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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.

Abstract This paper describes the development of the programming language Erlang during the period 1985-1997. Erlang is a concurrent programming language designed for programming large-scale distributed soft real-time control applications. The design of Erlang was heavily influenced by ideas from the logic and functional programming communities. Other sources of inspiration came from languages such as Chill and Ada which are used in industry for programming control systems. 1 Introduction This paper describes the development of the Erlang programming language. Erlang is a language which draws heavily from various traditions in the logic, functional and realtime control programming communities. Our goal was to make a language which could be used for building large soft real-time control systems. By large I mean systems with possibly millions of lines of code. By a soft real-time system I mean a system which does not fail catastrophically if a real-time deadline is missed.

product, having over a million lines of Erlang code. This product (the AXD301) is thought to be one of the most reliable products ever made by Ericsson.

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...

Many general-purpose, object-oriented scripting languages are dynamically typed, which provides flexibility but leaves the programmer without the benefits of static typing, including early error detection and the documentation provided by type annotations. This paper describes Diamondback Ruby (DRuby), a tool that blends Ruby’s dynamic type system with a static typing discipline. DRuby provides a type language that is rich enough to precisely type Ruby code we have encountered, without unneeded complexity. When possible, DRuby infers static types to discover type errors in Ruby programs. When necessary, the programmer can provide DRuby with annotations that assign static types to dynamic code. These annotations are checked at run time, isolating type errors to unverified code. We applied DRuby to a suite of benchmarks and found several bugs that would cause run-time type errors. DRuby also reported a number of warnings that reveal questionable programming practices in the benchmarks. We believe that DRuby takes a major step toward bringing the benefits of combined static and dynamic typing to Ruby and other object-oriented languages.

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The system FT of ordering constraints over feature trees has been introduced as an extension of the system FT of equality constraints over feature trees. We investigate the first-order theory of FT and its fragments, both over finite trees and over possibly infinite trees. We prove that the first-order theory of FT is undecidable, in contrast to the first-order theory of FT which is well-known to be decidable. We determine the complexity of the entailment problem of FT with existential quantification to be PSPACE-complete, by proving its equivalence to the inclusion problem of non-deterministic finite automata. Our reduction from the entailment problem to the inclusion problem is based on a new alogrithm that, given an existential formula of FT , computes a finite automaton which accepts all its logic consequences.

. We study entailment of structural and nonstructural recursive subtyping constraints. Constraints are formal inequalities between type expressions, interpreted over an ordered set of possibly infinite labeled trees. The nonstructural ordering on trees is the one introduced by Amadio and Cardelli for subtyping with recursive types. The structural ordering compares only trees with common shape. A constraint set entails an inequality if every assignment of meanings (trees) to type expressions that satisfies all the constraints also satisfies the inequality. In this paper we prove that nonstructural subtype entailment is PSPACEhard, both for finite trees (simple types) and infinite trees (recursive types). For the structural ordering we prove that subtype entailment over infinite trees is PSPACE-complete, when the order on trees is generated from a lattice of type constants. Since structural subtype entailment over finite trees has been shown to be coNP-complete these are the first comple...

Abstract. JavaScript is the main scripting language for Web browsers, and it is essential to modern Web applications. Programmers have started using it for writing complex applications, but there is still little tool support available during development. We present a static program analysis infrastructure that can infer detailed interpretation. The analysis is designed to support the full language as defined in the ECMAScript standard, including its peculiar object model and all built-in functions. The analysis results can be used to detect common programming errors – or rather, prove their absence, and for producing type information for program comprehension. Preliminary experiments conducted on real-life JavaScript code indicate that the approach is promising regarding analysis precision on small and medium size programs, which constitute the majority of JavaScript applications. With potential for further improvement, we propose the analysis as a foundation for building tools that can aid JavaScript programmers. 1