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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Lecture Notes in Computer Science 1205
(1999) · Industrial Robot: An International Journal · doi:10.1108/ir.1999.04926fae.001 · Cited by 38,662
(1994) · Cited by 21,711
The vision of autonomic computing
Kephart, J. O., & Chess, D. M. (2003) · Computer · doi:10.1109/mc.2003.1160055 · Cited by 6,572
Decisions with Multiple Objectives
Keeney, R. L., & Raiffa, H. (1993) · Cambridge University Press eBooks · doi:10.1017/cbo9781139174084 · Cited by 4,570
Supervisory Control of a Class of Discrete Event Processes
Ramadge, P. J., & Wonham, W. M. (1987) · SIAM Journal on Control and Optimization · doi:10.1137/0325013 · Cited by 3,346
Proceedings of the International Joint Conference on Artificial Intelligence 2007
Bundy, A. (2007) · International Joint Conference on Artificial Intelligence · Cited by 2,761
Artificial Intelligence: A Modern Approach
Ligęza, A. (1995) · Neurocomputing · doi:10.1016/0925-2312(95)90020-9 · Cited by 1,868
Artificial Intelligence: A Modern Approach
Russell, S., & Norvig, P. (1995) · Cited by 1,753
Castro, B. F. (1997) · Computación y Sistemas · Cited by 1,504
Design and evaluation of a wide-area event notification service
Carzaniga, A., Rosenblum, D. S., & Wolf, A. L. (2001) · ACM Transactions on Computer Systems · doi:10.1145/380749.380767 · Cited by 1,425
Research works printed but not linked: 15
- 10.5555/1756301.1756316 · doi:10.5555/1756301.1756316
- Buschmann F. Meunier R. Rohnert H. Sommerlad P. and Stal M. 1996. A System of Patterns—Pattern Oriented Software Architecture. Wiley. Buschmann F. Meunier R. Rohnert H. Sommerlad P. and Stal M. 1996. A System of Patterns—Pattern Oriented Software Architecture. Wiley.
- Ibm ref. arch . 2005 . An architectural blueprint for autonomic computing. IBM white paper. http://www-03.ibm.com/autonomic/pdfs/ACBlueprintWhitePaperV7.pdf. Ibm ref. arch. 2005. An architectural blueprint for autonomic computing. IBM white paper. http://www-03.ibm.com/autonomic/pdfs/ACBlueprintWhitePaperV7.pdf.
- Ieee-iso/iec 14764. 2006. Standard for software maintenance - IEEE 14764-2006 - ISO/IEC 14764. URL = http://ieeexplore.ieee.org/iel5/11168/35960/01703974.pdf. Ieee-iso/iec 14764. 2006. Standard for software maintenance - IEEE 14764-2006 - ISO/IEC 14764. URL = http://ieeexplore.ieee.org/iel5/11168/35960/01703974.pdf.
- Iso /Iec 9126-1. 2001. ISO/IEC 9126-1 Standard : Software Eng. -Product quality - Part 1: Quality model , International Standard Organization , 2001 . Iso/Iec 9126-1. 2001. ISO/IEC 9126-1 Standard: Software Eng. -Product quality - Part 1: Quality model, International Standard Organization, 2001.
- 10.5555/375094.375105 · doi:10.5555/375094.375105
- Laddaga , R. , Robertson , P. , and Shrobe , H. E . 2001 . Results of the 2nd International workshop on self-adaptive software. In Proceedings of the International Workshop on Self-Adaptive Software. 281--290 . Laddaga, R., Robertson, P., and Shrobe, H. E. 2001. Results of the 2nd International workshop on self-adaptive software. In Proceedings of the International Workshop on Self-Adaptive Software. 281--290.
- 10.5555/646195.681473 · doi:10.5555/646195.681473
- Murch , R. 2004. Autonomic Computing . Prentice Hall . Murch, R. 2004. Autonomic Computing. Prentice Hall.
- 10.5555/2167575.2167592 · doi:10.5555/2167575.2167592
- 10.1145/214956.214961 · DOI
- 10.5555/977400.977958 · doi:10.5555/977400.977958
- Scott , J. , Neema , S. , Bapty , T. , and Abbott , B . 2000 . Hardware/ software runtime environment for dynamically reconfigurable systems. Tech. Rep. ISIS-2000-06, Vanderbilt Univ. Scott, J., Neema, S., Bapty, T., and Abbott, B. 2000. Hardware/software runtime environment for dynamically reconfigurable systems. Tech. Rep. ISIS-2000-06, Vanderbilt Univ.
- Serugendo , G. D. M. , Foukia , N. , Hassas , S. , Karageorgos , A. , Mostéfaoui , S. K. , Rana , O. F. , Ulieru , M. , Valckenaers , P. , and van Aart , C. 2003 . Self-organisation: Paradigms and app . In Proceedings of the Engineering Self-Organising Applications Workshop. 1--19 . Serugendo, G. D. M., Foukia, N., Hassas, S., Karageorgos, A., Mostéfaoui, S. K., Rana, O. F., Ulieru, M., Valckenaers, P., and van Aart, C. 2003. Self-organisation: Paradigms and app. In Proceedings of the Engineering Self-Organising Applications Workshop. 1--19.
