Search

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]

There have been success stories reported regarding the adoption of agile software development methods in the industry. There also exist observations on their limitations. One of these limitations is scalability since agile methods like Scrum were originally designed for small software teams. Scalable agile frameworks were introduced to address this limitation. We conducted an industrial case study on the adoption of such a framework, called Nexus. Our study involves quantitative and qualitative evaluation based on observations within a product development organization over a period of 12 months. Scrum is used for the development of a product during the first 6 months of this period. Nexus is used in the remaining 6 months. Data are collected throughout the whole period for measuring productivity, quality, and team member motivation. Results suggest a significant increase in productivity and product quality after switching to Nexus. Team motivation was slightly improved as well. [ABSTRACT FROM AUTHOR]

Agile software development has reached wide adoption in various countries including Turkey, even though from which its original cultural backgrounds differ. In Turkey, many organizations have started to adopt Agile approaches more and more in their software development processes. This interest in the country's software development is parallel to what the academic literature on Agile in the country exhibits. However, despite the prevalence of Agile in Turkey, there is a lack of sufficient secondary research and comprehensive review on Agile in Turkey, which poses a significant necessity for further investigation. Considering this gap, we performed a quantitative bibliometric analysis of Agile software development publications produced by Turkish organizations in a holistic and broad approach both for scholars and practitioners. We provide a summary of relevant academic studies that emerged in Agile research in Turkey by focusing on many aspects including bibliometric properties of papers, researchers, affiliations, venues, and thematic contents that are separated into 15 sub‐research questions. After delivering results based on the questions, we discuss the results and findings of our study and present implications regarding the findings. The main contributions of our work are twofold. First, the paper may help the readers to have a quick idea, understand the subject, and gain insight from a large volume of scientific data. Second, the paper can help readers to use these analyses to form future research. [ABSTRACT FROM AUTHOR]

Enterprise architecture is a growing trend that aims to help deal with the complexity of socio‐technical systems such as human organizations, as well as their information technology and systems areas. Nevertheless, the contribution of enterprise architecture to the field of software engineering remains unclear. The purpose of this systematic literature review is to see how enterprise architecture is used in software development and maintenance practice. To this end, we first carried out a search in the SCOPUS database and then organized the papers according to the Software Engineering Body of Knowledge to determine what areas of software engineering are covered by each research study. To understand how enterprise architecture is used, we established a classification based on ISO 42010 and TOGAF. From the systematic literature review, we noticed that the early stages of development are the most impacted by the enterprise architecture. On the other hand, we observed that enterprise architecture is of assistance in the areas of engineering management, engineering processes, and engineering models and methods; these tasks are carried out by teams or managers using different, often agile, development methods or standards. In turn, we found that the most common categories are architecture descriptions; these are often used to facilitate communication and information‐sharing between different stakeholders, in addition to frameworks, which will help to establish common practices in the organization related to the joint use of enterprise architecture and software development. [ABSTRACT FROM AUTHOR]

The practices of lean and agile methods are important to manage and guide projects development in different situations. However, selecting the appropriate practices of lean and agile methods is a daunting task, owing to the availability of hundreds of practices. This wide variety of available practices bewilders potential users, in terms of the best practices that may yield satisfactory solution when applied to the project development. Lean and agile practices selection model is necessary to guide both academic and industrial experts to choose the appropriate practices for a specific project development. Thus, this study aimed to develop lean and agile practices selection (LAPS) model that presents a clear picture of how developers can use LAPS model to select and adopt different practices from various lean and agile methods. Qualitative research method (e.g., grounded theory) was used to interview 18 software developers across 13 countries. The validated qualitative analysis results showed that the proposed LAPS model consists of two main components, which are (1) lean and agile practices that include 41 best practices related to lean and agile methods and (2) factors that affect the process of lean and agile practices selection including five main factors and 17 subfactors associated with the five main factors. The two case studies conducted assured the validity and applicability of the lean and agile practices selection model. [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 pace of technological advancements has been rapidly increasing in recent years, with the advent of artificial intelligence, virtual/augmented reality, and other emerging technologies fundamentally changing the way human beings work. The adoption and integration of these advanced technologies necessitate teams with diverse disciplinary expertise, to help teams remain agile in an ever-evolving technological landscape. Significant disciplinary diversity amongst teams, however, can be detrimental to team communication and performance. Additionally, accelerated by the COVID-19 pandemic, the adoption and use of technologies that enable design teams to collaborate across significant geographical distances have become the norm in today's work environments, further complicating communication and performance issues. Little is known about the way in which technology-mediated communication affects the collaborative processes of design. As a first step toward filling this gap, the current work explores the fundamental ways experts from distinct disciplinary backgrounds collaborate in virtual design environments. Specifically, we explore the conversational dynamics between experts from two complementary yet distinct fields: non-destructive evaluation (NDE) and design for additive manufacturing (DFAM). Using Markov modeling, the study identified distinct communicative patterns that emerged during collaborative design efforts. Our findings suggest that traditional assumptions regarding communication patterns and design dynamics may not be applicable to expert design teams working in virtual environments. [ABSTRACT FROM AUTHOR]

