential for these intelligent algorithms and methods. [ABSTRACT FROM AUTHOR]

Context: In agile transformations, there are many challenges such as alignment between agile practices and the organizational goals and strategies or issues with shifts in how work is organized and executed. One very important challenge but less considered and treated in research are cultural challenges associated with an agile mindset. Although research shows that cultural clashes and general organizational resistance to change are part of the most significant agile adoption barriers. Objective: We identify challenges that arise from the interplay between agile culture and organizational culture. In doing so, we tackle this field and come up with important contributions for further research regarding a problem that practitioners face today. Method: This is done with a mixed-method research approach. First, we gathered qualitative data among our network of agile practitioners and derived in sum 15 challenges with agile culture. Then, we conducted quantitative data by means of a questionnaire study with 92 participants. Results:We identified 7 key challenges out of the 15 challenges with agile culture. These key challenges refer to the technical agility (doing agile) and the cultural agility (being agile). The results are presented in type of a conceptual model named the Agile Cultural Challenges (ACuCa). Conclusion: Based on our results, we started deriving future work aspects to do more detailed research on the topic of cultural challenges while transitioning or using agile methods in software development and beyond. [ABSTRACT FROM AUTHOR]

The development of medical technology devices leads to the introduction and use of agile methods, which enable the delivery of increasingly complex software with the fastest possible innovations. Delivery of the highest quality software must be considered during development, as medical products are important elements in saving human lives. Their development begins with determining a set of product requirements that exactly correspond to it. The development of specified medical products is finally delivered to the customer, who participates in the development. In this article, we present the use and combination of agile methods in software development, which correct and facilitate timely and continuous delivery of products. They also know how to smooth out a quick reaction to the customer's changing needs and mainly focus on team management and communication. Specific agile methods make it possible to implement development through gradual improvements by integrating customer requirements towards the product. This article identifies three interconnected approaches to integrating agile methods and principles: SCRUM, SAFe, and Kanban combined with the V-model. The methods are gradually analysed based on the literature review, and the article presents a practical application in Siemens Healthcare Slovakia. [ABSTRACT FROM AUTHOR]

One of the significant challenges in scaling agile software development is organizing software development teams to ensure effective communication among members while equipping them with the capabilities to deliver business value independently. A formal approach to address this challenge involves modeling it as an optimization problem: given a professional staff, how can they be organized to optimize the number of communication channels, considering both intra-team and inter-team channels? In this article, we propose applying a set of bio-inspired algorithms to solve this problem. We introduce an enhancement that incorporates ensemble learning into the resolution process to achieve nearly optimal results. Ensemble learning integrates multiple machine-learning strategies with diverse characteristics to boost optimizer performance. Furthermore, the studied metaheuristics offer an excellent opportunity to explore their linear convergence, contingent on the exploration and exploitation phases. The results produce more precise definitions for team sizes, aligning with industry standards. Our approach demonstrates superior performance compared to the traditional versions of these algorithms. [ABSTRACT FROM AUTHOR]

Scrum has emerged as the most widely used and desired Agile approach for providing corporate strategic competency by establishing a solid foundation for project management. However, there are several issues confronted during its implementation. Some researchers tried to solve specific areas of Scrum issues except only research that covers several aspects without resolving all of them. So, this study presents the EFSP model for improving maintainability, security and reusability. Methodologically, in this study, we carry out the following tasks: (i) apply Mark or 7C model on requirements, and (ii) identify Scrum aspects (artifacts and/or activities) that should be expanded as follows: adding the concept of systematic reusability into sprint planning, classifying the requirements into four layers according to clean architecture into sprint backlog, and evolutionary model into sprint. This model offers solutions to these problems while maintaining the simplicity and flexibility of Scrum. The system evaluation results have achieved an improvement in maintainability by reducing technical debt from 1.6% to 0.9%, security from 10 to 3, timeliness from 5 to 2, and improving team productivity from 1.24 to 2.78. The EFSP model may be utilized to develop a standard in other projects. [ABSTRACT FROM AUTHOR]

Agile Software Development (ASD) confronts the challenge of effectively measurement and predicting the capabilities of software engineers and teams to improve individual performance, team efficiency, and project success. This study delves into exploring and identifying gaps and research prospects in assessing and predicting human capabilities within ASD. Thus, we conducted a Systematic Literature Review, building upon a prior review from 2001 to 2016 by different authors. To encompass primary studies published after 2016, we extended to 2022. Further, our study extends the scope of the previous SLR with a new research question to identify key attributes in publications focused on agile team formation. Our findings disclosed new attributes for evaluating and predicting the capabilities of professionals engaged in ASD, such as Openness to Creativity and Agile Adaptation. These attributes boost individual performance, contribute to ameliorated team productivity, and facilitate the precise composition of teams. Moreover, this study expands our prior study, providing more details on capability identification and research design, extends the analysis of attributes and prediction models, provides a more granular discussion of discoveries and comparisons with prior review, and more indepth discussion about practical implications and thoroughly examines study validity. We observed that technical metrics were more prevalent than social and innovative aspects. Also, the study identified the prediction of agile capabilities as an emerging research domain necessitating further scrutiny due to the scarcity of existing models. The majority of studies (78%) supplied detailed metric descriptions, facilitating the evolution of the capabilities repository and supporting future investigations in this domain. Ultimately, these findings can aid agile practitioners in formulating team composition decisions based on individuals’ and teams’ appraised and foreseen abilities.

