Projection-Based Program Analysis

Projection-based program analysis techniques are remarkable for their ability to give highly detailed and useful information not obtainable by other methods. The first proposed projection-based analysis techniques were those of Wadler and Hughes for strictness analysis, and Launchbury for binding-time analysis; both techniques are restricted to analysis of first-order monomorphic languages. Hughes and Launchbury generalised the strictness analysis technique, and Launchbury the binding-time analysis technique, to handle polymorphic languages, again restricted to first order. Other than a general approach to higher-order analysis suggested by Hughes, and an ad hoc implementation of higher-order binding-time analysis by Mogensen, neither of which had any formal notion of correctness, there has been no successful generalisation to higher-order analysis. We present a complete redevelopment of monomorphic projection-based program analysis from first principles, starting by considering the analysis of functions (rather than programs) to establish bounds on the intrinsic power of projection-based analysis, showing also that projection-based analysis can capture interesting termination properties. The development of program analysis proceeds in two distinct steps: first for first-order, then higher order. Throughout we maintain a rigorous notion of correctness and prove that our techniques satisfy their correctness conditions. Our higher-order strictness analysis technique is able to capture various so-called data-structure-strictness properties such as head strictness-the fact that a function may be safely assumed to evaluate the head of every cons cell in a list for which it evaluates the cons cell. Our technique, and Hunt's PER-based technique (originally proposed at about the same time as ours), are the first techniques of any kind to capture such properties at higher order. Both the first-order and higher-order techniques are the first projection-based techniques to capture joint strictness properties-for example, the fact that a function may be safely assumed to evaluate at least one of several arguments. The first-order binding-time analysis technique is essentially the same as Launchbury's; the higher-order technique is the first such formally-based higher-order generalisation. Ours are the first projection-based termination analysis techniques, and are the first techniques of any kind that are able to detect termination properties such as head termination-the fact that termination of a cons cell implies termination of the head. A notable feature of the development is the method by which the first-order analysis semantics are generalised to higher-order: except for the fixed-point constant the higher-order semantics are all instances of a higher-order semantics parameterised by the constants defining the various first-order semantics

Local Speculative Evaluation for Distributed Graph Reduction

In a parallel graph reduction system, speculative evaluation can increase parallelism by performing potentially useful computations before they are known to be necessary. Speculative computations may be coded explicitly in a program, or they may be scheduled implicitly by the reduction system as idle processors become available. A general approach to both kinds of speculation incurs a great deal of overhead that may outweigh the benefits of speculative evaluation for fine-grain speculative tasks. The basic principle of local speculation is to permanently bind all implicit speculative computations to the sparking processor. Should all local mandatory tasks become blocked, local speculation offers a lowcost alternative to task migration. Restricting speculation to the local processor simplifies the problems of speculative task management, and opens the door for fine-grain speculative tasks. Though there are fewer opportunities for local speculation than for more general speculation, loca..