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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]

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]

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]

As a subclass of nanosatellites, CubeSats have changed the game's rules in the scientific research industry and the development of new space technologies. The main success factors are their cost effectiveness, relative ease of production, and predictable life cycle. CubeSats are very important for training future engineers: bachelor's and master's students of universities. At the same time, using CubeSats is a cost-effective method of nearest space exploration and scientific work. However, many issues are related to efficient time-limited development, software and system-level quality assurance, maintenance, and software reuse. In order to increase the flexibility and reduce the complexity of CubeSat projects, this article proposes a "hybrid" development model that combines the strengths of two approaches: the agile-a-like model for software and the waterfall model for hardware. The paper proposes a new computing platform solution, "Falco SBC/CDHM", based on Microchip (Atmel) ATSAMV71Q21 with improved performance. This type of platform emphasizes low-cost space hardware that can compete with space-grade platforms. The paper substantiates the architecture of onboard software based on microservices and containerization to break down complex software into relatively simple components that undergraduates and graduates can handle within their Master's studies, and postgraduates can use for scientific space projects. The checking of the effectiveness of the microservice architecture and the new proposed platform was carried out experimentally, involving the time spent on executing three typical algorithms of different algorithmic complexities. Algorithms were implemented using native C (Bare-metal) and WASM3 on FreeRTOS containers on two platforms, and performance was measured on both "Falco" and "Pi Pico" by Raspberry. The experiment confirmed the feasibility of the complex application of the "hybrid" development model and microservices and container-based architecture. The proposed approach makes it possible to develop complex software in teams of inexperienced students, minimize risks, provide reusability, and thus increase the attractiveness of CubeSat student projects. [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]

Effort estimation is always quite a challenge, especially for agile software development projects. This paper describes the process of building a Bayesian network model for effort prediction in agile development. Very few studies have addressed the application of Bayesian networks to assess agile development efforts. Some research has not been validated in practice, and some has been validated on one or two projects. This paper aims to bring the implementation and use of Bayesian networks for effort prediction closer to the practitioners. This process consists of two phases. The Bayesian network model for task effort estimation is constructed and validated in the first phase on real agile projects. A relatively small model showed satisfactory estimation accuracy, but only five output intervals were used. The model was proven to be useful in daily work, but the project manager wanted to obtain more output intervals, although increasing the number of output intervals reduces the prediction accuracy. In the second phase, the focus is on increasing the number of output intervals while maintaining satisfactory accuracy. The advanced model for task effort estimation is developed and tested on real projects of two software firms. [ABSTRACT FROM AUTHOR]

Agile software requirements engineering processes enable quick responses to reflect changes in the client's software requirements. However, there are challenges associated with agile requirements engineering processes, which hinder fast, sustainable software development. Research addressing the challenges with available solutions is patchy, diverse and inclusive. In this study, we use a systematic literature review coupled with thematic classification and gap mapping analysis to examine extant solutions against challenges; the typologies/classifications of challenges faced with agile software development in general and specifically in requirements engineering and how the solutions address the challenges. Our study covers the period from 2009 to 2023. Scopus—the largest database for credible academic publications was searched. Using the exclusion criteria to filter the articles, a total of 78 valid papers were selected and reviewed. Following our investigation, we develop a framework that takes a three-dimensional view of agile requirements engineering solutions and suggest an orchestrated approach balancing the focus between the business context, project management and agile techniques. This study contributes to the theoretical frontier of agile software requirement engineering approaches and guidelines for practice. [ABSTRACT FROM AUTHOR]

This paper discusses the "Get Real Get Better" (GRGB) approach to implementing agile program management in the U.S. Navy, supported by advanced data analytics and artificial intelligence (AI). GRGB was designed as a set of foundational principles to advance Navy culture and support its core values. This article identifies a need for a more informed and efficient approach to program management by highlighting the benefits of implementing comprehensive data analytics that leverage recent advances in cloud computing and machine learning. The Jupiter enclave within Advana implemented by the U.S. Navy, is also discussed. The presented approach represents a practical framework that cultivates a "Get Real Get Better" mindset for implementing agile program management in the U.S. Navy. [ABSTRACT FROM AUTHOR]

Agile development processes based on user stories often face issues such as incomplete, inconsistent, and inaccurate user requirements, which increase the workload of agile development teams and reduce the efficiency of product function development, ultimately resulting in the inability to respond quickly to user requirements. This paper proposes a user requirement quality assessment method based on user stories to address these problems. This method relies on the agile development process, constructs a user requirement quality assessment framework, defines a user story model and a user requirement quality model, develops seven user requirement quality assessment criteria, and designs a user requirement quality assessment process. A data experiment exploring the development of smartphone requirements is used to validate the feasibility and effectiveness of the method. The experimental results demonstrate that the method improves user requirement quality to some extent, providing an automated solution for agile development teams to enhance user requirement quality. [ABSTRACT FROM AUTHOR]