In the early 2000s, the Agile Manifesto was launched, over time many organizations have sought to use agile methods in projects, bringing to the discussion the issue of the scalability of these methods, considering the practical implications related to the organizational structure, culture, models governance, leadership, and shared management of projects. Brazil has stood out in the adoption and adopted the use of agile project management methodologies. In this context, this research aims to obtain an overview of the adoption and use of agile practices in Brazilian organizations, seeking to deepen the understanding of the methods, techniques and tools used in Brazil. To this end, a survey was carried out among practitioners of agile methods, resulting in 341 completed questionnaires, of which 199 were considered valid. The results indicate that agile practices have been institutionalized and become a current business practice. Regarding the adoption of agile practices in organizations, respondents reported, among other things, that perceived motivations were speed up the delivery of products, improve the ability to manage projects and better serve the clients, and increase productivity. Regarding the benefits perceived by organizations due to the adoption of agile methods, the greater ability to manage changes, shorter product delivery time, and better alignment between the project team and the clients were highlighted. When asked about the indicators used by managers to measure the success of their projects, customer satisfaction, delivery of products, and the creation of value for the business, among other, were highlighted. [ABSTRACT FROM AUTHOR]

The agile approach to software development has significantly impacted the industry, given its ability to cope with requirements. Despite this, many aspects of the agile paradigm's compatibility with various software project characteristics have not been thoroughly researched. To address this lacuna, the study presents a systematic literature review (SLR) that aims to assess the compatibility of the agile methodology with each of the knowledge areas included in the Project Management Body of Knowledge (PMBOK). By employing Machine Learning (ML) text-mining and sentiment analysis techniques, the paper explores the sentiment regarding each PMBOK knowledge area (PM-KA). It thus provides valuable insights to assist practitioners and researchers in assessing the compatibility of the agile methodology with each PM-KA and identifying potential gaps or significant challenges within the agile paradigm. [ABSTRACT FROM AUTHOR]

Managing smart contracts in an Agile software development based on blockchain technology enables project managers to offer rules for software processes to meet the needs and expectations of stakeholders. On the one hand, smart contracts' faster cycle time, lower fraud, and lower fees and charges have ensured that the business logic satisfies the stakeholder's criteria. Agile approaches, on the other hand, are development processes that use incremental and iterative engineering methodologies to drive the system life cycle. Such methodologies are typically well-suited for incorporating and adapting management ideas early in the development life cycle. To reconcile both viewpoints, this work provides an organization modeling for constructing smart contracts on the blockchain utilizing organizational modeling techniques that allow all processes as well as the smart contracts management discipline in supply chain finance system development to be illustrated. [ABSTRACT FROM AUTHOR]

The primary objective of this investigation is to explore the key factors within a large corporation that facilitate the transition from a conventional hierarchical organizational structure to a more agile one. Although there are studies in the literature on the different agile organizational structures, there are no clear guidelines for a large company to transform to an agile framework. This study employs contingency theory as its framework and specifically focuses on the financial sector to identify both opportunities and challenges encountered during this transformation process. Qualitative research methods were employed, involving an analysis of five case studies in which managers served as respondents. This research contributes to the identification of a model as a guideline for the transformation of the organizational structure towards agility that can provide valuable information for companies undergoing such a transformation. The managers surveyed provided their experience and the competencies of their profiles were validated, in addition to the application of the Delphi method to obtain more objective information. The findings underscore that large companies should refrain from adopting a completely flat hierarchical structure. Moreover, there exists a set of strategic-level elements that serve as a guiding framework for the transformation process. Furthermore, it is essential to acknowledge that the transformation process itself does not follow a one-size-fits-all approach; rather, it is contingent upon the unique context of each individual case, and it is also a cultural challenge. [ABSTRACT FROM AUTHOR]

The impact of projects is vital, from business operations to research to the national economy. Therefore, management science and operation research have extensively studied project scheduling and resource allocation for over six decades. Project databases were proposed to test algorithms, including simulated or real, single or multiprojects, and single-mode or multi-mode projects. However, the dozens of project databases are extremely heterogeneous regarding the file structure and the features of the modeled projects. Furthermore, the efficiency and performance of project scheduling and resource allocation algorithms are susceptible to the characteristics of projects. Therefore, the proposed Compound Matrix-Based Project Database (CMPD) collects and consolidates the most frequently used project databases. The proposed Unified Matrix-Based Project-Planning Model (UMP) sparse matrix-based model enables the addition of new features to existing project structures, such as completion priorities, structural flexibility, and quality parameters, to broaden the scope of considered projects and to take account of flexible approaches, such as agile, extreme, and hybrid projects. [ABSTRACT FROM AUTHOR]

