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This article explores historians' role in shaping public policy amid crises through the programs of the Idaho State Historical Society (ISHS). ISHS navigated the post-2008 recession, aligning with the History Relevance Campaign to redefine history's societal value and develop a legislative outreach program. This article encapsulates the ISHS's journey and history's power--through the agency's new briefing paper program--to inform, unite, guide policy, and promote informed governance. The article describes the author's workflow, which features traditional research methodology and adaptable projectmanagement philosophies and stresses the value of searchable research libraries as a framework for historians to manage multiple projects. [ABSTRACT FROM AUTHOR]

Technology has changed the way we work. These have increased the productivity in the workplace. The purpose of having a conference paper app is to aid researcher to improve the effectiveness and efficiency of management of conference paper. Without a proper management of these substances, people might suffer from the inconvenience by using a desktop system to complete certain tasks and monitor them efficiently. However, based on investigating the existing applications, a few shortcomings have been identified. Certain shortcoming leads us to develop a new mobile application to fix the identified shortcomings. Some others include complex navigation of user interfaces, this cause a poor user experience for users. Hence, this project proposes a development of a mobile application that is called CPMA, which serve as a better alternative tool to allow users managing and monitoring information related to conference paper in a more efficient way. This app specifically developed for researchers in higher learning institutions who are needed to proceed with conference paper. Software development methodology named prototyping will be adopted, which consisted of phases such as planning, repeated phases (analysis, design, implementation and system prototype), implementation and final system. The essential significance of this project is to provide a platform for researcher to manage and monitor conference paper in a savvy manner. By the time of completing this project, users are expected to access this application without any costs and increase the efficiency and effectiveness of managing conference paper. To ensure the security is presented in a tabular form for each online marketplace. [ABSTRACT FROM AUTHOR]

Various approaches toward the development of sustainable software systems have been proposed by the requirements engineering community over the last decade. We conducted a systematic mapping study, analyzed 55 publications, and identified 29 approaches that have been published since the year 2000. We analyzed how the approaches evolved over time and how the publications and authors are influenced by each other. Furthermore, the approaches are analyzed in terms of their supported requirements engineering activities, along with the evidence provided in the publications. Additionally, we also analyzed which sustainability definitions have been used, if an iterative application of the approaches is discussed, and if the approaches also provide a tool-support for practitioners. We noticed an increase of publications on requirements engineering approaches toward sustainability in the last years, whereas a majority discuss sustainability based on the same multi-dimensional concept. Although different case studies have been already conducted, we noticed a lack of an industrial application. Our main findings concern the need of an evaluation on how the proposed requirements engineering approaches can also be applied in agile software development processes. Additionally, we also promote the development of supporting software tools to support practitioners in adapting the proposed approaches. [ABSTRACT FROM AUTHOR]

Crowdsourcing is an emerging approach in software development, where software is developed by unknown, heterogeneous people around the globe, via an open call by the employer. Crowdsourcing, when used with agile, faces challenges because of the different development methodologies. Agile development methodology has practices that involve face-to-face frequent interaction, whereas crowdsourcing is a distributed development with no or limited face-to-face interaction. Both concepts are actively being used in the software development industry due to their benefits. However, there is a need to explore the integration of both methodologies for an effective and efficient software development. In this regard, the first step is to identify the challenges of integrating crowdsourcing and agile. In this paper, we intend to identify the possible challenges that may be faced while executing agile along with crowdsourcing. For this, we have conducted a Systematic Literature Review. Five main categories of challenges are presented which are: team issues, coordination and communication issues, organizational issues, project-related issues and task-related issues. A list of possible challenges of Agile–Crowd Software Development (ACSD) is presented in this study. [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]

