A Semantics Comparison Workbench for a Concurrent, Asynchronous, Distributed Programming Language

TL;DR

This paper introduces a semantics comparison workbench for SCOOP, enabling analysis and comparison of different execution models to ensure consistency and correctness in concurrent, asynchronous, and distributed programming.

Contribution

It presents a modular, graph transformation-based tool for analyzing and comparing semantics of SCOOP, supporting extensions and detecting discrepancies like deadlocks.

Findings

Identified deadlock-related discrepancies between SCOOP execution models

Demonstrated the workbench's ability to verify property consistency across semantics

Extended the formalisation to support distributed programming extensions

Abstract

A number of high-level languages and libraries have been proposed that offer novel and simple to use abstractions for concurrent, asynchronous, and distributed programming. The execution models that realise them, however, often change over time---whether to improve performance, or to extend them to new language features---potentially affecting behavioural and safety properties of existing programs. This is exemplified by SCOOP, a message-passing approach to concurrent object-oriented programming that has seen multiple changes proposed and implemented, with demonstrable consequences for an idiomatic usage of its core abstraction. We propose a semantics comparison workbench for SCOOP with fully and semi-automatic tools for analysing and comparing the state spaces of programs with respect to different execution models or semantics. We demonstrate its use in checking the consistency of properties across semantics by applying it to a set of representative programs, and highlighting a deadlock-related discrepancy between the principal execution models of SCOOP. Furthermore, we demonstrate the extensibility of the workbench by generalising the formalisation of an execution model to support recently proposed extensions for distributed programming. Our workbench is based on a modular and parameterisable graph transformation semantics implemented in the GROOVE tool. We discuss how graph transformations are leveraged to atomically model intricate language abstractions, how the visual yet algebraic nature of the model can be used to ascertain soundness, and highlight how the approach could be applied to similar languages.