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

Abstract. In safety-critical and high-reliability systems, software development and maintenance are costly endeavors. The cost can be reduced if software errors can be identified through automatic tools such as program analyzers and compile-time software checkers. To this effect, this paper describes the architecture and implementation of a software tool that uses lightweight static analysis to detect discrepancies (i.e., software defects such as exception-raising code or hidden failures) in large commercial telecom applications written in Erlang. Our tool, starting from virtual machine bytecode, discovers, tracks, and propagates type information which is often implicit in Erlang programs, and reports warnings when a variety of type errors and other software discrepancies are identified. Since the analysis currently starts from bytecode, it is completely automatic and does not rely on any user annotations. Moreover, it is effective in identifying software defects even in cases where source code is not available, and more specifically in legacy software which is often employed in high-reliability systems in operation, such as telecom switches. We have applied our tool to a handful of real-world applications, each consisting of several hundred thousand lines of code, and describe our experiences and the effectiveness of our techniques. Keywords: Compile-time program checking, software development, software tools, defect detection, software quality assurance.

Many large software systems originate from untyped scripting language code. While good for initial development, the lack of static type annotations can impact code-quality and performance in the long run. We present an approach for integrating untyped, or dynamically typed, code and typed code in the same system to allow an initial prototype to be smoothly evolved into an efficient and robust program. Our approach adds like types, a novel intermediate point between dynamic and static typing. Locally to their scope, like types variables are checked statically, but as they may be bound to dynamic values their usage is checked dynamically. Thus like types provide some of the benefits of static typing without substantially decreasing the expressiveness of the language. We provide a formal account of like types in a core object calculus and evaluate their applicability in the context of a new scripting language. 1.

Developers who write code in a statically typed language are denied the ability to obtain dynamic feedback by executing their code during periods when it fails to type-check. They are further confined to the static typing discipline during times in the development process where it does not yield the highest productivity. If they opt instead to use a dynamic language, they forgo the many benefits of static typing. We present a novel approach to giving developers the benefits of both static and dynamic typing, throughout the development process, and without the burden of manually separating their program into statically- and dynamically-typed parts. Our approach relaxes the static type system and provides a semantics for many type-incorrect programs. We implemented our approach in a publicly available tool, DuctileJ, for the Java language. In case studies, DuctileJ conferred benefits both during prototyping and during the evolution of existing code. Categories and subject descriptors: General terms: Keywords:

We describe and document the techniques used in TYPER, a fully automatic type annotator for ERLANG programs based on constraint-based type inference of success typings (a notion closely related to principal typings). The inferred typings are fine-grained and the type system currently includes subtyping and subtype polymorphism but not parametric polymorphism. In particular, we describe and illustrate through examples a type inference algorithm tailored to ERLANG’s characteristics which is modular, reasonably fast, and appears to scale well in practice.