In the work reported in this paper, a lost-in-space star pattern identification algorithm for agile spacecraft was studied. Generally, the operation of a star tracker is known to exhibit serious degradation or even failure during fast attitude maneuvers. While tracking methods are widely used solutions to handle the dynamic conditions, they require prior information about the initial orientation. Therefore, the tracking methods may not be adequate for autonomy of attitude and control systems. In this paper a novel autonomous identification method for dynamic conditions is proposed. Additional constraints are taken into account that can significantly decrease the number of stars imaged and the centroid accuracy. A strategy combining two existing classes for star pattern identification is proposed. The new approach is intended to provide a unique way to determine the identity of stars that promises robustness against noise and rapid identification. Moreover, representative algorithms implemented in actual space applications were utilized as counterparts to analyze the performance of the proposed method in various scenarios. Numerical simulations show that the proposed method is not only highly robust against positional noise and false stars, but also guarantees fast run-time, which is appropriate for high-speed applications. [ABSTRACT FROM AUTHOR]

One of the main issues of an agile software project is how to accurately estimate development effort. In 2014, a Systematic Literature Review (SLR) regarding this subject was published. The authors concluded that there were several gaps in the literature, such as the low level of accuracy of the techniques and little consensus on appropriate cost drivers. The goal of our work is to provide an updated review of the state of the art based on this reference SLR work. We applied a Forward Snowballing approach, in which our seed set included the former SLR and its selected papers. We identified a strong indication of solutions based on Artificial Intelligence and Machine Learning methods for effort estimation in Agile Software Development (ASD). We also identified that there is a gap in terms of agreement on suitable cost drivers. Thus, we applied Thematic Analysis in the selected papers and identified a representative set of 10 cost drivers for effort estimation. This updated review of the state of the art resulted in 24 new relevant papers selected. [ABSTRACT FROM AUTHOR]

The quality of requirements is typically considered as an important factor for the quality of the end product. For traditional up-front requirements specifications, a number of standards have been defined on what constitutes good quality : Requirements should be complete, unambiguous, specific, time-bounded, consistent, etc. For agile requirements specifications, no new standards have been defined yet, and it is not clear yet whether traditional quality criteria still apply. To investigate what quality criteria for assessing the correctness of written agile requirements exist, we have conducted a systematic literature review. The review resulted in a list of 16 selected papers on this topic. These selected papers describe 28 different quality criteria for agile requirements specifications. We categorize and analyze these criteria and compare them with those from traditional requirements engineering. We discuss findings from the 16 papers in the form of recommendations for practitioners on quality assessment of agile requirements. At the same time, we indicate the open points in the form of a research agenda for researchers working on this topic. [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]

This special issue comprises a selected set of high quality and extended articles of the 27th Systems, Software and Services Process Improvement (EuroSPI) Conference, held in 2020 in Düsseldorf, Germany (Figure 1). Automotive software is a relatively new, but important research field [[14]] and these two papers are directing two different but crucial challenges: SPI Implementation practices and the integration of security in the automotive software development lifecycle. EuroSPI is an initiative with the following major action lines http://www.eurospi.net: Establishing an annual EuroSPI conference supported by software process improvement networks from different EU countries. [Extracted from the article]

Purpose: Numerous approaches from the field of economics already exist for the improvement of business processes. In the field of software development, work has been done on improving development processes. For years, the focus here has been on agile approaches. Although various approaches for improving business processes exist, it is becoming increasingly difficult to adapt business processes to the fast-moving conditions of the market and the business environment. Agile approaches address this issue. Thus, not only software development processes, but also business processes should benefit from agile approaches. Design/methodology/approach: To this end, values and principles of the Agile Manifesto, agile methods such as Scrum, and various agile practices such as the Kanban board should be applied in business processes. This paper examines the work already done on this topic. With the help of a systematic literature review (SLR), literature studies dealing with the implementation of the agile approach in business processes are identified. Findings: This paper presents, investigates and contrasts 12 primary sources dealing with agile and business processes and shows how they are different/ equal regarding three research questions. Originality/value: We provide an overview of existing approaches handling the combination of agile and business processes to improve business processes. [ABSTRACT FROM AUTHOR]

