Computer Science Library – serie

This work provides the foundation and undertanding necessary for proper design of databases for distributed and multi-database architectures. Introductory chapters help novices understand topics such as SQL, relational databases, transaction processing and deadlock detection. Subsequent sections dealing with homogenous, distributed databases, heterogenous multi-databases and federated databases explain the complexities of distributed database design.

Starting with an overview of quality software, this text identifies potential threats associated with software developments, explains how to establish an effective risk management programme and details six critical steps involved: asset valuation, security threat identification, security and control testing, safeguard assessment, economic value analyses and reiterative procedures. It also discusses various software metrics approaches used to measure software quality.

This reference is intended for experienced practitioners, consultants and students working on building practical applications. It discusses the most widely-used programming languages and their fuctional pros and cons for application and development. The author provides: a brief overview of programming languages principles and concepts; numerous diagrams, charts and sample programs; coverage of object-oriented programming and visual programming; and tables rating languages on such subjects as simplicity, data structuring, portability and efficiency.

An overview of software quality management, its key components and how they work together in forming a solid quality management programme are presented in this text. In non-technical langauge, the author identifies the eight components of QM programmes, analyzes each one in detail, and explains how to combine them to build or strengthen your programme.

This informative book goes beyond the technical aspects of data management to provide detailed analyses of quality problems and their impacts, potential solutions and how they are combined to form an overall data quality program, senior management's role, methods used to make improvements, and the life-cycle of data quality. It concludes with case studies, summaries of main points, roles and responsibilities for each individual, and a helpful listing of "dos and don'ts".