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.

The last years have witnessed a flurry of new results in the area of partial evaluation. These tutorial notes survey the field and present a critical assessment of the state of the art. 1 Introduction Partial evaluation is a source-to-source program transformation technique for specializing programs with respect to parts of their input. In essence, partial evaluation removes layers of interpretation. In the most general sense, an interpreter can be defined as a program whose control flow is determined by its input data. As Abelson points out, [43, Foreword], even programs that are not themselves interpreters have important interpreter-like pieces. These pieces contain both compile-time and run-time constructs. Partial evaluation identifies and eliminates the compile-time constructs. 1.1 A complete example We consider a function producing formatted text. Such functions exist in most programming languages (e.g., format in Lisp and printf in C). Figure 1 displays a formatting functio...

We present a new static system that reconstructs the types, regions and effects of expressions in an implicitly typed functional language that supports imperative operations on reference values. Just as types structurally abstract collections of concrete values, regions represent sets of possibly aliased reference values and effects represent approximations of the imperative behavior on regions. We introduce a static semantics for inferring types, regions and effects and prove that it is consistent with respect to the dynamic semantics of the language. We present a reconstruction algorithm that computes the types and effects of expressions and assigns regions to reference values. We prove the correctness of the reconstruction algorithm with respect to the static semantics. Finally, we discuss potential applications of our system to automatic stack allocation and parallel code generation.

Contexts have been proposed as a means of performing strictness analysis on non-flat domains. Roughly speaking, a context describes how much a sub-expression will be evaluated by the surrounding program. This paper shows how contexts can be represented using the notion of projection from domain theory. This is clearer than the previous explanation of contexts in terms of continuations. In addition, this paper describes finite domains of contexts over the non-flat list domain. This means that recursive context equations can be solved using standard fixpoint techniques, instead of the algebraic manipulation previously used. Praises of lazy functional languages have been widely sung, and so have some curses. One reason for praise is that laziness supports programming styles that are inconvenient or impossible otherwise [Joh87, Hug84, Wad85a]. One reason for cursing is that laziness hinders efficient implementation. Still, acceptable efficiency for lazy languages is at last being achieved...

We describe an escape analysis [32, 14], used to determine whether the lifetime of data exceeds its static scope. We give a new correctness proof starting directly from a semantics. Contrary to previous proofs, it takes into account all the features of functional languages, including imperative features and polymorphism. The analysis has been designed so that it can be implemented under the small complexity bound of O(n log 2 n) where n is the size of the analyzed program. We have included it in the Caml Special Light compiler (an implementation of ML), and applied it to very large programs. We plan to apply these techniques to the Java programming language. Escape analysis has been applied to stack allocation. We improve the optimization technique by determining minimal lifetime for stack allocated data, and using inlining. We manage to stack allocate 25% of data in the theorem prover Coq. We analyzed the effect of this optimization, and noticed that its main effect is to improve ...

This paper concerns the use of program slicing to perform a certain kind of program-specialization operation. The specialization operation that slicing performs is different from the specialization operations performed by algorithms for partial evaluation, supercompilation, bifurcation, and deforestation. In particular, we present an example in which the specialized program that we create via slicing could not be created as the result of applying partial evaluation, supercompilation, bifurcation, or deforestation to the original unspecialized program. Specialization via slicing also possesses an interesting property that partial evaluation, supercompilation, and bifurcation do not possess: The latter operations are somewhat limited in the sense that they support tailoring of existing software only according to the ways in which parameters of functions and procedures are used in a program. Because parameters to functions and procedures represent the range of usage patterns that the designer of a piece of software has anticipated, partial evaluation, supercompilation, and bifurcation support specialization only in ways that have already been “foreseen ” by the software’s author. In contrast, the specialization operation that slicing supports permits programs to be specialized in ways

This paper is concerned with the time-analysis of functional programs. Techniques which enable us to reason formally about a program's execution costs have had relatively little attention in the study of functional programming. We concentrate here on the construction of equations which compute the time-complexity of expressions in a lazy higher-order language. The problem with higher-order functions is that complexity is dependent on the cost of applying functional parameters. Structures called cost-closures are introduced to allow us to model both functional parameters and the cost of their application. The problem with laziness is that complexity is dependent on context. Projections are used to characterise the context in which an expression is evaluated, and cost-equations are parameterised by this context-description to give a compositional time-analysis. Using this form of context information we introduce two types of time-equation: sufficient-time equations and nece...

The effectiveness of traditional type checking in C is limited by the presence of type conversions using type casts. Because the C standard allows arbitrary type conversions between pointer types, neither C compilers, nor tools such as lint, can guarantee type safety in the presence of such type conversions. In particular, by using casts involving pointers to structures (C structs), a programmer can interpret any memory region to be of any desired type, further compromising C's weak type system. Not only do type casts make program vulnerable to type errors, they hinder program comprehension and maintenance by creating latent dependencies between seemingly independent pieces of code. To address these problems, we have developed a stronger form of type checking for C programs, called physical type checking. Physical type checking takes into account the layout of C struct fields in memory. This paper describes an inference-based physical type checking algorithm and its implementation. Ou...

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A systematic approach is given for deriving incremental programs that exploit caching. The cache-and-prune method presented in the article consists of three stages: (I) the original program is extended to cache the results of all its intermediate subcomputations as well as the final result, (II) the extended program is incrementalized so that computation on a new input can use all intermediate results on an old input, %using existing techniques, and (III) unused results cached by the extended program and maintained by the incremental program are pruned away, leaving a pruned extended program that caches only useful intermediate results and a pruned incremental program that uses and maintains only the useful results. All three stages utilize static analyses and semantics-preserving transformations. Stages I and III are simple, clean, and fully automatable. The overall method has a kind of optimality with respect to the techniques used in Stage II. The method can be applied straightforwardly to provide a systematic approach to program improvement via caching.