Many program analyses are naturally formulated and implemented using inclusion constraints. We present new results on the scalable implementation of such analyses based on two insights: first, that online elimination of cyclic constraints yields orders-of-magnitude improvements in analysis time for large problems; second, that the choice of constraint representation affects the quality and efficiency of online cycle elimination. We present an analytical model that explains our design choices and show that the model's predictions match well with results from a substantial experiment.

Soft type systems provide the benefits of static type checking for dynamically typed languages without rejecting untypable programs. A soft type checker infers types for variables and expressions and inserts explicit run-time checks to transform untypable programs to typable form. We describe a practical soft type system for R4RS Scheme. Our type checker uses a representation for types that is expressive, easy to interpret, and supports efficient type inference. Soft Scheme supports all of R4RS Scheme, including procedures of fixed and variable arity, assignment, continuations, and top-level definitions. Our implementation is available by anonymous FTP. The first author was supported in part by the United States Department of Defense under a National Defense Science and Engineering Graduate Fellowship. y The second author was supported by NSF grant CCR-9122518 and the Texas Advanced Technology Program under grant 003604-014. 1 Introduction Dynamically typed languages like Scheme...

DrScheme is a programming environment for Scheme. It fully integrates a graphicsenriched editor, a parser for multiple variants of Scheme, a functional read-eval-print loop, and an algebraic printer. The environment is especially useful for students, because it has a tower of syntactically restricted variants of Scheme that are designed to catch typical student mistakes and explain them in terms the students understand. The environment is also useful for professional programmers, due to its sophisticated programming tools, such as the static debugger, and its advanced language features, such as units and mixins. Beyond the ordinary programming environment tools, DrScheme provides an algebraic stepper, a context-sensitive syntax checker, and a static debugger. The stepper reduces Scheme programs to values, according to the reduction semantics of Scheme. It is useful for explaining the semantics of linguistic facilities and for studying the behavior of small programs. The syntax checker annotates programs with font and color changes based on the syntactic structure of the program. On demand, it draws arrows that point from bound to binding occurrences of identifiers. It also supports α-renaming. Finally, the static debugger provides a type inference system that explains specific inferences in terms of a value-flow graph, selectively overlaid on the program text.

. Teaching introductory computing courses with Scheme elevates the intellectual level of the course and thus makes the subject more appealing to students with scientific interests. Unfortunately, the poor quality of the available programming environments negates many of the pedagogic advantages. To overcome this problem, we have developed DrScheme, a comprehensive programming environment for Scheme. It fully integrates a graphics-enriched editor, a multi-lingual parser that can process a hierarchy of syntactically restrictive variants of Scheme, a functional read-eval-print loop, and an algebraically sensible printer. The environment catches the typical syntactic mistakes of beginners and pinpoints the exact source location of run-time exceptions. DrScheme also provides an algebraic stepper, a syntax checker and a static debugger. The first reduces Scheme programs, including programs with assignment and control effects, to values (and effects). The tool is useful for explaining the sem...

. This paper argues that for many algorithms, and static analysis

BANE (the Berkeley Analysis Engine) is a publicly available toolkit for constructing type- and constraint-based program analyses. We describe the goals of the project, the rationale for BANE's overall design, some examples coded in BANE, and briefly compare BANE with other program analysis frameworks.

There is a tension in program analysis between precision and efficiency. In constraint-based program analysis, at one extreme methods based on unification of equality constraints over terms are very fast but often imprecise. At the other extreme, methods based on the resolution of inclusion constraints over set expressions are quite precise, but are often inefficient in practice. We describe a parameterized framework for constraint-based program analyses that allows the analysis designer to embed terms and set expressions within each other. Constraints over these mixed expressions are partially between equality and inclusion, which enables an entire spectrum of program analyses with varying degrees of precision and efficiency to be expressed. We also show that there are interesting analyses that take advantage of this mixture. In particular, we report on the design and implementation of an uncaught exception analysis for core ML. Our results show that the analysis approaches...

We present a static analysis that detects potential runtime exceptions that are raised and never handled inside Standard ML(SML) programs. This analysis will predict abrupt termination of SML programs, which is SML's only one "safety hole." Even though SML program's control flow and exception flow are in general mutually dependent, analyzing the two flows are safely decoupled. Program's control-flow is firstly estimated by simple case analysis of call expressions. Using this call-graph information, program's exception flow is derived as set-constraints, whose least model is our analysis result. Both of these two analyses are proven safe and the reasons behind each design decision are discussed. Our implementation of this analysis has been applied to realistic SML programs and shows a promising cost-accuracy performance. For the ML-Lex program, for example, the analysis takes 1.36 seconds and it reports 3 may-uncaught exceptions, which are exactly the exceptions that can really escape. ...

Abstract not found

. Primitive recursion is a well known syntactic restriction on recursive definitions which guarantees termination. Unfortunately many natural definitions, such as the most common definition of Euclid's GCD algorithm, are not primitive recursive. Walther has recently given a proof system for verifying termination of a broader class of definitions. Although Walther's system is highly automatible, the class of acceptable definitions remains only semi-decidable. Here we simplify Walther's calculus and give a syntactic criterion on definitions which guarantees termination. This syntactic criteria generalizes primitive recursion and handles most of the examples given by Walther. We call the corresponding class of acceptable definitions "Walther recursive". 1 Introduction One of the central problems in verification logics, such as the Boyer-Moore theorem prover [2], [10], is the need to prove termination for recursive definitions. Many logics, such as that of Boyer and Moore, assu...