We define a practical algorithm for distrubuted rational tree unification and prove its correctness in both the off-line and on-line cases. We derive the distributed algorithm from a centralized one, showing clearly the trade-offs between local and distributed execution. The algorithm is used to realize logic variables in the Mozart Programming System, which implements the Oz language (see http://www/mozart-oz.org). Oz appears to the programmer as a concurrent object-oriented language with dataflow synchronization. Logic variables implement the dataflow behavior. We show that lohgic variables can easily be added to the more restricted models of Java and ML, thus providing an alternative way to do concurent programming in these languages. We present common distributed programming idioms in a network-transparent way using logic variables. We show that in common cases the algorithm maintains the same message latency as explicit message passing. In addition, it is able to handle uncommon cases that arise from the properties of latency tolerance and third-party independence. This is evidence that using logic variables in distributed computing is beneficial at both the system and language levels. At the system level, they improve latency tolerance and third-party independence. At the language level, they help make network-transparent distribution practical.

Some of the most difficult questions to answer when designing a distributed application are related to mobility: what information to transfer between sites and when and how to transfer it. Network-transparent distribution, the property that a program's behavior is independent of how it is partitioned among sites, does not directly address these questions. Therefore we propose to extend all language entities with a network behavior that enables efficient distributed programming by giving the programmer a simple and predictable control over network communication patterns. In particular, we show how to give objects an arbitrary mobility behavior that is independent of the objects definition. In this way, the syntax and semantics of objects are the same regardless of whether they are used as stationary servers, mobile agents, or simply as caches. These ideas have been implemented in Distributed Oz, a concurrent object-oriented language that is state aware and has dataflow synchronization. We prove that the implementation of objects in Distributed Oz is network transparent. To satisfy the predictability condition, the implementation avoids forwarding chains through intermediate sites. The implementation is an extension to the publicly available DFKI Oz 2.0 system.