Software development must be based on more than just the experience and capabilities of your programmers and your team. The importance of obtaining a quality product lies in the risks that can be exploited by software vulnerabilities, which can jeopardize organizational assets, consumer confidence, operations, and a broad spectrum of applications. Several methods, techniques, and models have been suggested and developed to address software security. However, only a few have solid evidence for creating secure software applications. The main objective of this paper is to survey the literature for methods or models suitable for considering the integration of security in all or some of the phases of the software development life cycle and which ones are most considered or neglected. This study represents the beginning of research to generate a methodology that integrates security practices in agile software development, allowing inexperienced developers to create more secure applications. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic accelerated the shift to online learning in higher education, making the need to rethink pedagogical approaches to on-campus education stronger than ever before. While online learning offers a wide range of benefits for both teachers and students, social, face-to-face interaction provides a strong rationale for in-person education. This paper proposes a novel approach to enhancing in-person social learning experiences through robot-supported collaborative learning facilitated by a social robot NAO in the case study "Planning poker with NAO", which is a collaborative game-based activity facilitated by the robot. The case study was designed to provide a scalable social learning experience in small groups of students. The evaluation results from a study with 46 university students who played Planning poker with NAO explore different quality aspects of the learning experience. The results indicate that students valued both the social learning experience and the robotic facilitator. The analysis revealed some significant differences among students with and without prior experience in interacting with NAO, suggesting directions for future research related to novelty and familiarisation effects as well as to scaling up of social learning in small groups by applying social robots. [ABSTRACT FROM AUTHOR]

Throughout the evolution of software systems, empirical methodologies have been used in their development process, even in the Internet of Things (IoT) paradigm, to develop IoT-based systems (IoTS). In this paper, we review the fundamentals included in the manifesto for agile software development, especially in the Scrum methodology, to determine its use and role in IoTS development. Initially, 4303 documents were retrieved, a number that was reduced to 186 after applying automatic filters and by the relevance of their titles. After analysing their contents, only 60 documents were considered. Of these, 38 documents present the development of an IoTS using some methodology, 8 present methodologies focused on the construction of IoTS software, and 14 present methodologies close to the systems life cycle (SLC). Finally, only one methodology can be considered SLC-compliant. Out of 38 papers presenting the development of some IoTS following a methodology for traditional information systems (ISs), 42.1% have used Scrum as the only methodology, while 10.5% have used Scrum combined with other methodologies, such as eXtreme Programming (XP), Kanban and Rapid Prototyping. In the analysis presented herein, the existing methodologies for developing IoTSs have been grouped according to the different approaches on which they are based, such as agile, modelling, and service oriented. This study also analyses whether the different proposals consider the standard stages of the development process or not: planning and requirements gathering, solution analysis, solution design, solution coding and unit testing (construction), integration and testing (implementation), and operation and maintenance. In addition, we include a review of the automated frameworks, platforms, and tools used in the methodologies analysed to improve the development of IoTSs and the design of their underlying architectures. To conclude, the main contribution of this work is a review for IoTS researchers and developers regarding existing methodologies, frameworks, platforms, tools, and guidelines for the development of IoTSs, with a deep analysis framed within international standards dictated for this purpose. [ABSTRACT FROM AUTHOR]

As part of agile methodologies seen in the past few years, IT organizations have continuously adopted new practices in their software delivery life-cycle to improve both efficiency and effectiveness of development teams. Two of these practices are continuous integration and continuous deployment, which are part of the DevOps cycle which has helped organizations build software effectively and efficiently. These practices must be considered for new technologies such as smart contracts, where security concerns and bugs might cost more once deployed than traditional software. This paper states the importance of using a proper DevOps routine and how it is possible to apply this practice to a smart contract build. Specifically, this paper introduces a framework to implement DevOps for smart contracts development by describing multiple DevOps tools and their applicability to smart contract development. [ABSTRACT FROM AUTHOR]