Software Development based on Scrum Agile in a distributed development environment plays a pivotal role in the contemporary software industry by facilitating software development across geographic boundaries. However, in the past different frameworks utilized to address the challenges like communication and collaboration in scrum agile distributed software development (SADSD) were notably inadequate in transparency, security, traceability, geographically dispersed location work agreements, geographically dispersed teamwork effectiveness, and trust. These deficiencies frequently resulted in delays in software development and deployment, customer dissatisfaction, canceled agreements, project failures, and disputes over payments between customers and development teams. To address these challenges of SADSD, this paper proposes a new framework called ChainAgile, which leverages blockchain technology. ChainAgile employs a private Ethereum blockchain to facilitate the execution of smart contracts. These smart contracts cover a range of functions, including acceptance testing, secure payments, requirement verification, task prioritization, sprint backlog, user story design and development and payments with the automated distribution of payments via digital wallets to development teams. Moreover, in the ChainAgile framework, smart contracts also play a pivotal role in automatically imposing penalties on customers for making late payments or for no payments and penalties on developers for completing the tasks that exceed their deadlines. Furthermore, ChainAgile effectively addresses the scalability limitations intrinsic in blockchain technology by incorporating the Interplanetary File System (IPFS) is used for storage solutions as an off-chain mechanism. The experimental results conclusively show that this innovative approach substantially improves transparency, traceability, coordination, communication, security, and trust for both customers and developers engaged in scrum agile distributed software development (SADSD). [ABSTRACT FROM AUTHOR]

Self-supervised learning (SSL) is a potential deep learning (DL) technique that uses massive volumes of unlabeled data to train neural networks. SSL techniques have evolved in response to the poor classification performance of conventional and even modern machine learning (ML) and DL models of enormous unlabeled data produced periodically in different disciplines. However, the literature does not fully address SSL's practicalities and workabilities necessary for industrial engineering and medicine. Accordingly, this thorough review is administered to identify these prominent possibilities for prediction, focusing on industrial and medical fields. This extensive survey, with its pivotal outcomes, could support industrial engineers and medical personnel in efficiently predicting machinery faults and patients' ailments without referring to traditional numerical models that require massive computational budgets, time, storage, and effort for data annotation. Additionally, the review's numerous addressed ideas could encourage industry and healthcare actors to take SSL principles into an agile application to achieve precise maintenance prognostics and illness diagnosis with remarkable levels of accuracy and feasibility, simulating functional human thinking and cognition without compromising prediction efficacy. [ABSTRACT FROM AUTHOR]

The agile methodology stands out as a prevalent model for efficient software development, particularly favored for its adaptability and suitability in small-scale projects across various software industries. Nevertheless, its widespread adoption has brought to light certain communication challenges, particularly when applied to large-scale distributed teams. Agile, it appears, may not be the optimal choice for extensive teams engaged in global software development efforts. This study delves into the intricacies of issues faced by teams employing agile in the context of large-scale distributed development, particularly focusing on communication-related challenges and their repercussions. Our approach involved in-depth interviews with diverse developers and teams hailing from various sectors within the software industry. Moreover, we conducted an extensive quantitative analysis, surveying 50 developers representing different distributed teams. The outcomes of our investigation unearthed several communication-related deficiencies that significantly impact the development process. To arrive at these insights, we employed two robust statistical analysis methods: descriptive analysis and regression analysis. The implications of our findings have led us to propose innovative software solutions, bearing distinctive features engineered to mitigate the communication issues often encountered in large-scale software development. These solutions have the potential to enhance the efficiency and effectiveness of agile practices when applied in extensive and globally dispersed development endeavors. [ABSTRACT FROM AUTHOR]

One of the main obstacles in software development projects is requirement volatility (RV), which is defined as uncertainty or changes in software requirements during the development process. Therefore, this research tries to understand the underlying factors behind the RV and the best practices to reduce it. The methodology used for this research is based upon qualitative research using interviews with 12 participants with experience in agile software development projects. The participants hailed from Austria, Nigeria, the USA, the Philippines, Armenia, Sri Lanka, Germany, Egypt, Canada, and Turkey and held roles such as project managers, software developers, Scrum Masters, testers, business analysts, and product owners. Our findings based on our empirical data revealed six primary factors that cause RV and three main agile practices that help to mitigate it. Theoretically, this study contributes to the body of knowledge relating to RV management. Practically, this research is expected to aid software development teams in comprehending the reasons behind RV and the best practices to effectively minimize it. [ABSTRACT FROM AUTHOR]