Customers are looking for suppliers to deliver complex systems at faster rates, targeting three year cycle. This timeframe is challenging for low Technology Readiness Level (TRL) developments, increasing requirements engineering effort, leaving engineers little time and scope for innovation. Test and Evaluation (T&E) activities are often performed in Australia near the end of the process diminishing their value , compensating for a lack of modelling and simulation in early stages. Waterfall Project Management dominates where capability is hardware focused, leading to overruns and deliver capability that falls short of customer expectations in some areas. The Agile approach has been successfully used in software-focused developments. Project managers have been slow to adopt Agile for developments in areas like Defence where the safety is hardware dominant claiming the Agile process lacks necessary governance , increasing risk in the development. This paper examines the extant developmental process in a Defence context and proposes a Minimal Viable Product (MVP)-based framework using Agile to accelerate the development and mitigate risk escalation. [ABSTRACT FROM AUTHOR]

The article introduces Project Controls 3.0 (PC-3.0), a new approach to project management that aims to address the shortcomings of traditional project controls systems. PC-3.0 focuses on providing timely and accurate information to empower management teams to make proactive decisions and achieve project objectives. The system is designed to be flexible and adaptable, allowing for different work methods and planning approaches for each work unit. Key aspects of PC-3.0 include Work Performance Management (WPM), proactive and adaptive planning, standardized reporting, and maintaining the strategic baseline. The article also emphasizes the need for cost control, Earned Value Management (EVM), project reports, and contractual considerations. Successful implementation of PC-3.0 requires a cultural shift in project management practices. [Extracted from the article]

This paper explains the Visual Milestone Planning (VMP) method using an agile vocabulary to facilitate its adoption by agile practitioners as a front end for a hybrid development process. VMP is a visual and collaborative planning approach which promotes a shared understanding of the work approach and commitment through the direct manipulation by team members of the reified planning constructs involved in the development of the plan. Once the product backlog has been established and relevant milestones identified, a novel construct called the milestone planning matrix is used to document the allocation of product backlog items to milestones. The milestones due dates are later determined by grouping sticky notes representing the work to be performed into timeboxes called work packages and accommodating them on a resource and time scaled scheduling canvas very much as it would be done in a Tetris game. [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]

Agile software development is one of the most important development paradigms these days. However, there are still some challenges to consider to reduce problems during the documentation process. Some assistive methods have been created to support developers in their documentation activities. In this regard, Natural Language Processing (NLP) can be used to create various related tools (such as assistants) to help with the documentation process. This paper presents the current state-of-the-art NLP techniques used in the agile development documentation process. A mapping review was done to complete the objective, the search strategy is used to obtain relevant studies from ScienceDirect, IEEE Xplore, ACM Digital Library, SpringerLink, and Willey. The search results after inclusion and exclusion criteria application left 47 relevant papers identified. These papers were analyzed to obtain the most used NLP techniques and NLP toolkits. The toolkits were also classified by the kind of techniques that are available in each of them. In addition, the behavior of the research area over time was analyzed using the relevant paper found by year. We found that performance measuring methods are not standardized, and, in consequence, the works are not easily comparable. In general, the number of related works and its distribution per year shows a growing trend of the works related to this topic in recent years; this indicates that the adoption of NLP techniques to improve agile methodologies is increasing. [ABSTRACT FROM AUTHOR]

Background: Agile methodology is known for delivering effective projects with added value within a shorter timeframe, especially in Business Intelligence (BI) system which is a valuable tool for informed decision-making. However, identifying impactful elements for successful BI implementation is complex due to the wide range of Agile attributes. Objective: This research aims to systematically review and analyze the integration of BI within Agile methodology, providing valuable guidance for future projects implementation, enhancing the understanding of effective application, and identifying influential factors. Methods: Based on the Kitchenham method, 19 papers were analyzed from 288 papers, sourced from databases like Scopus, ACM, IEEE, and others published in 2016-2022. Meanwhile the extracted key factors impacting agile BI implementation were validated by qualified expert. Results: Agile was discovered to provide numerous benefits to BI projects by promoting flexibility, collaboration, and rapid iteration for enhanced adaptability, while effectively addressing challenges including those related to technology, management, and skills gaps. In addition, Agile methods, including tasks such as calculating cycle time, measuring defect backlogs, mapping code ownership, and engaging end users, offered practical solutions. The advantages included adaptability, success, value enhancement, cost reduction, shortened timelines, and improved precision. The research additionally considered other critical Agile elements such as BI tools, Agile Practices, Manifesto, and Methods, thereby enhancing insights for successful implementation. Conclusion: In conclusion, the research outlined Agile BI implementation into seven key factor groups, validated by qualified expert, providing guidance for BI integration and practices, and establishing a fundamental baseline for future applications. [ABSTRACT FROM AUTHOR]

