The DOI matches its Crossref record, with a small difference in title or year; 157 of the 158 references it cites were found in a registry or an index.
Self-adaptive software: Landscape and research challenges
Abstract
Software systems dealing with distributed applications in changing environments normally require human supervision to continue operation in all conditions. These (re-)configuring, troubleshooting, and in general maintenance tasks lead to costly and time-consuming procedures during the operating phase. These problems are primarily due to the open-loop structure often followed in software development. Therefore, there is a high demand for management complexity reduction, management automation, robustness, and achieving all of the desired quality requirements within a reasonable cost and time range during operation. Self-adaptive software is a response to these demands; it is a closed-loop system with a feedback loop aiming to adjust itself to changes during its operation. These changes may stem from the software system'sself(internal causes, e.g., failure) orcontext(external events, e.g., increasing requests from users). Such a system is required tomonitoritself and its context,detectsignificant changes,decidehow to react, andactto execute such decisions. These processes depend on adaptation properties (called self-* properties), domain characteristics (context information or models), and preferences of stakeholders. Noting these requirements, it is widely believed that new models and frameworks are needed to design self-adaptive software. This survey article presents a taxonomy, based on concerns of adaptation, that is,how,what,whenandwhere, towards providing a unified view of…
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Sen, S., Alesio, S. D., Marijan, D., & Sarkar, A. (2015) · Euromicro Conference on Software Engineering and Advanced Applications (SEAA) · doi:10.1109/seaa.2015.72 · Cited by 9
Cariou, E., Barbier, F., & Goaër, O. L. (2012) · doi:10.1145/2422518.2422528 · Cited by 9
Robust-and-evolvable resilient software systems: open problems and lessons learned
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Towards a Taxonomy for the Evaluation of Self-* Software
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Toward a Real-Time Reconfiguration of Self-Adaptive Smart Assembly Systems
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Metadata
- Authors
- Salehie, M., & Tahvildari, L.
- Affiliations
- University of Waterloo (CA)
- Venue
- ACM Transactions on Autonomous and Adaptive Systems
- Published
- 2009-05
- Volume
- 4
- Issue
- 2
- Pages
- 1-42
- ISSN
- 1556-4665 (ISSN-L)
- 1556-4703
- OpenAlex
- W1964137226
- Cited by
- 1,266
- References
- 158
- Citations by year
- 2026: 25 · 2025: 45 · 2024: 35 · 2023: 34 · 2022: 50 · 2021: 42 · 2020: 69 · 2019: 70 · 2018: 91 · 2017: 109 · 2016: 99 · 2015: 102 · 2014: 119 · 2013: 105 · 2012: 110
- FWCI
- 96.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Autonomous and Adaptive Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Software › Advanced Software Engineering Methodologies
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed systems and fault tolerance
- Keywords
- self-adaptive software, self-* properties, distributed applications, context-aware systems, self-monitoring, self-configuration, self-healing, self-optimization, self-protection, research landscape, research gaps
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
