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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 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]

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]

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]

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]

Effort estimation is fundamental for the development of software projects and critical to their success. The objective of this paper is to understand how Colombian agile practitioners perform effort estimates and to identify opportunities for improvement based on these results. For this purpose, we conducted an exploratory survey study using as instrument an on-line questionnaire answered by agile practitioners with experience in effort estimation. Data was collected from 60 agile practitioners and the main findings are: (1) Agile practitioners prefer non-algorithmic estimation techniques, mainly those based on Expert Judgment. (2) Most of the respondents perceive that their estimates have a medium accuracy level; however, in most cases, no formal analysis of the accuracy level is carried out. (3) The determining effort predictors/cost drivers are characteristics of the project team (size, experience, and skills) and attributes of the software to be built (complexity, type, and domain). (4) The use of datasets for estimation is not common; proprietary datasets predominate and are used for productivity comparisons within the company. (5) Most of the results of related studies are comparable with ours; however, there are significant differences in terms of the roles involved and the techniques used in the effort estimation process. Based on the results and findings of the survey, we identified key opportunities to improve estimation accuracy through (1) software measurement standardization, (2) use of effort datasets, (3) implementation of techniques for measuring accuracy levels, and (4) knowledge management in effort estimation. [ABSTRACT FROM AUTHOR]

Effort estimation based on user stories plays a pivotal role in agile software development, where accurate predictions of project efforts are vital for success. While various supervised ML tools attempt to estimate effort, the prevalence of estimation errors presents significant challenges, as evidenced by the CHAOS report by the Standish Group, which highlights incorrect estimations contributing to a substantial percentage of failed agile projects. This research delves into the domain of user story-based effort estimation in agile software development, aiming to explore the issues arising from inaccurate estimations. The primary goal is to uncover these issues comprehensively and propose potential solutions, thus enhancing the efficacy of the user story-based estimation method. To achieve the research objectives, a systematic literature review (SLR) is conducted, surveying a wide range of sources to gather insights into issues surrounding user story-based effort estimation. The review encompasses diverse estimation methods, user story attributes, and the array of challenges that can result from inaccurate estimations. The SLR reveals a spectrum of issues undermining the accuracy of user story-based effort estimation. It identifies internal factors like communication, team expertise, and composition as crucial determinants of estimation reliability. Consistency in user stories, technical complexities, and task engineering practices also emerge as significant contributors to estimation inaccuracies. The study underscores the interconnectedness of these issues, emphasizing the need for a standardized protocol to minimize inaccuracies and enhance estimation precision. In light of the findings, it becomes evident that addressing the multi-dimensional factors influencing user story-based effort estimation is imperative for successful agile software development. The study underscores the interplay of various aspects, such as team dynamics, task complexity, and requirement engineering, in achieving accurate estimations. By recognizing these challenges and implementing recommended solutions, software development processes can avoid failures and enhance their prospects of success in the agile paradigm. [ABSTRACT FROM AUTHOR]

Highly volatile, uncertain, complex and ambiguous environments (VUCA) complicate and condition project management. With the emergence of agile project management, it is proposed to co-construct it with the client's active participation. Two used agile methodologies are Scrum and Kanban. Scrum is based on executing fast, interactive cycles (Sprints) for the incremental construction of products. Kanban promotes the balance of the continuous workflow through synchronizing tasks and seeking perfection. The combined use of Scrum-Kanban facilitates the integration of the best of both approaches. The Theory of Constraints (TOC) proposes a method for managing constraints in a system (Constraint Management). The Drum-Buffer-Rope (DBR) method and Buffer Management are practical applications of this theory. This study seeks to maximize the continuous flow of value (Throughput) in agile project management by synergistically integrating the DBR method with Scrum-Kanban. The five-step process is implemented for the planning, executing, and controlling the Kanban board in a Scrum Sprint cycle. Four scenarios are evaluated: (1) Balanced Line; (2) Unbalanced Line; (3) Unbalanced Line Modification 1 - Stable, Robust and Fast; and (4) Unbalanced Line Modification 2 - Focusing and Elevation. Measurement of completed work (Kanban cards in the "Done" column) and final inventory for the Sprint cycle reveals that Simulation 4 is the optimal scenario, achieving the highest average "output" ("Done" cards) with reduced inventory ("Doing" cards). The integration of DBR with Scrum-Kanban maximizes the completed work (Throughput) and minimizes the final inventory of the Sprint cycle, which is corroborated by the principle of Little's Law. [ABSTRACT FROM AUTHOR]

The multi-objective dynamic agile earth observation satellite scheduling problem (MO-DAEOSSP) aims to schedule a set of real-time arrival requests and form a reasonable observation plan to satisfy various criteria. According to the requirements in practical applications, the total profit and the average image quality of scheduled requests are taken as optimization goals in this study. Compared to manually designed heuristics and iterative-based methods used in previous research, genetic programming based hyper heuristics (GPHH) can automatically evolve high-quality heuristic rules (HRs) for real-time scheduling without being highly dependent on expert knowledge. In this paper, a knowledge-transfer based multi-objective GPHH framework (KT-MOGP) is proposed, equipped with a heuristic-based simulation considering the idle monitoring, to evolve non-dominated HRs for solving MO-DAEOSSP. The heuristic-based simulation generates feasible schedules and returns fitness values for given HRs, which are the individuals evolved by KT-MOGP. KT-MOGP applies a knowledge transfer mechanism to accelerate convergence. Once a source problem is trained, its non-dominated solutions are extracted and their feature importance is transferred to guide the initialization of another target problem, by which the knowledge generated during the training process can be fully utilized. Experimental results on three sets of instances show that KT-MOGP outperforms the existing GPHH-based method and that the evolved HRs are competitive compared to several classical constructive heuristics and multi-objective evolutionary algorithms. The results also show the effectiveness of the proposed knowledge transfer-based initialization. To the best of our knowledge, this study is the first attempt to consider both multi-objective scenarios and real-time arrival requests. [ABSTRACT FROM AUTHOR]