A particular characteristic of disruptive products is in reengineering advanced technologies for addressing the needs of low-end consumers and/or non-consumers, to transform them into new consumers. This requires a lean co-creative analysis of requirements with all stakeholders involved. Even if a theory encourages the continuous connection of designers and users throughout the design lifecycle for agile adaptation of requirements to the new experiences of users by intersecting them with various versions of the prototype, the rigid budget and time allocated to the design project require novel approaches to clarify the right vectors of product-evolution from the very early design stages of the project lifecycle—allowing agile approaches to fine-tune the set of requirements. In this context, an analysis process of requirements that uses a constructor inspired by living systems is introduced in this paper. This constructor identifies gaps in requirement formulation and indicates areas where improvements must be undertaken. The method is applied in the case of a new cybersecurity software solution that targets micro and small companies. [ABSTRACT FROM AUTHOR]

Inadequate early scope estimation is a common problem in software projects, leading to failures in meeting project requirements. Agile projects usually do not concentrate on a comprehensive requirements analysis and specification before the start of the project, making scope assessment difficult. This paper presents the methodology for facilitating a more accurate early estimation of project scope, based on requirements information gathered in various forms (requirements models and textual descriptions) during the requirements workshop. The requirements from different sources are compiled into one list and reconciled, since they are prepared by a number of participants in the requirements workshop using different notations (UML diagrams, SysML models, Story map) and may have differences in the vocabulary. Reconciliation encompasses the unification of vocabulary, as well as the identification and the removal of overlaps in requirements. The final list of requirements is used to estimate the scope of the project in story points. The estimate can be presented to the client and used as a basis for the project contract. A case study on the application of the proposed methodology is presented, using the animal shelter information system as a development project. It demonstrates that the methodology is viable and can facilitate the gathering of a more extensive set of requirements, thus ensuring a more detailed scope estimation. [ABSTRACT FROM AUTHOR]

The cost-reducing potential of intelligent supply chains (ISCs) has been recognized by companies and researchers. This paper investigates a two-echelon steel supply chain scheduling problem that considers the parallel-batching processing and deterioration effect in the production stage and sufficient vehicles in the port delivery stage. To solve this problem, we first analyze several sufficient and necessary conditions of the optimal scheme. We then propose a heuristic algorithm based on a dynamic programming algorithm to obtain the optimal solution for a special case where the assignment of all ingots to the soaking pits is known. Based on the results of this special case, we develop a modified biased random-key genetic algorithm (BRKGA), which incorporates genetic operations based on the flower pollination algorithm (FPA) to obtain joint production and distribution schedules for the general problem. Finally, we conduct a series of computational experiments, the results of which indicate that BRKGA-FPA has certain advantages in solving quality and convergence speed issues. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to present a model of factors affecting the successful project implementation by introducing agility and artificial intelligence to increase the company's competitiveness. In the model, the multidimensional constructs describing the implementation of an agile work environment and artificial intelligence technologies and tools were developed. These multidimensional constructs are agile work environment, agile leadership, agile team skills and capabilities, improving the work of the leader in the project, adopting AI technologies in the project, and using AI solutions in a project. Their impact on successful project implementation and on the company competitiveness was tested. The fundamental reason for conducting this research and developing the model is to enhance the understanding of factors that contribute to the successful implementation of projects and to increase a company's competitiveness. Our developed model encompasses multidimensional constructs that describe the agile work environment and the utilization of AI technologies. By examining the impact of these constructs on both successful project implementation and company competitiveness, we aimed to establish a comprehensive framework that captures the relationship between agility, AI, and successful project implementation. This model serves as a valuable tool for companies seeking to improve their project implementation processes and gain a competitive edge in the market. The research was based on a sample of 473 managers/owners in medium-sized and large companies. Structural equation modeling was used to test the hypotheses. In today's turbulent environment, the results will help develop guidelines for a successful combination of agile business practices and artificial intelligence to achieve successful project implementation, increasing a company's competitiveness. [ABSTRACT FROM AUTHOR]

Transport activities and citizen mobility have a deep impact on enlarged smart cities. By analyzing Big Data streams generated through Internet of Things (IoT) devices, this paper aims to show the efficiency of using IoT analytics, as an agile optimization input for solving real-time problems in smart cities. IoT analytics has become the main core of large-scale Internet applications, however, its utilization in optimization approaches for real-time configuration and dynamic conditions of a smart city has been less discussed. The challenging research topic is how to reach real-time IoT analytics for use in optimization approaches. In this paper, we consider integrating IoT analytics into agile optimization problems. A realistic waste collection problem is modeled as a dynamic team orienteering problem with mandatory visits. Open data repositories from smart cities are used for extracting the IoT analytics to achieve maximum advantage under the city environment condition. Our developed methodology allows us to process real-time information gathered from IoT systems in order to optimize the vehicle routing decision under dynamic changes of the traffic environments. A series of computational experiments is provided in order to illustrate our approach and discuss its effectiveness. In these experiments, a traditional static approach is compared against a dynamic one. In the former, the solution is calculated only once at the beginning, while in the latter, the solution is re-calculated periodically as new data are obtained. The results of the experiments clearly show that our proposed dynamic approach outperforms the static one in terms of rewards. [ABSTRACT FROM AUTHOR]