Agile Software Development (ASD) confronts the challenge of effectively measurement and predicting the capabilities of software engineers and teams to improve individual performance, team efficiency, and project success. This study delves into exploring and identifying gaps and research prospects in assessing and predicting human capabilities within ASD. Thus, we conducted a Systematic Literature Review, building upon a prior review from 2001 to 2016 by different authors. To encompass primary studies published after 2016, we extended to 2022. Further, our study extends the scope of the previous SLR with a new research question to identify key attributes in publications focused on agile team formation. Our findings disclosed new attributes for evaluating and predicting the capabilities of professionals engaged in ASD, such as Openness to Creativity and Agile Adaptation. These attributes boost individual performance, contribute to ameliorated team productivity, and facilitate the precise composition of teams. Moreover, this study expands our prior study, providing more details on capability identification and research design, extends the analysis of attributes and prediction models, provides a more granular discussion of discoveries and comparisons with prior review, and more indepth discussion about practical implications and thoroughly examines study validity. We observed that technical metrics were more prevalent than social and innovative aspects. Also, the study identified the prediction of agile capabilities as an emerging research domain necessitating further scrutiny due to the scarcity of existing models. The majority of studies (78%) supplied detailed metric descriptions, facilitating the evolution of the capabilities repository and supporting future investigations in this domain. Ultimately, these findings can aid agile practitioners in formulating team composition decisions based on individuals’ and teams’ appraised and foreseen abilities. [ABSTRACT FROM AUTHOR]

In real-time production planning, there are exceptional events that can cause problems and deviations in the production schedule. These circumstances can be solved with real-time production planning, which is able to quickly reschedule the operations at each work centre. Mobile autonomous robots are a key element in this real-time planning and are a fundamental link between production centres. Work centres in Industry 4.0 environments can use current technology, i.e., a biomimetic strategy that emulates echolocation, with the aim of establishing bidirectional communication with other work centres through the application of agile algorithms. Taking advantage of these communication capabilities, the basic idea is to distribute the execution of the algorithm among different work centres that interact like a parasympathetic system that makes automatic movements to reorder the production schedule. The aim is to use algorithms with an optimal solution based on the simplicity of the task distribution, trying to avoid heuristic algorithms or heavy computations. This paper presents the following result: the development of an Industrial Sonar algorithm which allows real-time scheduling and obtains the optimal solution at all times. The objective of this is to reduce the makespan, reduce energy costs and carbon footprint, and reduce the waiting and transport times for autonomous mobile robots using the Internet of Things, cloud computing and machine learning technologies to emulate echolocation. [ABSTRACT FROM AUTHOR]

Developing, implementing, and maintaining a multi-intelligent body collaboration system necessitates significant investments in finances, time, and expertise. While multi-intelligent body collaboration has the potential to enhance power system stability significantly, it also comes with challenges related to interoperability, security, system complexity, and resource allocation. Resource allocation and training costs can be substantial. Addressing these challenges is crucial to harnessing the full benefits of this approach and ensuring the reliable and efficient operation of power systems. Effective communication and coordination strategies among intelligent agents are integral to maintaining power system stability. Timely information exchange, load balancing, disturbance management, and the integration of AI contribute to a more resilient and adaptive energy grid. As technology advances, refining these strategies will be essential to meet the growing demands of an ever-evolving power landscape. As technology marches forward, it becomes increasingly evident that the refinement of these strategies is paramount. The dynamism of the power landscape, driven by technological advancements and evolving needs, necessitates an agile and adaptable power system. The fusion of multiintelligent bodies and modern technology stands as a testament to our collective pursuit of a more reliable, efficient, and sustainable energy future. In this ever-evolving landscape, the innovation and enhancement of these strategies are our compass, guiding us toward a brighter and more efficient future. [ABSTRACT FROM AUTHOR]

Query-time Exploratory Data Analysis (qEDA) is an increasingly demanding aspect of the data analysis process that entails visually and quantitatively summarizing, comprehending, and interpreting the primary characteristics of a dataset. Nowadays, an imperative procedure is popular in relational databases for EDA because it enables us to write multiple dependent declarative queries with imperative logic. As online analytical processing (OLAP) systems contain extremely large datasets, data scientists often need quick visualizations of data, using approximate processing of imperative procedures, before analyzing them in their entirety. We identify gaps in the existing techniques, in that they are unable to sample both declarative-dependent statements and control logic at the same time and perform multi-dependent sampling-based approximate processing within the permitted time in qEDA. Traditional approximate query processing (AQP) involves tuple sampling for a single query approximation and enables queries to be executed over arbitrary random samples of tables. However, available AQP methods cannot produce a further representative sample of the data distribution for the dependent statements to estimate accurately and quickly for multiple dependent statements. On the other hand, sampling control structures, like loops and conditional statements, are discussed separately, without regard to the imperative structure of statements in a procedure. In this study, we propose Forester, a novel agile approximate processing method for imperative procedures that performs imperative program-aware sampling, which includes both statements with control regions (i.e., branch and loop) and processes them approximately within the permitted time in qEDA. Our method produces more targeted samples for each relation, while maintaining the data and control flow of dependent queries and imperative logic and determining all the conditions for a relation across all the statements in the sample that guarantee the existence of relevant data for dependent data distribution. Utilizing a workload of multi-statement imperative procedures from the Transaction Processing Performance Council Decision Support (TPC-DS) database, our experiment demonstrates that Forester outperforms the existing system in sampling, producing minimum error, and improving response time. [ABSTRACT FROM AUTHOR]

