Handbook On Artificial Intelligence Empowered Applied Software Engineering

This book provides a structured overview of artificial intelligence-empowered applied software engineering. Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. This book at hand, devoted to Novel Methodologies to Engineering Smart Software Systems Novel Methodologies to Engineering Smart Software Systems, constitutes the first volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in (i) Artificial Intelligence-Assisted Software Development and (ii) Software Engineering Tools to develop Artificial Intelligence Applications, as well as a detailed Survey of Recent Relevant Literature. Professors, researchers, scientists, engineers and students in artificial intelligence, software engineering and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.

Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions, lead current research toward the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. The book at hand, devoted to Smart Software Applications in Cyber-Physical Systems, constitutes the second volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in Smart Software Applications in (i) Scientific Document Processing, (ii) Enterprise Modeling, (iii) Education, (iv) Health care and Medicine, and (v) Infrastructure Monitoring. Professors, researchers, scientists, engineers, and students in artificial intelligence, software engineering, and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.

Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions, lead current research toward the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. The book at hand, devoted to Smart Software Applications in Cyber-Physical Systems, constitutes the second volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in Smart Software Applications in (i) Scientific Document Processing, (ii) Enterprise Modeling, (iii) Education, (iv) Health care and Medicine, and (v) Infrastructure Monitoring. Professors, researchers, scientists, engineers, and students in artificial intelligence, software engineering, and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.

In a world driven by technology and data, classical computing faces limitations in tackling complex challenges like climate modeling and financial risk assessment. These barriers impede our aspirations to revolutionize industries and solve intricate real-world problems. To bridge this gap, we must embrace quantum computing. Edited by Alex Khang PH, Principles and Applications of Quantum Computing is a transformative solution to this challenge. It delves into the interdisciplinary realms of computer science, physics, and mathematics, unveiling the incredible potential of quantum computing, which outperforms supercomputers by 158 million times. This technology, rooted in quantum mechanics, offers solutions to global problems and opens new frontiers in AI, cybersecurity, finance, drug development, and more. By engaging with this book, you become a pioneer in the quantum revolution, contributing to reshaping the limits of what's achievable in our digital age.

"This book provides an overview of useful techniques in artificial intelligence for future software development along with critical assessment for further advancement"--Provided by publisher.

It is well known that high-tech startups need to innovate to survive, yet the failure rate for innovation is shockingly high. Nearly three out of four new products or services, i.e., their startups, miss their revenue and profit goals–or fail entirely. It’s a misconception that high-tech startups fail only because of the failing products or finances. The failures could also be because of erroneous choice of technology platforms, development teams or methodology, or even the project execution. Accordingly, this book takes a holistic view of a startups’ aesthetics that enables it to become attractive for all stakeholders especially investors in all aspects of its operations at all stages of its lifecycle. This book: Looks at aspects of venture capital financing and what investors look for in a contemporary startup. Shows how only an overarching aspiration for a startup to become a Unicorn is sufficient to explain the typical characteristics of legendry Silicon Valley Unicorns like Google, Facebook, LinkedIn, and Twitter. Covers major application areas of current/future interest, namely, intelligent systems, intelligent assistants, wireless sensor networks, Internet of Things (IoT), and blockchain systems. Introduces the contemporary skills-set in demand for Startups. To succinctly cover all aspects of a contemporary startup, Unleashing the Startup Unicorn is organized to reflect the natural grouping of competencies that are essential for entrepreneurial ventures–from conception to successful exit. To understand and analyze these competencies, the book uses an extended 9S model inspired by the pioneering McKinsey 7S model.

This book offers a practical introduction to the use of artificial intelligence (AI) techniques to improve and optimise the various phases of the software development process, from the initial project planning to the latest deployment. All chapters were written by leading experts in the field and include practical and reproducible examples. Following the introductory chapter, Chapters 2-9 respectively apply AI techniques to the classic phases of the software development process: project management, requirement engineering, analysis and design, coding, cloud deployment, unit and system testing, and maintenance. Subsequently, Chapters 10 and 11 provide foundational tutorials on the AI techniques used in the preceding chapters: metaheuristics and machine learning. Given its scope and focus, the book represents a valuable resource for researchers, practitioners and students with a basic grasp of software engineering.

Readings in Artificial Intelligence and Software Engineering covers the main techniques and application of artificial intelligence and software engineering. The ultimate goal of artificial intelligence applied to software engineering is automatic programming. Automatic programming would allow a user to simply say what is wanted and have a program produced completely automatically. This book is organized into 11 parts encompassing 34 chapters that specifically tackle the topics of deductive synthesis, program transformations, program verification, and programming tutors. The opening parts provide an introduction to the key ideas to the deductive approach, namely the correspondence between theorems and specifications and between constructive proofs and programs. These parts also describes automatic theorem provers whose development has be designed for the programming domain. The subsequent parts present generalized program transformation systems, the problems involved in using natural language input, the features of very high level languages, and the advantages of the programming by example system. Other parts explore the intelligent assistant approach and the significance and relation of programming knowledge in other programming system. The concluding parts focus on the features of the domain knowledge system and the artificial intelligence programming. Software engineers and designers and computer programmers, as well as researchers in the field of artificial intelligence will find this book invaluable.