Software architecture-based self-adaptation in robotics

IF 3.7 2区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Journal of Systems and Software Pub Date : 2024-10-18 DOI:10.1016/j.jss.2024.112258

Elvin Alberts , Ilias Gerostathopoulos , Ivano Malavolta , Carlos Hernández Corbato , Patricia Lago

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引用次数: 0

Abstract

Context:

Robotics software architecture-based self-adaptive systems (RSASSs) are robotics systems made robust to runtime uncertainty by adapting their software architectures. The research landscape of RSASS approaches is multidisciplinary and fragmented, with many aspects still unexplored or ineffectively shared among communities involved.

Objective:

We aim at identifying, classifying, and analyzing the state of the art of existing approaches for RSASSs from the following perspectives: (i) the key characteristics of approaches and (ii) the evaluation strategies applied by researchers.

Method:

We apply the systematic mapping research method. We selected

37

primary studies via automatic, manual, and snowballing-based search and selection procedures. We rigorously defined and applied a classification framework composed of 32 parameters and synthesize the obtained data to produce a comprehensive overview of the state of the art.

Results:

This work contributes (i) a rigorously defined classification framework for studies on RSASSs, (ii) a systematic map of the research efforts on RSASSs, (iii) a discussion of emerging findings and implications for future research, and (iv) a publicly available replication package.

Conclusion:

This study provides a solid evidence-based overview of the state of the art in RSASS approaches. Its results can benefit RSASS researchers at different levels of seniority and involvement in RSASS research.

Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

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机器人技术中基于软件架构的自适应

背景：基于机器人软件架构的自适应系统（RSASS）是指通过调整软件架构使机器人系统能够应对运行时的不确定性。RSASS方法的研究领域涉及多个学科，且各自为政，许多方面仍未得到探索，或相关群体之间未能有效共享。目标：我们旨在从以下角度对现有RSASS方法的技术现状进行识别、分类和分析：(i) 方法的关键特征；(ii) 研究人员采用的评估策略。方法：我们采用了系统映射研究方法。我们通过自动、手动和 "滚雪球 "式搜索和筛选程序，选出了 37 项主要研究。我们严格定义并应用了一个由 32 个参数组成的分类框架，并对所获得的数据进行了综合，从而得出了一份关于研究现状的全面概述。结果：这项工作的贡献包括：(i) 一个严格定义的 RSASS 研究分类框架；(ii) 一份关于 RSASS 研究工作的系统地图；(iii) 关于新发现和对未来研究的影响的讨论；以及 (iv) 一个公开可用的复制包。编者注：开放科学材料由《系统与软件期刊》开放科学委员会审定。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Systems and Software 工程技术-计算机：理论方法

CiteScore

8.60

自引率

5.70%

发文量

193

审稿时长

16 weeks

期刊介绍： The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to: • Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution • Agile, model-driven, service-oriented, open source and global software development • Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems • Human factors and management concerns of software development • Data management and big data issues of software systems • Metrics and evaluation, data mining of software development resources • Business and economic aspects of software development processes The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.