Many organizations have adopted agile values and principles in their products and services to provide increasing value to their customers. Although agile started with software development, it has been applicable and used in different industries and disciplines, including the space industry. This article presents the practical implications of teams transitioning to be agile teams using a general inductive analysis of 33 individuals from different NASA agile teams. The findings and recommendations are part of a larger effort performed as part of the development of a model for agile leadership. Some organizations may see agile as very risky and costly, and this article provides some guidance derived from the data to help support planning for agile transformation efforts. • Agile transformations of NASA Agile teams. • Being Agile with a continuous learning mindset. • Ability to create sustainable value to the customer in a technology-driven organization. • Recommendations to becoming Agile organizations. [ABSTRACT FROM AUTHOR]

Digital transformation in the public sector provides digital services to the citizens aiming at increasing their quality of life, as well as the transparency and accountability of a public administration. Since adaptation to the citizens changing needs is central for its success, Agile methodologies seem best suited for the software development of digital services in that area. However, as well documented by an attempt to use Scrum for an important Public Administration in Italy, substantial modifications to standard Agile were needed, giving rise to a new proposal called improved Agile (in short, iAgile). Another notable example is the Scrum@IMI method developed by the City of Barcelona for the deployment of its digital services. However, given the importance of digital transformation in the public sector and the scarcity of efforts (documented in the scholarly literature) to effectively bring Agile within it, a strategically important contribution that Computer Science can offer is a general paradigm describing how to tailor Agile methodologies and, in particular, Scrum, for such a specific context. Our proposal, called Scrum@PA, addresses this strategic need. Based on it, a public administration has a technically sound avenue to follow to adopt Scrum rather than a generic set of guidelines as in the current state of the art. We show the validity of our proposal by describing how the quite successful Scrum@IMI approach can be derived from Scrum@PA. Although iAgile can also be derived from our paradigm, we have chosen Scrum@IMI as a pilot example since it is publicly available on GitHub. [ABSTRACT FROM AUTHOR]

Although there have been some studies on the success factors for IT software projects, there is still a lack of coherent research on the success factors for IT service projects. Therefore, this study aimed to identify and understand the factors and their relationships that contribute to the success of IT service projects. For this purpose, multivariate regressions and structural equation models (SEMs) were developed and analyzed. The regression models included six project management success criteria used as dependent variables (quality of the delivered product, scope realization and requirements, timeliness of delivery, delivery within budget, customer satisfaction, and provider satisfaction) and four independent variables (agile techniques and change management, organization and people, stakeholders and risk analysis, work environment), which had been identified through exploratory factor analysis. The results showed that not all success factors were relevant to all success criteria, and there were differences in their importance. An additional series of exploratory and confirmatory factor analyses along with appropriate statistical measures were employed to evaluate the quality of these four factors. The SEM approach was based on five latent constructs with a total of twenty components. The study suggests that investing in improving people's knowledge and skills, using agile methodologies, creating a supportive work environment, and involving stakeholders in regular risk analysis are important for project management success. The results also suggest that the success factors for IT service projects depend on both traditional and agile approaches. The study extensively compared its findings with similar research and discussed common issues and differences in both the model structures and methodologies applied. The investigation utilized mathematical methods and techniques that are not commonly applied in the field of project management success modeling. The comprehensive methodology that was applied may be helpful to other researchers who are interested in this topic. [ABSTRACT FROM AUTHOR]

Abstract Risk management is often overlooked in the software industry, especially in agile methodology-based projects, which can have negative impacts on the schedule, budget, and quality of a project, eventually leading to customer dissatisfaction. Hence, it is essential to identify the risks and prioritize them based on their level of importance. This study has utilized the Analytic Hierarchy Process (AHP) methodology for prioritizing the software risk factors identified during our previously executed risk identification phase experimental study in small and medium software enterprises that follow agile and traditional methodologies for software development. Among the 16 risk factors categorized under four different risk natures named 'difficulties', 'changes', 'mistakes', and 'challenges', the 'challenges' risk nature category is found to be the most significant one by the research findings, followed by 'difficulties', 'mistakes', and 'changes' risk natures. The results also highlight that 'proper utilization of funds', 'complicated tasks', and 'convincing the customer with alternative technologies' are the most significant risk factors. The study gives an insight into the possible risk factors in a software environment, along with their significance. [ABSTRACT FROM AUTHOR]