Attention is currently being focused on DevOps, which aims to reduce software development time by means of close collaboration between the development and operations areas. However, little effort has been made to determine the role of requirements management in DevOps. The objective of this study is to help both researchers and practitioners by providing an overview of the best practices regarding requirements engineering in DevOps and identifying which areas still need to be investigated. A multivocal mapping study has, therefore, been carried out in order to study which methodologies, techniques and tools are used to support requirements management in DevOps environments. After applying the review protocol, 37 papers from formal literature and 14 references from grey literature were selected for analysis. The general conclusions obtained after analysing these papers were that, within DevOps, more attention should be paid to: (1) the reuse of requirements in order to identify systems and software artefacts that can serve as a basis for the specification of new projects; (2) the communication of requirements between the different areas of an organisation and the stakeholders of a project; (3) the traceability of requirements in order to identify the relationship with other requirements, artefacts, tasks and processes; (4) non-functional requirements in order to identify the requirements of the operations area in the early phases of a project; and finally (5) specific requirements tools that should be seamlessly integrated into the DevOps toolchain. All these issues must be considered without ignoring the agile and continuous practices of development, operations and business teams. More effort must also be made to validate new methodologies in industry so as to assess and determine their strengths and weaknesses. [ABSTRACT FROM AUTHOR]

Traditional project management methods are based on scientific principles considered “normal science” but lack a theoretical basis for this approach. [35, 36, 69] These principles result in linear stepwise refinement of the project’s outcomes by applying the planning-as-management paradigm. Linear feedback methods adjust plans made in this paradigm. These plans cannot cope with the multiple interacting and continuously changing technology and market forces. They behave as a linear, deterministic, Closed-Loop control system. A Closed-Loop adaptive control paradigm parallels this approach and agile project management methods. From these, a comparison is made between project management practices and the tenets of agile development processes in terms of feedback control and emergent solutions with a control system capable of adjusting to the changes brought about by changes in the dynamics of the process, disturbances, or some other cause not established in the original plan. This paper suggests that when managing in the presence of uncertainties that create a risk to project success, adaptive control theory may be better suited as a model for project management in a rapidly changing, dynamically evolving network of statistical processes than traditional linear approaches. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue which are extended versions of the best papers from the magazine's 2017 conference, on topics including agile software, user requirements quality, and user rationale in software engineering.