The aim of this study is to identify practices that would enable building construction companies to adopt agile project management methodologies during the design stage of projects that use building information modelling (BIM) solutions in the designing process. Due to the benefits of agile project management methodologies, a considerable amount of research has been conducted regarding the adoption of this methodology for building construction projects. However, waterfall project management is still more widely used in the building construction industry than agile project management is. Several recent studies claim that firms could focus on adopting agile methodologies during the design stage of a building construction project because due to the advent of BIM software solutions, the design stage can be carried out in a manner such as a software development project. Since software development industry is experiencing a widespread adoption of agile methods, if the design stage of a building construction project can be carried out such as a software development project, then there is a possibility to drive agile adoption in the design stage. Based on this information, researchers found an architectural consultancy firm that has been using a BIM solution to adopt agile project management methodologies in the design stage. The authors carried out a systematic literature review and identified 10 possible practices that might drive the adoption of agile practices. Those practices were presented to the architectural consultancy firm to identify practices that they are using to successfully adopt agile methods. The findings suggest that maintaining a backlog, running sprints, engaging a cross-functional team, continuous integration, and iterative/incremental development of the design are practices that have enabled the firm to adopt agile methods. Practical and theoretical implications were derived from the findings, and suggestions for future research and limitations of the study are discussed in the discussion. Concluding remarks are provided in final section of the paper. [ABSTRACT FROM AUTHOR]

Computation intelligence techniques are important for making decisions in an agile-based offshore software development paradigm. Offshore development faces additional challenges, such as trust, communication and coordination, and socio-cultural and knowledge transfer. There is a need to determine the rankings of challenges considering their criticality concerning practitioners working in agile-based offshore software development. This paper aims to identify and rank agile challenges in offshore software development by applying computational intelligence techniques. From the systematic literature review, we identified 30 communication and coordination challenges. The distributed agile pattern catalog consists of 15 patterns, from which eight were used to solve communication and collaboration challenges. Many researchers have used fuzzy logic to quantify their results. We further applied the fuzzy analytical technique to determine the priority order concerning the criticality of the identified agile pattern catalog. The results showed that Central Code Repository Pattern ranked the most significant for solving communication and coordination challenges. Global Scrum Board Pattern and Synchronous Communication Pattern ranked second. [ABSTRACT FROM AUTHOR]

Agile project management (APM) can be defined as an iterative approach that promotes satisfying customer requirements, adjusts to change, and develops a working product in rapidly changing environments. Managers usually apply agile management as the project management approach in projects requiring extraordinary speed and flexibility in their processes. Earned value management (EVM) is a fundamental part of project management to establish practical measures. Often, managers use a task board to visually represent the work on a project and the path to completion. Still, managing an agile project can be a challenging endeavor. In this paper, we propose an agent-based model describing the management of tasks within a project using earned value assessment and a task board. Our model illustrates how EVM yields an efficient method to measure a project's performance by comparing actual progress against planned activities, thus facilitating the formulation of more accurate predicted estimations. As proof of concept, we leverage our implementation to calculate EVM performance indexes according to a performance measurement baseline (PMB) in a task board fashion. [ABSTRACT FROM AUTHOR]

The key objective of this paper is to investigate the evolution of hybrid software development methods and highlight the main difficulties that arise with regard to information systems (IS) auditing. While technology firms today are under constant pressure to deliver software faster due to emerging needs worldwide, this continuous effort leads to innovative development models, apparently driven by practice. Since modern software development is neither pure linear phases progression nor agile, a challenge arises with regards to selecting the appropriate combination of approaches that serve to reach goals and assure value creation for organizations. [ABSTRACT FROM AUTHOR]

Agile software development methods were introduced to minimize problems faced using traditional software development approaches. There are several Agile approaches used in developing software projects, these include Scrum, Extreme programming and Kanban. An Agile approach focuses on collaboration between customers and developers and encourages development teams to be self-organizing. To achieve this there are different Agile practices teams choose to use in their projects. Some teams only use one practice whilst others use a combination of practices. The most common practices used are stand-ups, user stories, Burndown chart/Burnup chart, pair programming, Epic and User stories. This paper reports on the analysis of the data collected from people involved in Agile software development teams and identifies that the combination of practices in Agile software development have an impact on the communication in the team, project requirements and project priorities, with more practices being adopted correlating with better project outcomes. [ABSTRACT FROM AUTHOR]

