The treatment of state in optimistic systems

Abstract

Optimistic computation methods typically save copies of objects' state information, so that they can recover from erroneous “over-optimistic” computations. Such state saving is generally time and space consuming, and can be rather complicated both to implement and to use. I show how the data structure community's theory of persistence can be used not only to analyse and explain the treatment of state in optimistic systems, but also as a simple yet general mechanism for performing the necessary state saving with minimal impact on application code. Preliminary results based on a benchmark application and an existing optimistic simulator are presented, showing that providing support for fully general object states is a realistic and practical option. In addition, I show how some existing state saving techniques—including support for shared state—can be derived, and discuss a number of ways in which the model might be extended.