Background: In Agile software development, an essential initial stage is eliciting software requirements. This process engages stakeholders to achieve comprehensive results. However, a common issue is the variance in domain and technical knowledge among stakeholders, potentially impacting the quality of software requirements elicitation. Objective: Understanding the characteristics of user stories produced by stakeholders becomes crucial, particularly considering the differences in domain and technical knowledge. This study aims to compare the characteristics of user stories generated by stakeholders with varying backgrounds in domain and technical expertise. Methods: The initial step involves categorizing respondents into distinct stakeholder groups. Three stakeholders are involved in this study, constituting a combination of those with high and low technical and domain knowledge. Subsequently, data collection of user stories is conducted across various case studies. Finally, the acquired user stories are analyzed for further insights. Results: The analysis reveals variations in user stories generated by the three stakeholder categories across the three case studies. Stakeholders with domain knowledge tend to focus on 'what' aspects with task elements and 'why' aspects with hard-goal elements. Meanwhile, technical knowledge crafts user stories with capability elements in the 'what' aspect. Utilizing the QUS framework, it is evident that technical knowledge consistently produces a higher number of high-quality user stories across all quality categories. Conclusion: The contribution offered by this study lies in determining the distinct characteristics of user stories produced by different types of stakeholders, focusing on disparities in domain and technical knowledge. The study highlights the comparison of various characteristics of user story elements, such as hard-goals, soft-goals, tasks, or capabilities, and assesses the quality of user stories based on the user story framework. Additionally, it endorse the importance of process innovation in shaping the requirements gathering process and subsequently influencing the quality of user stories. [ABSTRACT FROM AUTHOR]

Agile project management pursues repetitive and continuous management through an empirical process control method considering the complexity of the project. This study aimed to propose a collaborative Building Information Modeling (BIM)-based work process, focusing on construction coordination tasks among participants during the construction phase of a project. The theoretical framework chosen for this endeavor was the Scrum framework, selected after analyzing previous research to align with the specific characteristics of construction coordination. Using the Scrum framework as a foundation, the study employed the exCPM methodology to model the collaborative BIM-based construction coordination progress. To validate the model, it underwent a transformation into a Petri-Nets model through the marked graph building block (MGBB) along with established rules for model conversion. The converted model was then subjected to validation through reachability tree analysis. The findings of this study hold applicability to diverse collaboration processes that leverage BIM in the construction industry. [ABSTRACT FROM AUTHOR]

Background: South African insurance companies are under pressure to adapt to the constantly changing environment and customer-changing requirements. Agile software development presents itself as a viable solution for swiftly meeting these demands. However, there is a lack of comprehensive understanding regarding the current utilisation of agile methodologies within the South African insurance sector; this article aims to bridge this gap. Objectives: The purpose of this theme is to fully understand the extensive level of the experience for the participants and the nature of projects the participants have been involved in and lastly time frames of the projects and how long have insurance been using agile methodology. Method: For this study, purposive sampling that involves the selection of the units to be observed based on your own judgement about which ones were the most useful or representative will be applied. The criteria were based on the participants having played a role as stakeholder in a project that has used agile methodology within the selected organisation within the past 3 years to remain relevant to this study purpose. Results: The identified pattens from the respondents showed that agile methodology is currently utilised for the following in the selected insurance company: software upgrades new product new function Conclusion: In summary, the current state of agile methodology utilisation in a South African insurance company is associated with application transformation to cloud computing, work transformation, onboarding of new applicants, environment enhancements, schema amendment, introduction of new product such as sales force, automating insurance claims documents, scheme enhancement, fund anniversary and renewal of people’s schemes. Contribution: This comprehensive research significantly contributes to the body of knowledge, shaping the strategic direction of agile methodologies within software development project environments.

Agile software development (ASD) methods such as Scrum promote collocated team collaboration. However, adopting Scrum in hybrid work environments can pose challenges. Therefore, understanding the positive aspects and challenges of adopting Scrum in hybrid settings and the relevant agile tools and practices is important. Software engineering education should also prepare students with the necessary knowledge and skills for implementing ASD methods in hybrid settings. This study provides insight into implementing Scrum in a hybrid setting, in a course project, discussing its positive aspects, challenges, and relevant project management and communication tools. We used a questionnaire to collect feedback from 12 scrum teams, made up of 59 master’s degree students at the University of Oulu, who developed student well-being prototypes in four sprints. We applied thematic analysis to analyze the teams’ feedback. We found 16 challenges, 12 positive aspects, and varying ASD practices and tools. Key challenges included scheduling conflicts, communication issues, and estimating efforts. Discord and Microsoft Teams were popular for communication, while JIRA and Trello were favored for agile project management. This study complements software engineering literature with new empirical findings. It reveals practices and tools applicable to software practitioners and start-up teams for effectively adopting scrum in hybrid settings. It also contributes by illustrating the adoption of scrum course projects in hybrid settings and providing recommendations to enhance the design of similar courses. It identifies research gaps, such as the need for tools and practices to improve collaboration and the potential of asynchronous chats in hybrid environments.

This study presents a novel approach to resource allocation in software development teams working with Kanban. The simulation algorithm created in this study takes three types of resources, three types of work, resource capabilities, and a blocking mechanism different from the classic machine breakdown scenario. The data generated by the simulations are used to train a decision tree regression which is integrated into an optimization model as a clearing function. In numerical analysis, the research compares the decision tree clearing function to a straightforward two-step model that only takes the best of the simulation data and finds a resource allocation and a greedy heuristic algorithm which starts from an initial feasible solution and improves it step-by-step. Findings show that the developed decision tree clearing function model outperforms the other two benchmark models in mid and high amounts of data.

