In optimizing compilers, data structure choices directly influence the power and efficiency of practical program optimization. A poor choice of data structure can inhibit optimization or slow compilation to the point that advanced optimization features become undesirable. Recently, static single assignment form and the control dependence graph have been proposed to represent data flow and control flow propertiee of programs. Each of these previously unrelated techniques lends efficiency and power to a useful class of program optimization. Although both of these structures are attractive, the difficulty of their construction and their potential size have discouraged their use. We present new algorithms that efficiently compute these data structures for arbitrary control flow graphs. The algorithms use dominance frontiers, a new concept that may have other applications. We also give analytical and experimental evidence that all of these data structures are usually linear in the size of the original program. This paper thus presents strong evidence that these structures can be of practical use in optimization.

This paper explores compiler techniques for reducing the memory needed to load and run program executables. In embedded systems, where economic incentives to reduce both ram and rom are strong, the size of compiled code is increasingly important. Similarly, in mobile and network computing, the need to transmit an executable before running it places a premium on code size. Our work focuses on reducing the size of a program's code segment, using pattern-matching techniques to identify and coalesce together repeated instruction sequences. In contrast to other methods, our framework preserves the ability to run program executables directly, without an intervening decompression stage. Our compression framework is integrated into an industrial-strength optimizing compiler, which allows us to explore the interaction between code compression and classical code optimization techniques, and requires that we contend with the difficulties of compressing previously optimized code. The specific contributions in this paper include a comprehensive experimental evaluation of code compression for a Risc-like architecture, a more powerful pattern-matching scheme for improved identification of repeated code fragments, and a new form of profile-driven code compression that reduces the speed penalty arising from compression.

this document is intended to help determine the state of the art of optimization in production C compilers. I hope that the document itself will be useful to compiler writers, industrial and academic, and to programmers who are interested in learning what they can expect from a compiler. This program should not be used to compare compilers. When comparison shopping for compilers, the following factors should be considered: