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"This book presents theoretical measurement models and metrics for measuring software size and complexity of large scale enterprise resource planning software. It focuses on the relationship between software complexity and quality with the aim of controlling quality and on enterprise resource planning development, performance, challenges, and even success stories"--
Enterprise resource planning (ERP) is a class of integrated software that uses software technologies to implement real-time management of business processes in an organization. ERPs normally cut across organizations, making them large and complex. Software researchers have for many years established that complexity affects software quality negatively and must therefore be controlled with novel metrics and models of evaluation that can determine when the software is at acceptable levels of quality and when not. Metrics and Models for Evaluating the Quality and Effectiveness of ERP Software is a critical scholarly publication that examines ERP development, performance, and challenges in business settings to help improve decision making in organizations that have embraced ERPs, improve the efficiency and effectiveness of their activities, and improve their return on investments (ROI). Highlighting a wide range of topics such as data mining, higher education, and security, this book is essential for professionals, software developers, researchers, academicians, and security professionals.
"This edited book discusses data analytics and complex communication networks and recommends new methodologies, system architectures, and other solutions to prevail over the current limitations faced by the field"--
With today’s technological advancements, the evolution of software has led to various challenges regarding mass markets and crowds. High quality processing must be capable of handling large groups in an efficient manner without error. Solutions that have been applied include artificial intelligence and natural language processing, but extensive research in this area has yet to be undertaken. Crowdsourcing and Probabilistic Decision-Making in Software Engineering: Emerging Research and Opportunities is a pivotal reference source that provides vital research on the application of crowd-based software engineering and supports software engineers who want to improve the manner in which software is developed by increasing the accuracy of probabilistic reasoning to support their decision-making and getting automation support. While highlighting topics such as modeling techniques and programming practices, this publication is ideally designed for software developers, software engineers, computer engineers, executives, professionals, and researchers.
Many companies want to make their sales agile. Some of them have tried to set up agile sales organizations, but such top-down approaches and big-bang rollouts seldom seem to work. This book shows how the elements of the leading agile framework “Scrum” should be applied to install agility in the salesforce, improve sales performance, and resolve typical performance issues in sales organizations. It contains concrete guidelines, real-world examples, and useful tools to create the necessary change step by step and built to last.
In today’s modernized environment, a growing number of software companies are changing their traditional engineering approaches in response to the rapid development of computing technologies. As these businesses adopt modern software engineering practices, they face various challenges including the integration of current methodologies and contemporary design models and the refactoring of existing systems using advanced approaches. Applications and Approaches to Object-Oriented Software Design: Emerging Research and Opportunities is a pivotal reference source that provides vital research on the development of modern software practices that impact maintenance, design, and developer productivity. While highlighting topics such as augmented reality, distributed computing, and big data processing, this publication explores the current infrastructure of software systems as well as future advancements. This book is ideally designed for software engineers, IT specialists, data scientists, business professionals, developers, researchers, students, and academicians seeking current research on contemporary software engineering methods.
Technology in today’s world has continued to develop into multifaceted structures. The performance of computers, specifically, has significantly increased leading to various and complex problems regarding the dependability of these systems. Recently, solutions for these issues have been based on soft computing methods; however, there lacks a considerable amount of research on the applications of these techniques within system dependability. Soft Computing Methods for System Dependability is a collection of innovative research on the applications of these processing techniques for solving problems within the dependability of computer system performance. This book will feature comparative experiences shared by researchers regarding the development of these technological solutions. While highlighting topics including evolutionary computing, chaos theory, and artificial neural networks, this book is ideally designed for researchers, data scientists, computing engineers, industrialists, students, and academicians in the field of computer science.
Mobile wireless communication systems have affected every aspect of life. By providing seamless connectivity, these systems enable almost all the smart devices in the world to communicate with high speed throughput and extremely low latency. The next generation of cellular mobile communications, 5G, aims to support the tremendous growth of interconnected things/devices (i.e., internet of things [IoT]) using the current technologies and extending them to be used in higher frequencies to cope with the huge number of different devices. In addition, 5G will provide massive capacity, high throughput, lower end-to-end delay, green communication, cost reduction, and extended coverage area. Fundamental and Supportive Technologies for 5G Mobile Networks provides detailed research on technologies used in 5G, their benefits, practical designs, and recent challenges and focuses on future applications that could exploit 5G network benefits. The content within this publication examines cellular communication, data transmission, and high-speed communication. It is designed for network analysts, IT specialists, industry professionals, software engineers, researchers, academicians, students, and scientists.
Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.