Behavior-driven development (BDD) is an Agile testing methodology fostering collaboration among developers, QA analysts, and stakeholders. In this manuscript, we propose a novel approach to enhance BDD practices using large language models (LLMs) to automate acceptance test generation. Our study uses zero and few-shot prompts to evaluate LLMs such as GPT-3.5, GPT-4, Llama-2-13B, and PaLM-2. The paper presents a detailed methodology that includes the dataset, prompt techniques, LLMs, and the evaluation process. The results demonstrate that GPT-3.5 and GPT-4 generate error-free BDD acceptance tests with better performance. The few-shot prompt technique highlights its ability to provide higher accuracy by incorporating examples for in-context learning. Furthermore, the study examines syntax errors, validation accuracy, and comparative analysis of LLMs, revealing their effectiveness in enhancing BDD practices. However, our study acknowledges that there are limitations to the proposed approach. We emphasize that this approach can support collaborative BDD processes and create opportunities for future research into automated BDD acceptance test generation using LLMs.

Privacy requirements engineering acts as a role to systematically elicit privacy requirements from system requirements and legal requirements such as the GDPR. Many methodologies have been proposed, but the majority of them are focused on the waterfall approach, making adopting privacy engineering in agile software development difficult. The other major issue is that the process currently is to a high degree manual. This paper focuses on closing these gaps through the development of a machine learning-based approach for identifying privacy requirements in an agile software development environment, employing natural language processing (NLP) techniques. Our method aims to allow agile teams to focus on functional requirements while NLP tools assist them in generating privacy requirements. The main input for our method is a collection of user stories, which are typically used to identify functional requirements in agile software development. The NLP approach is then used to automate some human-intensive tasks such as identifying personal data and creating data flow diagrams from user stories. The data flow diagram forms the basis for the automatic creation of privacy requirements. Our evaluation shows that our NLP method achieves a fairly good performance in terms of F-Measure. We are also demonstrate the feasibility of our NLP approach in CamperPlus project. Lastly, we are developing a tool to integrate our NLP approach into the privacy requirements engineering pipeline, allowing for manual editing of results so that agile teams can maintain control over the automated approach.

The goal of Digital Transformation of the Public Sector is the achievement of a better quality of life for citizens, via a more responsive and transparent administration and governance. By now it is clear that technological innovation, both in terms of computer architectures and software systems, is a crucial component of it, yet not sufficient. Indeed, a cultural, organizational and legal shift in how public organizations operate and relate to the citizens is also required. Nevertheless, computer scientists can play a key role in such a transformation and, given its impact on Society, it is essential to achieve a broader level of awareness of it and involvement in it of those scientific and professional figures. To this end, a technical map specifically designed for computer scientists, but properly placed in the context of the cultural, organizational and legal changes mentioned above, would be highly beneficial. To date, such a map is missing, to the best of our knowledge. The main contribution of this Tutorial is to provide it, together with a guided tour describing which key technological aspects enable and drive such a transformation. More specifically, based on a careful analysis of the available scholarly literature, that does not seem to include any Computer Science textbook material, a model of such a transformation is proposed, together with carefully selected examples incarnating it to show its validity: the cities of Barcelona and Chicago. Finally, a look at the future of this area is also provided.

Advances in software engineering, particularly in Agile software development (ASD), demand innovative approaches to effort estimation due to the volatility in Agile environments. Recent trends have made the automation of story point (SP) estimation increasingly relevant, with significant potential for enhancing accuracy. This study introduces a novel model for software effort estimation (SEE) utilizing a deep learning (DL)-based sentence-BERT (SBERT) model for feature extraction combined with advanced gradient-boosted tree (GBT) algorithms. A comprehensive evaluation shows that the proposed model outperforms standard SEE and state-of-the-art models, demonstrating a mean absolute error (MAE) of 2.15 and a median absolute error (MdAE) of 1.85, representing a 12% improvement over the baseline model and an 18% improvement over the best-performing state-of-the-art model. The standardized accuracy (SA) is 93%, which is 7% higher than the next best model, across a dataset of 31,960 issues from 26 open-source Agile projects. This study contributes to software engineering by offering a more accurate and reliable decision support system for estimating project efforts.

