A large number of call graph construction algorithms for object-oriented and functional languages have been proposed, each embodying different tradeoffs between analysis cost and call graph precision. In this article we present a unifying framework for understanding call graph construction algorithms and an empirical comparison of a representative set of algorithms. We first present a general parameterized algorithm that encompasses many well-known and novel call graph construction algorithms. We have implemented this general algorithm in the Vortex compiler infrastructure, a mature, multilanguage, optimizing compiler. The Vortex implementation provides a “level playing field ” for meaningful cross-algorithm performance comparisons. The costs and benefits of a number of call graph construction algorithms are empirically assessed by applying their Vortex implementation to a suite of sizeable (5,000 to 50,000 lines of code) Cecil and Java programs. For many of these applications, interprocedural analysis enabled substantial speed-ups over an already highly optimized baseline. Furthermore, a significant fraction of these speed-ups can be obtained through the use of a scalable, near-linear time call graph construction algorithm.

Abstract. Precise type information is invaluable for analysis and optimization of object-oriented programs. Some forms of polymorphism found in object-oriented languages pose significant difficulty for type inference, in particular data polymorphism. Agesen’s Cartesian Product Algorithm (CPA) can analyze programs with parametric polymorphism in a reasonably precise and efficient manner, but CPA loses precision for programs with data polymorphism. This paper presents a precise constraintbased type inference system for Java. It uses Data-Polymorphic CPA (DCPA), a novel constraint-based type inference algorithm which extends CPA with the ability to accurately and efficiently analyze data polymorphic programs. The system is implemented for the full Java language, and is used to statically verify the correctness of Java downcasts. Benchmark results are given which show that DCPA is significantly more accurate than CPA and the efficiency of DCPA is close to CPA. 1

In prior work we introduced a pure type assignment system that encompasses a rich set of property types, including intersections, unions, and universally and existentially quantified dependent types. In this paper

We present # CIL , a typed #-calculus which serves as the foundation for a typed intermediate language for optimizing compilers for higher-order polymorphic programming languages. The key innovation of # CIL is a novel formulation of intersection and union types and flow labels on both terms and types. These flow types can encode polyvariant control and data flow information within a polymorphically typed program representation. Flow types can guide a compiler in generating customized data representations in a strongly typed setting. Since # CIL enjoys confluence, standardization, and subject reduction properties, it is a valuable tool for reasoning about programs and program transformations.

Refinement types allow many more properties of programs to be expressed and statically checked than conventional type systems. We present a practical algorithm for refinement-type checking in a -calculus enriched with refinement-type annotations. We prove that our basic algorithm is sound and complete, and show that every term which has a refinement type can be annotated as required by our algorithm. Our positive experience with an implementation of an extension of this algorithm to the full core language of Standard ML demonstrates that refinement types can be a practical program development tool in a realistic programming language. The required refinement type definitions and annotations are not much of a burden and serve as formal, machine-checked explanations of code invariants which otherwise would remain implicit. 1 Introduction The advantages of statically-typed programming languages are well known, and have been described many times (e.g. see [Car97]). However, conventional ty...

We show a type-based method for useless variable elimination, i.e., transformation that eliminates variables whose values contribute nothing to the final outcome of a computation, and prove its correctness. The algorithm is a surprisingly simple extension of the usual type reconstruction algorithm. Our method seems more attractive than Wand and Siveroni's 0CFA-based method in many respects. First, it is efficient: it runs in time almost linear in the size of an input expression for a simply-typed -calculus, while the 0CFA-based method may require a cubic time. Second, our transformation can be shown to be optimal among those that preserve well-typedness, both for the simply-typed language and for an ML-style polymorphically-typed language. On the other hand, the 0CFA-based method is not optimal for the polymophically-typed language. ANY OTHER IDENTIFYING INFORMATION OF THIS REPORT Summary has been submitted for publication. Up-to-date version of this report will be available through ...

We develop a system of type assignment with intersection types, union types, indexed types, and universal and existential dependent types that is sound in a call-by- value functional language. The combination of logical and computational principles underlying our formulation naturally leads to the central idea of type-checking subterms in evaluation order. We thereby provide a uniform generalization and explanation of several earlier isolated systems. The proof of progress and type preservation, usually formulated for closed terms only, relies on a notion of definite substitution.

This dissertation demonstrates that interprocedural analysis can be both practical and effective for sizeable object-oriented programs. Although frequent procedure calls and message sends are important structuring techniques in object-oriented languages, they can also severely degrade application run-time performance. A number of analyses and transformations have been developed that attack this performance problem by enabling the compile-time replacement of message sends with procedure calls and of procedure calls with inlined copies of their callees. Despite the success of these techniques, even after they are applied it is extremely likely that some message sends and non-inlined procedure calls will remain in the program. These remaining call sites can force an optimizing compiler to make pessimistic assumptions about program behavior, causing it to miss opportunities for potentially profitable optimizations. Interprocedural analysis is one well-known technique for enabling an optimizing compiler to more precisely model the effects of noninlined calls, thus reducing their impact on application performance.

In PLT Scheme, programs consist of modules with contracts. The latter describe the inputs and outputs of functions and objects via predicates. A run-time system enforces these predicates; if a predicate fails, the enforcer raises an exception that blames a specific module with an explanation of the fault. In this paper, we show how to use such module contracts to turn set-based analysis into a fully modular parameterized analysis. Using this analysis, a static debugger can indicate for any given contract check whether the corresponding predicate is always satisfied, partially satisfied, or (potentially) completely violated. The static debugger can also predict the source of potential errors, i.e., it is sound with respect to the blame assignment of the contract system.

Most real-time systems require responsive interrupt handling.