International audienceThis paper presents a program analysis to estimate un-caught exceptions in ML programs. This analysis relies on unification-based type inference in a non-standard type system, using rows to approximate both the flow of escaping exceptions (a la effect systems) and the flow of result values (a la control-flow analyses). The resulting analysis is efficient and precise; in particular, arguments carried by exceptions are accurately handled
In this paper we present the first exception analysis for a non-strict language. We augment a simply...
Texte intégral accessible uniquement aux membres de l'Université de LorraineBy analysing the way ML ...
AbstractExceptions are a feature often provided by programming languages to deal with computations w...
International audienceThis paper presents a program analysis to estimate uncaught exceptions in ML p...
This paper presents a program analysis to estimate uncaught exceptions in ML programs. This analysis...
AbstractWe present a static analysis that detects potential runtime exceptions that are raised and n...
We present a static analysis that detects potential runtime exceptions that are raised and never han...
We describe our experiences with an exception analysis tool for Standard ML. Information about excep...
We present in this paper an extension to the ML type system by which it is possible to statically es...
AbstractWe present a static analysis that detects potential runtime exceptions that are raised and n...
International audienceThis is the year 2008 and ML-style exceptions are everywhere. Most modern lang...
We present a static analysis to automatically generate test data that raise exceptions in the input ...
ML's exception handling makes it possible to describe exceptional execution flows conveniently, but ...
Most statically typed functional programming languages allow programmers to write partial functions:...
This paper presents a program analysis to estimate un aught ex eptions in ML programs. This analysis...
In this paper we present the first exception analysis for a non-strict language. We augment a simply...
Texte intégral accessible uniquement aux membres de l'Université de LorraineBy analysing the way ML ...
AbstractExceptions are a feature often provided by programming languages to deal with computations w...
International audienceThis paper presents a program analysis to estimate uncaught exceptions in ML p...
This paper presents a program analysis to estimate uncaught exceptions in ML programs. This analysis...
AbstractWe present a static analysis that detects potential runtime exceptions that are raised and n...
We present a static analysis that detects potential runtime exceptions that are raised and never han...
We describe our experiences with an exception analysis tool for Standard ML. Information about excep...
We present in this paper an extension to the ML type system by which it is possible to statically es...
AbstractWe present a static analysis that detects potential runtime exceptions that are raised and n...
International audienceThis is the year 2008 and ML-style exceptions are everywhere. Most modern lang...
We present a static analysis to automatically generate test data that raise exceptions in the input ...
ML's exception handling makes it possible to describe exceptional execution flows conveniently, but ...
Most statically typed functional programming languages allow programmers to write partial functions:...
This paper presents a program analysis to estimate un aught ex eptions in ML programs. This analysis...
In this paper we present the first exception analysis for a non-strict language. We augment a simply...
Texte intégral accessible uniquement aux membres de l'Université de LorraineBy analysing the way ML ...
AbstractExceptions are a feature often provided by programming languages to deal with computations w...