Lately, the software development industry is going through a slow but real transformation. Software is increasingly a part of everything, and, software developers, are trying to cope with this exploding demand through more automation. The pipelining technique of continuous integration (CI) and continuous delivery (CD) has developed considerably due to the overwhelming demand for the deployment and deliverability of new features and applications. As a result, DevOps approaches and Agile principles have been developed, in which developers collaborate closely with infrastructure engineers to guarantee that their applications are deployed quickly and reliably. Thanks to pipeline approach thinking, the efficiency of projects has greatly improved. Agile practices represent the introduction to the system of new features in each sprint delivery. Those practices may contain well-developed features or can contain bugs or failures which impact the delivery. The pipeline approach, depicted in this paper, overcomes the problems of delivery, improving the delivery timeline, the test load steps, and the benchmarking tasks. It decreases system interruption by integrating multiple test steps and adds stability and deliverability to the entire process. It provides standardization which means having an established, time-tested process to use, and can also decrease ambiguity and guesswork, guarantee quality and boost productivity. This tool is developed with an interpreted language, namely Bash, which offers an easier method to integrate it into any platform. Based on the experimental results, we demonstrate the value that this solution currently creates. This solution provides an effective and efficient way to generate, manage, customize, and automate Agile-based CI and CD projects through automated pipelines. The suggested system acts as a starting point for standard CI/CD processes, caches Docker layers for subsequent usage, and implements highly available deliverables in a Kubernetes cluster using Helm. Changing the principles of this solution and expanding it into multiple platforms (windows) will be addressed in a future discussion. [ABSTRACT FROM AUTHOR]

Featured Application: The presented results were used to design innovative mechatronic solutions: motion control algorithm of 5-axis feed drive "X-5" processing centre owned by the AVIA company, loading and forestry crane control system designed within the EU 7FP IAPP project called iLOAD. The paper presents the issue of metamodeling of Domain-Specific Languages (DSL) for the purpose of designing complex mechatronics systems. Usually, one of the problems during the development of such projects is an interdisciplinary character of the team that is involved in this endeavour. The success of a complex machine project (e.g., Computer Numerically Controlled machine (CNC), loading crane, forestry crane) often depends on a proper communication between team members. The domain-specific modelling languages developed using one of the two approaches discussed in the work, lead to a machine design that can be carried out much more efficiently than with conventional approaches. Within the paper, the Meta-Object Facility (MOF) approach to metamodeling is presented; it is much more prevalent in modern modelling software tools than Graph-Object-Property-Relationship-Role (GOPRR). The main outcome of this work is the first presentation of researchML modelling language that is the result of more than twenty ambitious research and development projects. It is effectively used within new enterprises and leads to improved traceability of the project goals. It enables for fully-featured automatic code generation which is one of the main pillars of the agile management within mechatronic system design projects. [ABSTRACT FROM AUTHOR]

Education is crucial for the growth of society, and the usage of effective learning methods is key to transmit knowledge to young students. Some initiatives present Virtual Reality technologies as a promising medium to provide active, effective, and innovative teaching. In turn, the use of this technology seems to be very attractive to students, making it possible to acquire knowledge through it. On the other hand, agile methodologies have taken an essential role within information technologies and they are key in Software Engineering education. This paper combines both areas and presents prior research about Virtual Reality experiences with educational purposes and introduces a serious VR video game that aims to promote the learning of agile methodologies in Software Engineering education, specifically the Scrum methodology. This application tries to bring students closer to their first days of work within a software development team that uses the Scrum methodology. Two evaluation processes performed with university teachers and students indicate that the developed video game meets the proposed objectives and looks promising. [ABSTRACT FROM AUTHOR]

Agile is one of the most popular contemporary management concepts and buzzwords. This paper provides an in-depth examination of the influence of the Agile concept on the discourse, thinking and practices of organizations worldwide. The paper traces the emergence and evolution of the Agile concept from inception to the present by synthesizing findings from a wide range of academic and practitioner-oriented sources. Overall, the picture that emerges from the analysis is that the Agile concept has grown considerably in popularity and has become one of the most dominant concepts in public management discourse. The popularization of Agile has, to a large extent, been driven by an active supply-side made up of actors such as consultants, coaches, and trainers. Another finding is that the Agile concept has evolved considerably over time, from its initial presentation as a narrow and specialized concept rooted in the software development community to a much broader and general approach applicable across nearly all types of organizations and industries. The broadening of the concept has led to neologisms such as Agile Marketing, Agile Government, and Agile Management. The paper ends with reflections on the current status of Agile and some speculation about the concept's likely future trajectory. [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]