Traditional Systems Engineering artifacts and terminology have a negative connotation in some companies and industries that use Agile development. This paper aims to show that the terms and concepts typically associated with traditional systems engineering are not scary for Agile software development. They can, and should, be tailored and utilized during the Agile development process. Many times, terminology and lack of understanding lead to Agile practitioners shying away from what are considered traditional Systems Engineering artifacts such as requirements, architectures designs, documented interfaces, verification, gate reviews, etc. Agile actually already employs many of these artifacts and concepts but simply uses a different terminology when referring to them. This paper helps advance the mindset that traditional Systems Engineering terms, concepts, and artifacts are not something to avoid in Agile by providing alternative ways to describe and think about them in an Agile setting. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to characterize the interfaces between manufacturing companies and the Internet of Things (IoT) suppliers involved in their digital servitization. Design/methodology/approach: This paper builds on an explorative case study of a manufacturing firm and its IoT suppliers. This paper relies on the Industrial Network Approach to study interfaces between buying firms and their suppliers. Findings: This paper identifies three distinct types of supplier interfaces: connected, digital and digital-physical. They all contain technical resource interfaces with additional organizational and/or technical complexities that need to be managed. Connectivity, an Agile approach to software development and strong technical dependence emerged as key factors that impact the interactions between manufacturing firms and IoT suppliers and how their resources are combined. Practical implications: This paper offers managerial implications regarding the importance of internal organization (such as appropriate cross-functional teams) to manage the dynamics of collaborations required by digital technologies, maintain interactions with IoT suppliers and identify and manage interdependences between IoT suppliers. Building close relationships with suppliers of crucial infrastructure (e.g. IoT cloud platform and data security systems) can also be beneficial for manufacturing firms to reduce risks. Finally, attention should be given to IoT technology strategy, which impacts both digital and digital-physical supplier interfaces. Originality/value: In digital servitization, manufacturing firms are heavily reliant on external resources for IoT technology. Despite this, few studies have investigated the characteristics of their interfaces with IoT suppliers, how these can be managed and how resources are combined. [ABSTRACT FROM AUTHOR]

There have been several studies on mono- and multi-repository structures and branching strategies. However, most of those studies focused on the basics of repository structures and used a small number of project samples. This paper uses data from more than 50 000 repositories collected from GitHub. The results indicate that: 1) mono-repository projects generally involve smaller teams, with the majority being handled by one or two developers, 2) multi-repository projects often require larger teams, typically consisting of three or more developers, 3) mono-repository projects are favored for shorter durations, with over half of the projects completed within six months, 4) multi-repository projects, on the other hand, have higher usage percentages in longer development periods, suggesting their suitability for more time-consuming endeavors. Examining branching strategies reveals that: 1) the trunk-based approach is commonly used in both mono- and multirepository projects, 2) GitHub Flow has much wider usage in multi-repository projects rather than mono-repository. These findings offer valuable insights for developers and project managers in selecting the appropriate repository structure and branching strategy based on project requirements. Understanding team dynamics, project complexity, and desired development periods aids in optimizing collaboration and achieving successful outcomes. [ABSTRACT FROM AUTHOR]

Context: The recent research trend has highlighted that multiple stakeholders are involved during requirement gathering in agile software development. Hence, leading to an increased number of duplicate user stories in agile product backlog during requirement gathering. Objective: The objective of this paper is to evaluate the existing techniques employed in identifying and eliminating the duplicate user stories from agile product backlog and to overcome the existing gaps with the help of a newly proposed clustering algorithm. Method: An agile user story is expressed as a function of input and output parameters. That said multiple user stories having similar set of input parameters are most likely to be duplicate causing a redundancy. The newly proposed algorithm is used for clustering user stories having similar set of input parameters through various iterations and then removing the identified duplicate user stories from agile product backlog. This paper also introduces the concept of mass clustering which means clustering a number of user stories in single run. Results: Experimental results prove the proposed model is capable of handling small and large releases ranging between 100 to 1000 user stories with similar efficiency. The proposed clustering algorithm outperformed the clustering algorithms and resulted in 37% decrease in agile product backlog by eliminating duplicate user stories causing redundancy. The experimental results are obtained from the logs of the MATLAB tool. However, the provided algorithm is generic in nature and can be implemented using R, Python or SAS programming tools. The provided algorithms employs proven matrix operations. Conclusion: The proposed clustering algorithm overcomes the limitation of existing user story management methods and clearly out performs when compared with other clustering algorithms. Finally, this paper gives recommendations about the usage of the provided clustering algorithm during agile release planning for eliminating duplicate user stories from agile product backlog. [ABSTRACT FROM AUTHOR]

Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial intelligence (AI) has empowered smart manufacturing and digital transformation. AI enhances the migration towards industry 4.0 through AI-based decision-making by analyzing real-time data to optimize different processes such as production planning, predictive maintenance, quality control etc., thus guaranteeing reduced costs, high precision, efficiency and accuracy. This paper explores AI-driven smart manufacturing, revolutionizing traditional approaches and unlocking new possibilities throughout the major phases of the industrial equipment lifecycle. Through a comprehensive review, we delve into a wide range of AI techniques employed to tackle challenges such as optimizing process control, machining parameters, facilitating decision-making, and elevating maintenance strategies within the major phases of an industrial equipment lifecycle. These phases encompass design, manufacturing, maintenance, and recycling/retrofitting. As reported in the 2022 McKinsey Global Survey (https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review), the adoption of AI has witnessed more than a two-fold increase since 2017. This has contributed to an increase in AI research within the last six years. Therefore, from a meticulous search of relevant electronic databases, we carefully selected and synthesized 42 articles spanning from 01 January 2017 to 20 May 2023 to highlight and review the most recent research, adhering to specific inclusion and exclusion criteria, and shedding light on the latest trends and popular AI techniques adopted by researchers. This includes AI techniques such as Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Bayesian Networks, Support Vector Machines (SVM) etc., which are extensively discussed in this paper. Additionally, we provide insights into the advantages (e.g., enhanced decision making) and challenges (e.g., AI integration with legacy systems due to technical complexities and compatibilities) of integrating AI across the major stages of industrial equipment operations. Strategically implementing AI techniques in each phase enables industries to achieve enhanced productivity, improved product quality, cost-effectiveness, and sustainability. This exploration of the potential of AI in smart manufacturing fosters agile and resilient processes, keeping industries at the forefront of technological advancements and harnessing the full potential of AI-driven solutions to improve manufacturing processes and products. [ABSTRACT FROM AUTHOR]

Agile planning offers a number of benefits that make the customers active members of the team throughout the project. In global software development (GSD), geographic separations demand special attention to harness these benefits. Our paper conducted a systematic mapping study (SMS) to analyze GSD-specific agile planning challenges followed by a systematic literature review (SLR) for efficient solutions. These studies led to a model for agile planning in global software development supporting GSD practitioners during this process. [ABSTRACT FROM AUTHOR]

Background: Research shows that emotional intelligence (EI) should be used alongside cognitive intelligence during requirements change (RC) handling in Software Engineering (SE), especially in agile settings. Objective: We wanted to study the role of EI in-depth during RC handling. Method: We conducted a mixed-methods study (an interview study followed by a survey study) with 124 software practitioners. Findings: We found the causal condition, intervening condition and causes lead to key direct consequences of regulating own emotions, managing relationships, and extended consequences of sustaining productivity, setting and sustaining team goals. We found several strategies of supporting EI during RC handling. Further, we found strong correlations between six strategies and one being aware of own emotions, regulating own emotions, sustaining team productivity, and setting and sustaining team goals. Conclusion: Empathising with others and tracking commitments and decisions as a team are key strategies that have strong correlations between managing emotions, between sustaining team productivity, and between setting and sustaining team goals. To the best of our knowledge, the framework we present in this paper is the first theoretical framework on EI in SE research. We provide recommendations for software practitioners to consider during RC handling. [ABSTRACT FROM AUTHOR]

This article explores the differences between projects and programs in project management and the need for different management approaches. It emphasizes the importance of understanding the value generation and interactions within a program to guide scheduling and resource allocation. The article suggests the use of a program-level value breakdown structure (PgVBS) and an AI-based program management system to improve program scheduling and maximize return on investment. It also discusses the complexities of planning and scheduling programs compared to projects and highlights the significance of program scheduling in optimizing revenue generation. The author, Stephen Devaux, is an experienced project management theorist, consultant, author, and educator who has introduced innovative methods and metrics to the field. [Extracted from the article]

