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Abstract Data Types in Standard ML Rachel Harrison University of Southampton, UK This book presents a thorough treatment of data abstraction within a functional framework. The approach to abstract data types strikes a balance between the theoretical and the practical, stressing the importance of producing reliable, high quality code which is robust and reusable. Exercises are provided, as well as numerous annotated algorithms in Standard ML. Emphasis is placed on the key concepts of specification, modularity and generality. Each chapter shows how to specify, apply and implement generic abstract data types, and the specifications are used to verify and validate the correctness of the implementations. Students of software engineering will find this book particularly attractive--for courses such as advanced programming, program design, algorithms and data structures, and program specification. It will also serve as a useful post-introductory text for courses on functional programming.