research-article

SEALS: a framework for building self-adaptive virtual machines

Authors:

Gwendal Jouneaux,

Olivier Barais,

Benoit Combemale,

Gunter MussbacherAuthors Info & Claims

SLE 2021: Proceedings of the 14th ACM SIGPLAN International Conference on Software Language Engineering

Pages 150 - 163

https://doi.org/10.1145/3486608.3486912

Published: 22 November 2021 Publication History

Abstract

Over recent years, self-adaptation has become a major concern for software systems that evolve in changing environments. While expert developers may choose a manual implementation when self-adaptation is the primary concern, self-adaptation should be abstracted for non-expert developers or when it is a secondary concern. We present SEALS, a framework for building self-adaptive virtual machines for domain-specific languages. This framework provides first-class entities for the language engineer to promote domain-specific feedback loops in the definition of the DSL operational semantics. In particular, the framework supports the definition of (i) the abstract syntax and the semantics of the language as well as the correctness envelope defining the acceptable semantics for a domain concept, (ii) the feedback loop and associated trade-off reasoning, and (iii) the adaptations and the predictive model of their impact on the trade-off. We use this framework to build three languages with self-adaptive virtual machines and discuss the relevance of the abstractions, effectiveness of correctness envelopes, and compare their code size and performance results to their manually implemented counterparts. We show that the framework provides suitable abstractions for the implementation of self-adaptive operational semantics while introducing little performance overhead compared to a manual implementation.

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Cited By

Topfer MAbdullah MKrulis MBures THnetynka P(2022)ML-DEECo: a Machine-Learning-Enabled Framework for Self-organizing Components2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)10.1109/ACSOSC56246.2022.00033(66-69)Online publication date: Sep-2022
https://doi.org/10.1109/ACSOSC56246.2022.00033

Index Terms

SEALS: a framework for building self-adaptive virtual machines
1. Software and its engineering
  1. Software notations and tools
    1. Development frameworks and environments
      1. Object oriented frameworks
  2. Software organization and properties
    1. Software system structures
      1. Abstraction, modeling and modularity

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cover image ACM Conferences

SLE 2021: Proceedings of the 14th ACM SIGPLAN International Conference on Software Language Engineering

October 2021

176 pages

ISBN:9781450391115

DOI:10.1145/3486608

General Chair:
Eelco Visser
Delft University of Technology, Netherlands
,
Program Chairs:
Dimitris Kolovos
University of York, UK
,
Emma Söderberg
Lund University, Sweden

Copyright © 2021 ACM.

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Published: 22 November 2021

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Cited By

Topfer MAbdullah MKrulis MBures THnetynka P(2022)ML-DEECo: a Machine-Learning-Enabled Framework for Self-organizing Components2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)10.1109/ACSOSC56246.2022.00033(66-69)Online publication date: Sep-2022
https://doi.org/10.1109/ACSOSC56246.2022.00033

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