Zhi Jin Livres

Focusing on the intersection of environmental modeling and requirements engineering, this book presents innovative approaches for managing requirements in software-intensive systems. It emphasizes the importance of understanding environmental contexts to enhance system performance and reliability. The authors explore various modeling techniques and methodologies, providing practical insights and case studies. This resource is essential for software engineers and researchers aiming to improve the development process by integrating environmental considerations into requirements engineering.

The book explores three primary approaches to improving software productivity and reliability: engineering, formal, and knowledge-based. It emphasizes that relying solely on one method is insufficient for achieving optimal results. Instead, it advocates for the integration of these diverse approaches, highlighting this integration as a significant area of research in the field.

This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data. TBCNNsare related to existing convolutional neural networks (CNNs) and recursive neural networks (RNNs), but they combine the merits of both: thanks to their short propagation path, they are as efficient in learning as CNNs; yet they are also as structure-sensitive as RNNs. In this book, readers will also find a comprehensive literature review of related work, detailed descriptions of TBCNNs and their variants, and experiments applied to program analysis and natural language processing tasks. It is also an enjoyable read for all those with a general interest in deep learning.