The forthcoming industrial requirements to ensure increasingly flexible and agile production processes will require an ever-increasing ability to recognise, predict and optimise the state of processes with respect to the planned state. Advanced tools such as Digital Twins (DT) and Cyber Physical Systems (CPS) can help manage and address these problems. This paper presents some results of the authors' research on the adoption of a basic methodology for the design and implementation of Digital Twins aimed at manufacturing applications and subsequent integration into a Cyber Physical Production Systems (CPPS). Reference publications were selected based on the level of detail of DT and CPS architectures. The aim is also to combine methodological development with industrial tools and requirements. The architecture is potentially applicable to different production scenarios. Finally, the first results of application on a scale production line are shown. [ABSTRACT FROM AUTHOR]

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Agile organizations represent a transformation in the search for convergence in relation to the dynamic challenges of the environment, market transformations and the growing complexity of social systems. The objective of this study was to develop a descriptive bibliometric study to identify research trends on agile organizations. Web of Science and Scopus databases were used to retrieve scientific production. Bibliometric indicators of production, collaboration, visibility, and impact were analyzed. The analysis of 150 documents, with the total participation of 340 authors, showed a growth rate of 4% per year in the time interval from 1995 to the beginning of 2023. Dominant trends were identified with respect to the research topic, the first referring to the human factor, organizational innovation and organization and management, and the second, agile methods, agile transformations, agile software development and agile organizations. [ABSTRACT FROM AUTHOR]

Copyright of Revista Tecno Lógicas is the property of Instituto Tecnologico Metropolitano and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Tecno Lógicas is the property of Instituto Tecnologico Metropolitano and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article explores the author's experience as a PhD student studying technology adoption and usage. It emphasizes the importance of studying these topics and draws on ethnographic and ethnomethodological studies. The article also discusses the concept of information infrastructures and their foundation in complexity sciences. It highlights the shift from descriptive analysis to normative and prescriptive guidance for establishing these infrastructures. The text includes references to academic articles on topics such as the design and access of large information spaces, the impact of digitalization on society, and human-machine communication, providing readers with further resources for research in these areas. [Extracted from the article]

Lean production is becoming popular in IT-related industries, including the business processes outsourcing (BPO) industry. Managers of companies try to implement lean principles in software development projects and, as a result, Agile Software Development (ASD) is becoming more common in practice. According to ASD authors, this approach aims to increase employee productivity and provide better working conditions. However, little is known about the experience of working in such conditions. This article aims to analyze the experience of working under ASD conditions in the BPO industry in Poland. Based on interviews with employees and trade unionists in the BPO industry and using Grounded Theory Methodology procedures during the data analysis, three categories of work experiences in the BPO industry were reconstructed. The reconstructed categories are: "enthusiasm," "instrumentalism," and "disenchantment." Modes of experience were determined by biographical work experiences, individual resources, and objective context. [ABSTRACT FROM AUTHOR]

By adopting a systematic literature and science mapping review, this paper aims to explore the impact of artificial intelligence (AI) on organizational justice and project performance. A total of 47 bibliographic records from the Scopus database were analyzed. The results revealed the annual publication trends of research articles and relevant peer-reviewed journals in the studied domain. It was found that while AI technology has made significant progress in several fields, its application areas in project management and organizational justice are still relatively low. Moreover, it objectively discussed the co-occurrence analysis of keywords, co-authors, countries/regions, and documents in the fields, revealing the current research topics. The main research topics include the (1) AI's influence on organizational justice, decision analysis, and digital transformation, (2) fostering organizational justice and AI's role in enhancing project performance, and (3) improving organizational performance approaches. Furthermore, this paper proposed research gaps and future research directions, including (1) advancing business intelligence strategies, (2) unlocking AI technology potential on organizational justice and project performance, (3) the adaption of cultural, diversity, environmental, and social factors, (4) the impact of AI on complex and challenging leadership styles, and (5) developing a comprehensive understanding of the agile framework. The findings of this paper could contribute to a better understanding of how AI shapes project/construction management and organizational justice, providing practical solutions for innovative development for researchers and policymakers. [ABSTRACT FROM AUTHOR]

Scaled agile development approaches are now used widely in modern software engineering, allowing businesses to improve teamwork, productivity, and product quality. The incorporation of artificial intelligence (AI) into scaled agile development methods (SADMs) has emerged as a potential strategy in response to the ongoing demand for simplified procedures and the increasing complexity of software projects. This paper explores the intersection of AI-driven assistants within the context of the scaled agile framework (SAFe) for large-scale software development, as it stands out as the most widely adopted framework. Our paper pursues three principal objectives: (1) an evaluation of the challenges and impediments encountered by organizations during the implementation of SADMs, (2) an assessment of the potential advantages stemming from the incorporation of AI in large-scale contexts, and (3) the compilation of aspects of SADMs that AI-driven assistants enhance. Through a comprehensive systematic literature review, we identified and described 18 distinct challenges that organizations confront. In the course of our research, we pinpointed seven benefits and five challenges associated with the implementation of AI in SADMs. These findings were systematically categorized based on their occurrence either within the development phase or the phases encompassing planning and control. Furthermore, we compiled a list of 15 different AI-driven assistants and tools, subjecting them to a more detailed examination, and employing them to address the challenges we uncovered during our research. One of the key takeaways from this paper is the exceptional versatility and effectiveness of AI-driven assistants, demonstrating their capability to tackle a broader spectrum of problems. In conclusion, this paper not only sheds light on the transformative potential of AI, but also provides invaluable insights for organizations aiming to enhance their agility and management capabilities. [ABSTRACT FROM AUTHOR]