Selecting the most suitable agile software development method is a challenging task due to the variety of available methods, each with its strengths and weaknesses. To achieve project goals effectively, factors such as project needs, team size, complexity, and customer involvement should be carefully evaluated. Choosing the appropriate agile method is crucial for achieving high client satisfaction and effective team management, but it can be a challenging task for project managers and higher-level management officials. This paper presents a solution aiming to help them in selecting the most suitable software development method for their project. In this regard, this solution includes a pre-project management approach model and a decision tree that considers the unique requirements of the project. In the proposed solution results, Scrum was found to be suitable for both small and large projects, on the condition that roles and responsibilities are clearly defined and that the approach is people-centric. Furthermore, high-risk mitigation measures should be added for small projects. To facilitate the use of our model, a software application has been developed which implements the decision-making tree. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Machine Learning (ML) approaches have emerged in the networking domain with great expectation. They can be broadly divided into AI/ML techniques for network engineering and management, network designs for AI/ML applications, and system concepts. AI/ML techniques for networking and management improve the way we address networking. They support efficient, rapid, and trustworthy engineering, operations, and management. As such, they meet the current interest in softwarization and network programmability that fuels the need for improved network automation in agile infrastructures, including edge and fog environments. Network design and optimization for AI/ML applications addresses the complementary topic of supporting AI/ML-based systems through novel networking techniques, including new architectures and algorithms. The third topic area is system implementation and open-source software development. [ABSTRACT FROM AUTHOR]

The success of agile development methods in software development has raised interest in System-on-Chip (SoC) design, which involves high architectural and development process complexity under time and project management pressure. This article discovers the current state of agile hardware development with the questions (1) how well literature covers the SoC development process, (2) what agile methods and practices are applied or (3) what proposals are made to increase the agility, and (4) what is the impact for the SoC community. To answer the questions, a mapping study and literature review were performed. Seven hundred thirty papers were first studied, and eventually, after a rigorous filtering process, 25 papers were thoroughly analyzed. The results show that the popular agile SW development methods are applied in 5 cases, ideas adapted from the agile Hardware manifesto in 9 cases, and 11 cases do not define the Agile HW development method. Most of the papers address shorter development time by better methodologies and tools that indirectly shape the SoC development toward agility. The focus of agile hardware development is mostly on the SoC artifacts and methodological improvements have not been quantified. However, the literature indicates a significant impact on many academic chip prototypes. The challenges are better understood and the interest in agile methods is clearly increasing. The methodological gaps in the prevalent situation encourage further research and more accurate reporting of the development in addition to the SoC artifacts. [ABSTRACT FROM AUTHOR]

In the armed forces, successful digitalization is crucial to ensure effective operations. Much of the existing literature on project factors during the planning and execution phases of public IT projects do not focus specifically on military sector projects. Therefore, the paper aims to provide empirical insights into the characteristics of successful military IT projects. Data from such projects in NATO countries and agencies were collected through interviews and project documents. The findings relating to the main variable of interest, "delivery of client benefit," supported previous findings on IT project performance. Medium-sized projects performed better than small and large projects, and the agile development method delivered more client benefit than traditional methods. Client involvement apparently had a positive effect on project success. Clearly specified objectives had a statistically significant effect on project success in terms of clients' benefits. The paper contributes to the gap in research on military IT projects and broadens the project management literature's focus on time and cost to include delivery of client benefit as a success variable. The use of cross-country data provided unique insights for academics and practitioners regarding which project characteristics affect the successful development and adoption of new software by the armed forces. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to bridge two seemingly disparate views of project management: proponents of project management methodologies promote a view where a standard set of predefined project practices guarantee project success, while a contingent view of projects suggests that project management needs to be adaptive to project actuality and context. Our aim in this paper is to understand how these different forms of managing projects impact project success. We investigate projects through a lens of discretion, defined as autonomy in the project team to adapt the project to its context as opposed to a reliance on a pre-defined set of rules for project management. We also look at the role of exploration, that is, whether the project focuses on the development of new knowledge, or whether the focus is on furthering existing competences. Based on our analysis, we propose a framework to determine the right amount of discretion in a project, highlighting which project management methodology is suited for the work at hand or whether discarding methodology altogether is more likely to lead to project success. [ABSTRACT FROM AUTHOR]