Computer science is a predominantly male field of study. Women face barriers while trying to insert themselves in the study of computer science. Those barriers extend to when women are exposed to the professional area of computer science. Despite decades of social fights for gender equity in Science, Technology, Engineering, and Mathematics (STEM) education and in computer science in general, few women participate in computer science, and some of the reasons include gender bias and lack of support for women when choosing a computer science career. Open source software development has been increasingly used by companies seeking the competitive advantages gained by team diversity. This diversification of the characteristics of team members includes, for example, the age of the participants, the level of experience, education and knowledge in the area, and their gender. In open source software projects women are underrepresented and a series of biases are involved in their participation. This paper conducts a systematic literature review with the objective of finding factors that could assist in increasing women's interest in contributing to open source communities and software development projects. The main contributions of this paper are: (i) identification of factors that cause women's lack of interest (engagement), (ii) possible solutions to increase the engagement of this public, (iii) to outline the profile of professional women who are participating in open source software projects and software development projects. The main findings of this research reveal that women are underrepresented in software development projects and in open source software projects. They represent less than 10% of the total developers and the main causes of this underrepresentation may be associated with their workplace conditions, which reflect male gender bias. [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]

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]

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]

As agile software development methods are spreading through the industry, they are no longer sufficient in their original design. With the increasing adoption by various types and sizes of organizations, these methods are scaled and tailored. The most popular framework for scaling Agile is the Scaled Agile Framework®, registered trademark of Scaled Agile, Inc. Boulder, USA. Some roles originating from the agile methods, such as Product Owner, are part of the framework and are impacted by scaling and tailoring. A Product Owner role is critical to the success of projects in agile environments. This paper aims to describe and discuss the evolution of and changes in Product Owner activities since Agile started to spread in the industry until the current concept of the Product Owner role in the Scaled Agile Framework. By identifying the activities typical of Product Owners outside of the Scaled Agile Framework context and mapping these activities to the Product Owner role description in Scaled Agile Framework, the changes in Product Owner role with respect to time and role specifics in the Scaled Agile Framework are revealed. It was identified that some of the activities previously described for Product Owner are distributed between various roles in the Scaled Agile Framework. In fact, the Product Owner loses the real product ownership in Scaled Agile Framework. The loss of ownership seems connected with the fact that, in the large environments that the Scaled Agile Framework is designed for, it is impossible to cover all required activities by one role using the hierarchical structures with a top-down approach in the Scaled Agile Framework. [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]

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]

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]

Progressing digitalization of business, economy, and the society places higher education institutions (HEIs) in the center of the debate on how to effectively respond to challenges and opportunities that are thus triggered. Several facets of this process and corresponding challenges exist, including the complex question of how to match students' skills and competencies with the demands and expectations of the industry. From a different angle, considering the changing nature of work, HEIs are responsible for equipping future employees with skills necessary to work in virtual, distributed, culturally diverse, and frequently global, teams. In the domain of software development, i.e., the backbone of the digital world, the challenge HEIs need to face is paramount. For this reason, the way software development is taught at HEIs is crucial for the industry, for the economy, for the students, and for the HEIs. As there is a tendency in the industry to embrace the scrum method and seek employees equipped with skills necessary for the scrum methodology use, it is necessary to ensure that HEIs offer the students the opportunity to get exposed to scrum. By querying the challenges of switching to agile software development methodologies in senior capstone projects, this paper makes a case that software development and software development methodology form the thrust of a multi-stakeholder ecosystem that defines today's digital economy and society. In this context, the added value of this paper rests in the elaboration of a method enabling HEIs to move toward scrum in senior projects. [ABSTRACT FROM AUTHOR]

In this work [[7]], authors improved the throughput estimation using prediction produced by LSTM artificial neural networks (ANNs). It is assumed that high performance and quality, especially in the case of signal transmission, will lead to great acceptance and usability. In order to improve the bit error performance while maintaining low decoding steps, the authors of [[2]] introduce a neural network subcode that can achieve optimal decoding performance and combine it with the traditional fast successive-cancellation (SC) decoding algorithm. [Extracted from the article]

Skin and proximity effects have a considerable impact on current distribution in multistrand cable lines. Under unfavorable heat exchange conditions, some strands may be subject to excessive overheating, which may lead to serious malfunctions or even fires of the installation. The paper proposes a new criterion for a quick choice of spatial configurations, for which the effect might be minimized. A comprehensive analysis of literature cases is provided, including the recommendations of the U.S. National Code and the Canadian standard. [ABSTRACT FROM AUTHOR]

