Software engineers are faced with a dilemma. They want to write general and wellstructured programs that are flexible and easy to maintain. On the other hand, generality has a price: efficiency. A specialized program solving a particular problem is often significantly faster than a general program. However, the development of specialized software is time-consuming, and is likely to exceed the production of today’s programmers. New techniques are required to solve this so-called software crisis. Partial evaluation is a program specialization technique that reconciles the benefits of generality with efficiency. This thesis presents an automatic partial evaluator for the Ansi C programming language. The content of this thesis is analysis and transformation of C programs. We develop several analyses that support the transformation of a program into its generating extension. A generating extension is a program that produces specialized programs when executed on parts of the input. The thesis contains the following main results.

This paper presents a general framework for deriving demanddriven algorithms for interprocedural data flow analysis of imperative programs. The goal of demand-driven analysis is to reduce the time and/or space overhead of conventional exhaustive analysis by avoiding the collection of information that is not needed. In our framework, a demand for data flow information is modeled as a set of data flow queries. The derived demand-driven algorithms find responses to these queries through a partial reversal of the respective data flow analysis. Depending on whether minimizing time or space is of primary concern, result caching may be incorporated in the derived algorithm. Our framework is applicable to interprocedural data flow problems with a finite domain set. If the problem's flow functions are distributive, the derived demand algorithms provide as precise information as the corresponding exhaustive analysis. For problems with monotone but non-distributive flow functions the provided dat...

This dissertation addresses a number of important issues related to interprocedural optimization. Interprocedural optimization is an integral component in a compilation system for high-performance computing. The importance of interprocedural optimization stems from two sources: it increases the context available to the optimizing compiler, and it enables programmers to use procedure calls without the concern of hurting execution time. While important, interprocedural optimization can introduce some significant compile-time costs. When interprocedural information is used to optimize a procedure, the procedure is then dependent on those interprocedural facts. Thus, even if the procedure is not edited, it may require recompilation due to changes in the interprocedural facts. In addition to these effects on recompilation, interprocedural information can also be expensive to compute. Furthermore, interprocedural optimizations can increase program size which can in turn increase compile tim...

Static single assignment (SSA) form is a program representation becoming increasingly popular for compiler-based code optimization. In this paper, we address three problems that have arisen in our use of SSA form. Two are variations to the SSA construction algorithms presented by Cytron et al. The first variation is a version of...

In this paper, we describe the program structure tree (PST), a hierarchical representation of program structure based on single entry single exit (SESE) regions of the control flow graph. We give a linear-time algorithm for finding SESE regions and for building the PST of arbitrary control flow graphs (including irreducible ones). Next, we establish a connection between SESE regions and control dependence equivalence classes, and show how to use the algorithm to find control regions in linear time. Finally, we discuss some applications of the PST. Many control-flow algorithms, such as construction of Static Single Assignment form, can be speeded up by applying the algorithms in a divide-and-conquer style to each SESE region on its own. The PST is also used to speed up data flow analysis by exploiting `sparsity'. Experimental results from the Perfect Club and SPEC89 benchmarks confirm that the PST approach finds and exploits program structure.

this article, we present a general framework for developing demand-driven interprocedural data flow analyzers and report our experience in evaluating the performance of this approach. A demand for data flow information is modeled as a set of queries. The framework includes a generic demand-driven algorithm that determines the response to a query by iteratively applying a system of query propagation rules. The propagation rules yield precise responses for the class of distributive finite data flow problems. We also describe a two-phase framework variation to accurately handle nondistributive problems. A performance evaluation of our demand-driven approach is presented for two data flow problems, namely, reaching-definitions and copy constant propagation. Our experiments show that demand-driven analysis performs well in practice, reducing both time and space requirements when compared with exhaustive analysis.

A unified model of a family of data flow algorithms, called elimination methods, is presented. The algorithms, which gather information about the definition and use of data in a program or a set of programs, are characterized by the manner in which they solve the systems of equations that describe data flow problems of interest. The unified model

Pointer aliasing analysis is crucial to compile-time analyses for languages with general-purpose pointer usage (such as C), but many aliasing methods have proven quite costly. We present a technique that partitions the statements of a program to allow separate, and therefore possibly different, pointer aliasing analysis methods to be used on independent parts of the program. This decomposition enables exploration of tradeoff between algorithm efficiency and precision. We also present a new, efficient flow-insensitive pointer aliasing algorithm, which is used together with an existing flow-sensitive aliasing algorithm in our experiments. We demonstrate our technique in the context of determining side effects and variable fetches through names containing pointer dereferences (Thru-deref MOD/REF). Initial empirical results using a combination of a flow-sensitive and a flowinsensitive aliasing analysis on the same program, demonstrate that the resulting analysis is much faster than solely ...

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The goal of this dissertation is to give programmers the ability to achieve high performance by focusing on developing parallel algorithms, rather than on architecturespecific details. The advantages of this approach also include program portability and legibility. To achieve high performance, we provide automatic compilation techniques that tailor parallel algorithms to shared-memory multiprocessors with local caches and a common bus. In particular, the compiler maps complete applications onto the specifics of a machine, exploiting both parallelism and memory. To optimize complete applications, we develop novel, general algorithms to transform loops that contain arbitrary conditional control flow. In addition, we provide new interprocedural transformations which enable optimization across procedure boundaries. These techniques provide the basis for a robust automatic parallelizing algorithm that is applicable to complete programs. The algorithm for automatic parallel code generation t...