An Alias occurs at some program point during execution when two or more names exist for the same location. We've investigated the theoretical difficulty of determining the aliases of a program, developed an approximation algorithm for solving for aliases in C like languages, and explored the precision (i.e., closeness of our approximate solution to the actual solution) and time behavior of this algorithm. Myers [Mye81] explored the theoretical difficulty of solving flow sensitive interprocedural data flow problems in the presence of aliasing. However, he did not make any claims about the difficulty of determining aliases. We isolate various programming language mechanisms that create aliases. The complexity of the alias problem (i.e., determining the aliases for a program) induced by each mechanism and their combinations is considered s...

A shape-analysis algorithm statically analyzes a program to determine information about the heap-allocated data structures that the program manipulates. The results can be used to understand or verify programs. They also contain information valuable for debugging, compile-time garbage collection, instruction scheduling, and parallelization.

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 ...

People benefit from tightly integrated systems that can be designed, realized and evolved affordably. Unfortunately, common software design methods do not easily accommodate requirements for tightly integrated systems. Indeed, when used to meet such requirements, common methods tend to yield unnecessarily complex structures that complicate design and realization and that inhibit subsequent evolution. After substantiating this claim, I present the mediator method as a solution. This method combines behavioral entity-relationship (ER) modeling for design with a mediator approach to implementation. The mediator method is better than common methods for designing, realizing, and evolving many integrated systems. I support this claim both by rational argument from simplifying models and by careful...

Programs written in high-level programming languages and in particular object-oriented languages make heavy use of references and dynamically allocated structures. As a result, precise analysis of such features is critical for producing efficient implementations. The information produced by this analysis is invaluable for compiling programs for both sequential and parallel machines. This paper presents a new structure analysis technique handling references and dynamic structures which enables precise analysis of infinite recursive data structures. The precise analysis depends on an enhancement of Chase et al.'s Storage Shape Graph (SSG) called the Abstract Storage Graph (ASG) which extends SSG's with choice nodes, identity paths, and specialized storage nodes and references. These extensions allow ASG's to precisely describe singly- and multiply-linked lists as well as a number of other pointer structures such as octrees, and to analyze programs which manipulate them. We des...

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High-performance architectures rely upon powerful optimizing and parallelizing compilers to maximize performance. Such compilers need accurate program analysis to enable their performance-enhancing transformations. In the domain of program analysis for parallelization, pointer analysis is a difficult and increasingly common problem. When faced with dynamic, pointer-based data structures, existing solutions are either too limited in the types of data structures they can analyze, or require too much effort on the part of the programmer. In this paper we present a powerful description language for expressing the aliasing properties of dynamic data structures. Such descriptions provide the compiler with better information during alias analysis, and require only minimal effort from the programmer. Ultimately, this enables a more accurate program analysis, and an increased application of performance-enhancing transformations.

A major challenge facing computer architects today is designing cost-effective hardware that executes multiple operations simultaneously. The goal of such designs is to improve performance by taking advantage of fine-grain parallelism. In this dissertation, I study vector architectures, the oldest of several processor designs that support fine-grain parallelism. Because implementing a cost-effective processor that performs well requires studying not only the design of processors but also the design of algorithms for compilers, this dissertation encompasses aspects of both hardware and software design. In the first half of this dissertation, I demonstrate that a vector architecture is a cost-effective processor that supports fine-grain parallelism. I show that implementing a vector architecture is no more costly than implementing a superscalar architecture, which is currently popular among designers of VLSI microprocessors. I then show that programs that are rich in parallelism tend als...

Software is difficult and costly to modify correctly. Automating tiresome mechanical tasks such as program restructuring is one approach to reducing the burden of software maintenance. Several restructuring tools have been proposed and prototyped, all centered on the concept of meaning-preserving transformations similar in spirit to compiler optimizations. Like optimizing compilers, these tools rely on static analysis to reason about the correctness of program changes. However, the cost (in both time and space) of static analysis serves as the limiting factor for transformation tools, resulting in slow, complex tool designs that scale poorly for use on large systems. To reduce these costs, this thesis proposes efficient, demand-driven flow analysis techniques as an alternate to traditional, compiler-based methods. These techniques operate directly on the abstract syntax tree (AST), the data structure most appropriate for use in a source-to-source tool architecture. By eliminating the need for other program representations such as the standard control flow graph (CFG) or program dependence graph (PDG), this approach greatly simplifies program modification. A key contribution of this work is the idea of virtual control flow, a method for computing the control successors or predecessors of individual AST expressions on demand. This method handles all types of structured and unstructured jumps found in an imperative programming language such as C. Virtual control flow couples well with demand-driven data flow analysis to minimize the cost of determining semantic information. To conservatively estimate data flow relationships, the effects of aliasing between memory locations can be inexpensively approximated using flow-insensitive points-to analysis based on type inference. These techniques were implemented in a prototype tool called Cstructure to support a simple restructuring transformation for reordering program statements. To check that this transformation does not change the program's behavior requires syntax, control flow and data dependence analysis. Experimental results on three programs ranging in size from 72,000 to 213,000 lines of code demonstrate the performance advantages of such aggressive demand-driven approaches. For the largest program, gcc, check times for the average statement were 50 milliseconds on a desktop workstation.

Data-flow analysis computes information about the potential behavior of a program in terms of the definitions and uses of data objects. Data-flow analysis for programs written in languages such as FORTRAN has been well developed. However, due to the presence of pointers, data-flow analysis has been less successful for languages such as C, C++, LISP, and Fortran 90. Data-flow analysis algorithms can be classified into two categories: flow-sensitive and flowinsensitive. To improve efficiency, flow-insensitive interprocedural analyses do not make use of the intraprocedural control flow information associated with individual procedures. Since pointer-induced aliases can change within a procedure, applying known flow-insensitive analyses can result in either incorrect or overly conservative solutions. In this paper, we present a flowinsensitive data-flow analysis algorithm that computes interprocedural pointer-induced aliases. We improve the precision of our analysis by (1) making use of c...