Software development stands out as one of the most rapidly expanding markets due to its pivotal role in crafting applications across diverse sectors like healthcare, transportation, and finance. Nevertheless, the sphere of cybersecurity has also undergone substantial growth, underscoring the escalating significance of software security. Despite the existence of different secure development frameworks, the persistence of vulnerabilities or software errors remains, providing potential exploitation opportunities for malicious actors. One pivotal contributor to subpar security quality within software lies in the neglect of cybersecurity requirements during the initial phases of software development. In this context, the focal aim of this study is to analyze the importance of integrating security modeling by software developers into the elicitation processes facilitated through the utilization of abuse stories. To this end, the study endeavors to introduce a comprehensive and generic model for a secure software development process. This model inherently encompasses critical elements such as new technologies, human factors, and the management of security for the formulation of abuse stories and their integration within Agile methodological processes. [ABSTRACT FROM AUTHOR]

Agile software development methodologies have become the most popular software development methods in the last few years. These methodologies facilitate rapid development. The low cost and prioritized user satisfaction make these methodologies more attractive. These methodologies were also intended for small scale developmental teams. Therefore, challenges were encountered when these methodologies were used in large-scale development teams. This study was based on the identification of factors which were discovered in our previous study. Some of the factors included "leadership strong commitment and team autonomy", "cooperative organizational culture", and "team competency—agile development expertise". A total of 147 practices were identified in this study via a systematic literature review. These practices will help practitioners and project managers to adopt agile software methodologies and encourage them to the enhance them. [ABSTRACT FROM AUTHOR]

Featured Application: The potential application of this study is to guide developers and organizations in effectively detecting and refactoring code smells, enhancing the quality and sustainability of software projects within an agile development context. (Context) Code smells indicate poor coding practices or design flaws, suggesting deeper software quality issues. While addressing code smells promptly improves software quality, traditional detection techniques often fail in continuous detection during software development. (Problem Statement) More recently, Interactive Detection (ID) technique has been proposed, enabling the detection of code smells continuously. Although the use of this technique by developers and organizations is promising, there are no practical recommendations for its use in the context of software development. (Goal) The objective of this study was to propose and evaluate the integration of ID into the widely adopted Scrum framework for agile software development. (Method) To achieve this objective, we utilized a mixed-method approach that combined a comprehensive literature review and expert knowledge to propose the integration. Furthermore, we conducted a focus group and a controlled experiment involving software development activities to evaluate this integration. (Results) The findings revealed that this integration significantly benefitted software development, such as early detection of code smells, increased effectiveness in code smell detection, and improved code quality. These findings shed light on the potential benefits of adopting this integration, offering valuable insights for developers and researchers. (Conclusions) This research emphasized the importance of continuous code smell detection as an integral part of agile development and opened avenues for further research in code quality management within agile methodologies. [ABSTRACT FROM AUTHOR]

Featured Application: In the field of medicine, daily high-stake decision-making scenarios arise. To enhance these decision-making processes, the utilization of modern machine learning techniques and their infusion with expert knowledge in a seamless manner while adhering to agile principles enables swift action and facilitates an understanding of the obtained knowledge, fostering trust in the decision-making process. Over the past few decades, machine learning has emerged as a valuable tool in the field of medicine, driven by the accumulation of vast amounts of medical data and the imperative to harness this data for the betterment of humanity. However, many of the prevailing machine learning algorithms in use today are characterized as black-box models, lacking transparency in their decision-making processes and are often devoid of clear visualization capabilities. The transparency of these machine learning models impedes medical experts from effectively leveraging them due to the high-stakes nature of their decisions. Consequently, the need for explainable artificial intelligence (XAI) that aims to address the demand for transparency in the decision-making mechanisms of black-box algorithms has arisen. Alternatively, employing white-box algorithms can empower medical experts by allowing them to contribute their knowledge to the decision-making process and obtain a clear and transparent output. This approach offers an opportunity to personalize machine learning models through an agile process. A novel white-box machine learning algorithm known as Data canyons was employed as a transparent and robust foundation for the proposed solution. By providing medical experts with a web framework where their expertise is transferred to a machine learning model and enabling the utilization of this process in an agile manner, a symbiotic relationship is fostered between the domains of medical expertise and machine learning. The flexibility to manipulate the output machine learning model and visually validate it, even without expertise in machine learning, establishes a crucial link between these two expert domains. [ABSTRACT FROM AUTHOR]

Workflow automation is taking over software development systems, helping businesses increase efficiency, accelerate production, and adapt quickly to market changes. Combined with agile principles, it has given birth to the DevOps paradigm. However, practitioners often face an important issue known as vendor lock-in caused by the cost of tool replacement or migration to different platforms. This issue could be addressed by standardising service interfaces to facilitate their integration. Linked Data is an attractive choice for implementing such a standard without sacrificing versatility. Following this approach, the Open Services for Lifecycle Collaboration (OSLC) proposal aims to build an environment where services can interoperate using standard models. Therefore, this article proposes an extension of the existing OSLC specification, based on the Event-Condition-Action (ECA) model, for event-based interoperable automation. This extension enables a new path in the field of semantic automation for OSLC services, which allows the self-interaction of services among them and with human users. The article presents the key concepts of the proposed model and exemplifies its application in an automation scenario with two real-life services. The validation of the proposal has been carried out using established ontology evaluation methods, such as coverage and similarity metrics and competency questions. [ABSTRACT FROM AUTHOR]

Agile Product Line Engineering (APLE), a relatively new approach combining the two successful methods of Agile Software Development (ASD) and Software Product Lines (SPLs), makes product lines more responsive to ever-changing customer needs or market changes. However, SPLs often fail to keep up with market demand due to high coordination costs, slow development processes, and long release cycles in the case of frequent changes in business requirements; in agile software projects, the lack of a unified specification for describing requirements leads to high coordination costs and inconvenient requirement management. Some studies in the literature have proposed optimized approaches to integrate ASD and SPLs, but they still have not covered all aspects of APLE's characteristics, and software resource reuse is rarely considered in these approaches during product line development. In view of this, we propose a collaborative framework of agile product line engineering for software resource reuse, namely ScrumOntoSPL. The ScrumOntoSPL approach efficiently merges ASD and SPL based on the agile method Scrum, SPL architecture, and ontology technology. In ScrumOntoSPL, uniform requirement specification is constructed by utilizing ontology, and the Matching Requirement with Component (MRC) process is designed to match product new requirements and software resources stored in a resource pool. In addition, we evaluated the proposed framework and approach with CMMI. In the end, a case study of a software development tool called IMC-Tool based on ScrumOntoSPL for a universal Instrument Microcontroller Chip (IMC) is discussed. The IMC-Tool case illustrates that the ScrumOntoSPL has the advantages of dynamically managing demand changes, enhancing software resource reuse, reducing coordination costs, and reducing time to market. [ABSTRACT FROM AUTHOR]

Metrics are key elements that can give us valuable information about the effectiveness of agile software development processes, particularly considering the Scrum environment. This study aims to learn about the metrics adopted to assess agile development processes and explore the impact of how the role performed by each member in Scrum contributed to increasing/reducing the perception of the importance of these metrics. The impact of years of experience in Scrum on this perception was also explored. To this end, a quantitative study was conducted with 191 Scrum professionals in companies based in Portugal. The results show that the Scrum role is not a determining factor, while individuals with more years of experience have a higher perception of the importance of metrics related to team performance. The same conclusion is observed for the business value metric of the product backlog and the percentage of test automation in the testing phase. The findings allow for extending the knowledge about Scrum project management processes and their teams, in addition to offering important insights into the implementation of metrics for software engineering companies that adopt Scrum. [ABSTRACT FROM AUTHOR]

Background: Several methodologies have been proposed since the first days of software development, from what is now named traditional/heavy methodologies, and later their counterpart, the agile methodologies. The whole idea behind agile methodologies is to produce software at a faster pace than what was considered with plan-based methodologies, which had a greater focus on documenting all tasks and activities before starting the proper software development. Problem: One issue here is that strict agilists are often against fully documenting the software architecture in the first phases of a software process development. However, architectural documentation cannot be neglected, given the well-known importance of software architecture to the success of a software project. Proposed Solution: In this article, we describe the past and current situation of agile methodologies and their relation to architecture description, as well as guidelines for future Agile Methodologies and Architecture Reconciliation. Method: We propose a literature review to understand how agile methodologies and architecture reconciliation can help in providing trends towards the success of a software project and supporting software development at a faster pace. This work was grounded in General Systems Theory as we describe the past, present, and future trends for rapid systems development through the integration of organizations, stakeholders, processes, and systems for software development. Summary of results: As extensively discussed in the literature, we found that there is a false dichotomy between agility and software architecture, and then we describe guidelines for future trends in agile methodologies and reconciliation of architecture to document agile architectures with both architectural decisions and agile processes for any system, as well as future trends to support organizations, stakeholders, processes, and systems. [ABSTRACT FROM AUTHOR]