Lazy programs are beautiful, but they are slow because they build many thunks. Simple measurements show that most of these thunks are unnecessary: they are in fact always evaluated, or are always cheap. In this paper we describe Optimistic Evaluation --- an evaluation strategy that exploits this observation. Optimistic Evaluation complements compile-time analyses with run-time experiments: it evaluates a thunk speculatively, but has an abortion mechanism to back out if it makes a bad choice. A run-time adaption mechanism records expressions found to be unsuitable for speculative evaluation, and arranges for them to be evaluated more lazily in the future.

This paper presents a global approach to representation analysis based on program-wide data and control flow information. Boxing and unboxing coercions can be placed around any variable occurrence, not only where values are produced and consumed.

Dynamic cheap eagerness extends cheap eagerness by allowing the decision of whether to build a thunk or speculatively evaluate its body to be deferred until run time. We have implemented this optimisation in a compiler for a simple functional language and measured its effect on a few benchmarks. It turns out that a large part of the overhead of graph reduction can be eliminated, but that run-times and instruction counts are not affected in the same degree.

The tracer Hat records in a detailed trace the computation of a program written in the lazy functional language Haskell. The trace can then be viewed in various ways to support program comprehension and debugging. The trace was named the augmented redex trail. Its structure was inspired by standard graph rewriting implementations of functional languages. Here we describe a model of the trace that captures its essential properties and allows formal reasoning. The trace is a graph constructed by graph rewriting but goes beyond simple term graphs. Although the trace is a graph whose structure is independent of any rewriting strategy, we define the trace inductively, thus giving us a powerful method for proving its properties. Keywords: Tracing, debugging, augmented redex trail, Haskell. 1