Synergizing Domain Expertise with Self-Awareness in Software Systems: A Patternized Architecture Guideline
Not on the map. Why?
Abstract (arXiv)
To promote engineering self-aware and self-adaptive software systems in a reusable manner, architectural patterns and the related methodology provide an unified solution to handle the recurring problems in the engineering process. However, in existing patterns and methods, domain knowledge and engineers' expertise that is built over time are not explicitly linked to the self-aware processes. This linkage is important, as the knowledge is a valuable asset for the related problems and its absence would cause unnecessary overhead, possibly misleading results and unwise waste of the tremendous benefit that could have been brought by the domain expertise. This paper highlights the importance of synergizing domain expertise and the self-awareness to enable better self-adaptation in software systems, relying on well-defined expertise representation, algorithms and techniques. In particular, we present a holistic framework of notions, enriched patterns and methodology, dubbed DBASES, that offers a principled guideline for the engineers to perform difficulty and benefit analysis on possible synergies, in an attempt to keep "engineers-in-the-loop". Through three tutorial case studies, we demonstrate how DBASES can be applied in different domains, within which a carefully selected set of candidates with different synergies can be used for quantitative investigation, providing more informed decisions of the design choices.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Jan 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 2; 2022: 5; 2023: 0; 2024: 1; 2025: 1.
9 papers.
- 2021Multi-Objectivizing Software Configuration Tuning (for a single performance concern)cited by 28
- 2021MMO: Meta Multi-Objectivization for Software Configuration Tuningcited by 20
- 2022The Weights can be Harmful: Pareto Search versus Weighted Search in Multi-Objective Search-Based Software Engineeringcited by 17
- 2022Lifelong Dynamic Optimization for Self-Adaptive Systems: Fact or Fiction?cited by 16
- 2022Planning Landscape Analysis for Self-Adaptive Systemscited by 12
- 2025Distilled Lifelong Self-Adaptation for Configurable Systemscited by 12
- 2022Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding Schemescited by 10
- 2024Deep Configuration Performance Learning: A Systematic Survey and Taxonomycited by 8
- 2022The Vision of Self-Evolving Computing Systemscited by 4
- 2025Distilled Lifelong Self-Adaptation for Configurable Systems1 Jan 2025
- 2024Deep Configuration Performance Learning: A Systematic Survey and Taxonomy5 Mar 2024
- 2022The Vision of Self-Evolving Computing Systems14 Apr 2022
- 2022Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding Schemes30 Mar 2022
- 2022Planning Landscape Analysis for Self-Adaptive Systems23 Mar 2022
- 2022The Weights can be Harmful: Pareto Search versus Weighted Search in Multi-Objective Search-Based Software Engineering8 Feb 2022
- 2022Lifelong Dynamic Optimization for Self-Adaptive Systems: Fact or Fiction?18 Jan 2022
- 2021MMO: Meta Multi-Objectivization for Software Configuration Tuning14 Dec 2021
- 2021Multi-Objectivizing Software Configuration Tuning (for a single performance concern)31 May 2021