Hrushikesha Mohanty – författare

This book is a collection of chapters written by experts on various aspects of big data. The book aims to explain what big data is and how it is stored and used. The book starts from  the fundamentals and builds up from there. It is intended to serve as a review of the state-of-the-practice in the field of big data handling. The traditional framework of relational databases can no longer provide appropriate solutions for handling big data and making it available and useful to users scattered around the globe. The study of big data covers a wide range of issues including management of heterogeneous data, big data frameworks, change management, finding patterns in data usage and evolution, data as a service, service-generated data, service management, privacy and security. All of these aspects are touched upon in this book. It also discusses big data applications in different domains. The book will prove useful to students, researchers, and practicing database and networking engineers.

This book is focused on the advancements in the field of software testing and the innovative practices that the industry is adopting. Considering the widely varied nature of software testing, the book addresses contemporary aspects that are important for both academia and industry. There are dedicated chapters on seamless high-efficiency frameworks, automation on regression testing, software by search, and system evolution management. There are a host of mathematical models that are promising for software quality improvement by model-based testing. There are three chapters addressing this concern. Students and researchers in particular will find these chapters useful for their mathematical strength and rigor. Other topics covered include uncertainty in testing, software security testing, testing as a service, test technical debt (or test debt), disruption caused by digital advancement (social media, cloud computing, mobile application and data analytics), and challenges and benefits of outsourcing. The book will be of interest to students, researchers as well as professionals in the software industry.

This book focuses on web service specification, search, composition, validation, resiliency, security and engineering, and discusses various service specification standards like WSDL, SAWSDL, WSMO and OWLS. The theory and associated algorithms for service specification verification are detailed using formal models like Petrinet, FSM and UML. The book also explores various approaches proposed for web service search and composition, highlighting input/output, parameter-based search, and selection of services based on both functional and non-functional parameters. In turn, it examines various types of composite web services and presents an overview of popular fault handling strategies for each of these types. Lastly, it discusses the standards used for implementing web service security on the basis of a case study, and introduces the Web Service Development Life Cycle (WSDLC), which defines co-operation between several industry partners to develop web services in a more structured way.

This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.