Engineering a Compiler, Third Edition covers the latest developments in compiler technology, with new chapters focusing on semantic elaboration (the problems that arise in generating code from the ad-hoc syntax-directed translation schemes in a generated parser), on runtime support for naming and addressability, and on code shape for expressions, assignments and control-structures. Leading educators and researchers, Keith Cooper and Linda Torczon, have revised this popular text with a fresh approach to learning important techniques for constructing a modern compiler, combining basic principles with pragmatic insights from their own experience building state-of-the-art compilers.

Presents in-depth treatments of algorithms and techniques used in the front end of a modern compiler
Pays particular attention to code optimization and code generation, both primary areas of recent research and development
Focuses on how compilers (and interpreters) implement abstraction, tying the underlying knowledge to students’ own experience and to the languages in which they have been taught to program
Covers bottom-up methods of register allocation at the local scope

Informazioni sugli autori

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.

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