Many agile projects use expert judgment-based methods for estimating effort. Commonly, the judgments made during estimating project features are consensual. However, this will hardly be achieved when a conflict arises between estimators. Besides, estimate depends on the experience and skills of the estimator and could be threatened by his uncertainty to make reliable and accurate assessments. To fill these gaps, an intuitionistic fuzzy expert judgment method is proposed. The latter allows making fuzzified assessments and integrates estimators' priorities according to a set of human factors. As well, it provides consensual estimates either by the end of the estimation rounds or automatically using an iterative algorithm. On the other hand, an initial empirical study has been conducted on an agile project in which user stories have been estimated by students and experts. The first findings have revealed that the proposal is more suitable for inexperienced estimators or in the first sprints of the project where disagreement is still significant. Nevertheless, when group agreement is increased during the estimating process, the proposal maintains a null bias toward the overestimation or the underestimation of the user stories. [ABSTRACT FROM AUTHOR]

Scrum is an important and essential technique for developing software. Scrum framework is a project management technique that can emphasize software development teamwork. If you are starting, consider scrum as a method for accomplishing tasks as a team in manageable chunks simultaneously, with ongoing experimentation and feedback loops to learn and improve as you go. Scrum enables individuals and groups to collaboratively and gradually generate value. Being an agile framework, scrum gives people and teams the perfect structure to fit into their workflows while still including the best practices to cater to their requirements. There are some important considerations for security in the agile software development process such as threat modeling, secure coding practices, continuous security testing, authentication, and authorization. In this work, we reviewed various scrum developing techniques to find out the research gaps. This article consider the scrum technique with blockchain technologies for review because it is preferred by most of the software industries. [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]

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]

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]

The Data Mine at Purdue University is a pioneering experiential learning community for undergraduate and graduate students of any background to learn data science. The first data‐intensive experience embedded in a large learning community, The Data Mine had nearly 1300 students in academic year (AY) 2022–2023 and nearly 1700 students for AY 2023–2024. The Data Mine embodies data‐infused education, research, and collaboration. Students learn Python, R, SQL, and shell‐scripting, while working on weekly projects within a high‐performance computing (HPC) cluster. In the Corporate Partners cohort, students work on teams of 5–15 students, led by a paid student team leader. Each cohort follows an Agile approach, working on data‐intensive projects provided by industry partners and mentored by company employees. Students develop professional and data skills throughout the academic year, from August through April. Many students return in subsequent years to the program, increasing their tenure with a Corporate Partner. Student teams are inherently interdisciplinary; students from 133 different majors are involved in the program, ranging from new incoming students through PhD level students. These interdisciplinary teams of students bring new perspectives to challenging problems in which data science is a key part of the solution. The interdisciplinary teams foster an environment of synthesis with ideas and solutions. Students come together with different life experiences, different levels of technical skill, but also varying ways they navigate paths to solutions because of the variety of majors represented, resulting in a more creative and robust solution than a traditional data science program. This article is categorized under:Applications of Computational Statistics > Education in Computational Statistics [ABSTRACT FROM AUTHOR]

The article discusses the use of model-based code generation and its limitations. While there have been successful industrial projects that have used code generation from abstract models, the widespread adoption of code generation from explicitly defined models has not been as successful. The article identifies several challenges, including developers' ability to think in abstract form, the limitations of existing tooling, the need for flexible adaptation of the generator, and weak tool support for defining abstraction levels in a model. The article suggests that a "smart" generator could address these challenges by generating code for various functionalities, such as data transportation, user interfaces, logging, and search functionality. However, the article acknowledges that current code generators are not yet capable of such smartness and that more work is needed in this area. [Extracted from the article]

In recent times, there has been a growing focus on the well-being and healthcare of small ruminants, particularly in relation to the issue of anemia due to infection with blood-feeding gastrointestinal nema-todes, such as Haemonchus contortus. The objective of this study was to assess the hematocrit levels in blood samples obtained from small ruminants, specifically goats. Additionally, the study is an attempt to design and create a quick sensor for identifying anemia, which could be conveniently used on farms. A total of 75 mature, intact male Spanish goats were subjected to hematocrit analysis to ascertain their spectrum of hematocrit values and association with anemic conditions. Simultaneously, a unique sensor with user-friendly features was developed to promptly provide farmers with feedback on the anemic status of animals using AI-based machine learning algorithms, enabling timely intervention. The sensor utilized a semi-invasive approach with minimal blood sample requirement. 30 ^L of blood was dropped on glycerol soaked Whatman filter paper No. 1, and images were taken at 90 sec, 150 sec, and 270 sec to capture the blood pattern on filter paper soaked in glycerol using a cell phone. These images were correlated with actual hematocrit value obtained from conventional hematocrit analysis. A RMSprop with adjusted learning rate convolution neural network (RMSprop-CNN) based images classification model was developed for the classification of different patterns at different levels of hematocrit. The model was trained on a total of 1,000 images with a training and testing split of 80:20 ratio. For the optimization process, the Adam optimizer with a learning rate of 0.001 is employed. The model is compiled with a categorical cross-entropy loss function, aiming to improve its accuracy metric over training iterations. The initial studies demonstrated a detection accuracy level of 70.31 % at 10 epochs in identifying different hematocrit levels (Level 1; healthy, to Level 5; severely anemic) but improved significantly up to 94.89 % by 100 epochs, resulting in a notable reduction in the time and level of knowledge previously necessary for conducting such evaluations. The present study not only provides valuable insights into the hematological characteristics of small ruminants, but also establishes a foundation for the development of a straightforward and efficient method for detecting anemia. Consequently, this advancement has the potential to enhance the overall care and well-being of animals within agricultural environments. [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]