Optimizations and extensions for fair join pattern matching
By: Ioannis Karras
Potential Business Impact:
Makes computer programs run much faster.
Join patterns are an underexplored approach for the programming of concurrent and distributed systems. When applied to the actor model, join patterns offer the novel capability of matching combinations of messages in the mailbox of an actor. Previous work by Philipp Haller et al. in the paper "Fair Join Pattern Matching for Actors" (ECOOP 2024) explored join patterns with conditional guards in an actor-based setting with a specification of fair and deterministic matching semantics. Nevertheless, the question of time efficiency in fair join pattern matching has remained underexplored. The stateful tree-based matching algorithm of Haller et al. performs worse than an implementation that adapts the Rete algorithm to the regular version of a join pattern matching benchmark, while outperforming on a variant with heavy conditional guards, which take longer to evaluate. Nevertheless, conforming Rete to the problem of join pattern matching requires heavy manual adaptation. In this thesis, we enhance and optimize the stateful tree-based matching algorithm of Haller et al. to achieve up to tenfold performance improvements on certain benchmarks, approaching the performance of Rete on regular benchmarks while maintaining the advantages of versatility and performance with heavy guards. We also enhance the benchmark suite, adding new features and enhancing its extensibility and user-friendliness. We extend the join pattern implementation with a less ambiguous syntax as well as dynamic pattern switching. Finally, we present a new complex model use case for join patterns, showing their applicability in a microservice web architecture.
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