Engineering a Compiler: Edition 2

Keith D. Cooper · Linda Torczon

Ιαν 2011 · Elsevier

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This entirely revised second edition of Engineering a Compiler is full of technical updates and new material covering the latest developments in compiler technology. In this comprehensive text you will learn important techniques for constructing a modern compiler. Leading educators and researchers Keith Cooper and Linda Torczon combine basic principles with pragmatic insights from their experience building state-of-the-art compilers. They will help you fully understand important techniques such as compilation of imperative and object-oriented languages, construction of static single assignment forms, instruction scheduling, and graph-coloring register allocation. - In-depth treatment of algorithms and techniques used in the front end of a modern compiler - Focus on code optimization and code generation, the primary areas of recent research and development - Improvements in presentation including conceptual overviews for each chapter, summaries and review questions for sections, and prominent placement of definitions for new terms - Examples drawn from several different programming languages

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Dr. Cooper Ph.D., Professor, Dept. of Computer Science at Rice University, is the leader of the Massively Scalar Compiler Project at Rice, which investigates issues relating to optimization and code generation for modern machines. He is also a member of the Center for High Performance Software Research, the Computer and Information Technology Institute, and the Center for Multimedia Communication -- all at Rice. He teaches courses in Compiler Construction at the undergraduate and graduate level.Linda Torczon is a principal investigator on the Massively Scalar Compiler Project at Rice University, and the Grid Application Development Software Project sponsored by the next Generation Software program of the National Science Foundation. She also serves as the executive director of HiPerSoft and of the Los Alamos Computer Science Institute. Her research interests include code generation, interprocedural dataflow analysis and optimization, and programming environments.