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Guido van Rossum, the celebrity programmer responsible for the Python programming language, published a horribly misinformed blog post last week that was meant to explain why tail calls are "unpythonic" and do not deserve a place in the Python language. Given the simplicity of the subject matter and the widespread availability of accurate information from experts like Will Clinger , it seems remarkable that anyone would still be confused about tail calls. Although the presence or absence of tail calls in Python is unimportant, this is still serious because Python is the new BASIC and, consequently, Guido is abusing his celebrity status by misguiding a huge number of young programmers. Indeed, this is very visible on the ensuing Reddit discussions where the majority of comments are factually incorrect. Definitions A tail call is a call that appears as the last thing a function does before it returns. In functional languages, this means the caller is returning the result of ...

Tail call elimination is an essential feature for functional programming languages. This feature simply refers to the ability for one function to end with a function call without leaking stack space. Tail call elimination can be essential in heavily functional code such as parser combinators and libraries written in continuation passing style. Lack of tail calls on the defacto-standard JVM has raised concerns around languages like Scala and Clojure. Fortunately, work is underway to address this issue by implementing tail call elimination on MLVM/OpenJDK. Microsoft's .NET has had tail call elimination for eight years and the Mono project is designed to replicate the Common Language Infrastructure (CLI) that is responsible for this feature. The Mono team have been advertising tail call elimination on their VM for many years. However, when we tested the elimination of tail calls on several VMs we discovered that tail calls are seriously broken on Mono but work on other VMs including ...

Mono 2.2 was recently shipped and a new JIT code generator was the main selling point promoted by the Mono project because it provides the first significant performance improvement Mono has seen for many years. We used the F# version of the SciMark2 benchmark to benchmark this new version of Mono against Mono 2.0 and some competing VMs using their native SciMark2 implementations: The composite results show that the new code generator in Mono is indeed substantially better at producing code that is 40% faster on average than the previous code generator from Mono 2.0 according to these results. However, Mono 2.2 is still a long way behind its competitors. Specifically, both LLVM and Sun's JVM are over 2.2× faster than the latest version of Mono. SciMark2 is composed of five different tests: Fast Fourier transform, successive over-relaxation, Monte Carlo, sparse matrix-vector multiply and LU matrix decomposition. We can get more detailed comparison of the VMs by looking at the indiv...