- 10.5555/1018409.1018780 · doi:10.5555/1018409.1018780
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Song, H., Zhang, X., Ferry, N., Chauvel, F., Solberg, A., & Huang, G. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11653-2_17 · Cited by 6
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Almorsy, M., Ibrahim, A. S., & Grundy, J. (2013) · Springer eBooks · doi:10.1007/978-3-642-38586-5_3 · Cited by 6
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Nitto, E. D., Meiländer, D., Meiländer, D., Gorlatch, S., Metzger, A., Psaier, H., Dustdar, S., Razavian, M., Tamburri, D. A., & Lago, P. (2012) · doi:10.1109/s-cube.2012.6225500 · Cited by 6
Learning self-adaptations for IoT networks: a genetic programming approach
Li, J., Nejati, S., & Sabetzadeh, M. (2022) · International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) · doi:10.1145/3524844.3528053 · Cited by 6
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Taming software adaptability with architecture-centric framework
Ding, B., Wang, H., Shi, D., & Cao, J. (2010) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2010.5466983 · Cited by 6
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Alloui, I., Esale, D., & Vernier, F. (2015) · International Conference on Software Engineering and Applications (ICSOFT-EA) · doi:10.5220/0005560104680471 · Cited by 6
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Omoronyia, I. (2016) · International Journal of Secure Software Engineering · doi:10.4018/ijsse.2016040102 · Cited by 6
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Farahani, A., Nazemi, E., Cabri, G., & Alireza, R. (2016) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2016.7844665 · Cited by 6
Temdee, P., & Prasad, R. (2017) · Springer series in wireless technology · doi:10.1007/978-3-319-59035-6_2 · Cited by 6
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Magableh, B. (2011) · doi:10.21427/cp4j-bp26 · Cited by 6
Mahin, M. S. R., Islam, M. J., Khatun, A., & Debnath, B. C. (2018) · doi:10.1109/ciet.2018.8660777 · Cited by 6
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Psaier, H., Juszczyk, Ł., Skopik, F., Schall, D., & Dustdar, S. (2011) · Springer eBooks · doi:10.1007/978-3-7091-0813-0_6 · Cited by 6
Christi, A., Groce, A., & Wellman, A. (2019) · IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) · doi:10.1109/issrew.2019.00046 · Cited by 6
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Weyns, D., & Oquendo, F. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.03475 · Cited by 6
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Xu, M., Liu, R. W., Stoodley, M., & Tahvildari, L. (2025) · IEEE International Conference on Software Engineering Education and Training (CSEE&T) · doi:10.1109/cseet66350.2025.00011 · Cited by 5
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Capodieci, N., Hart, E., & Cabri, G. (2013) · European Conference on Artificial Life · doi:10.1162/978-0-262-31709-2-ch127 · Cited by 5
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Hussein, M., Nouacer, R., & Radermacher, A. (2016) · Euromicro Conference on Digital System Design (DSD) · doi:10.1109/dsd.2016.21 · Cited by 5
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Gutsche, C., Prokopets, V., Wang, Z., Götz, S., & Aßmann, U. (2024) · Euromicro Conference on Software Engineering and Advanced Applications (SEAA) · doi:10.1109/seaa64295.2024.00011 · Cited by 5
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Dobrican, R.-A., & Zampuniéris, D. (2014) · Open Repository and Bibliography (University of Luxembourg) · Cited by 5
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Preisler, T., Dethlefs, T., & Renz, W. (2015) · IEEE International Conference on Autonomic Computing (ICAC) · doi:10.1109/icac.2015.56 · Cited by 5
Self-adaptation by coordination-targeted reconfigurations
Oliveira, N., & Barbosa, L. S. (2015) · Journal of Software Engineering Research and Development · doi:10.1186/s40411-015-0021-2 · Cited by 5
PRESC $$^{2}$$ 2 : efficient self-reconfiguration of cache strategies for elastic caching platforms
Qin, X., Wang, W., Zhang, W., Wei, J., Zhao, X., Zhong, H., & Huang, T. (2013) · Computing · doi:10.1007/s00607-013-0365-6 · Cited by 5
Portillo‐Dominguez, A. O., Wang, M., Murphy, J., Magoni, D., Mitchell, N., Sweeney, P. F., & Altman, E. (2014) · doi:10.1145/2631890.2631895 · Cited by 5
Energy-based adaptation in simulations of survivability of ad hoc communication
Raciti, M., Cucurull, J., & Nadjm‐Tehrani, S. (2011) · IFIP Wireless Days · doi:10.1109/wd.2011.6098216 · Cited by 5
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Preisler, T., Dethlefs, T., & Renz, W. (2016) · IEEE International Conference on Autonomic Computing (ICAC) · doi:10.1109/icac.2016.66 · Cited by 5
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Bocanegra, J., Pavlich‐Mariscal, J. A., & Carrillo-Ramos, Á. (2016) · IEEE Colombian Computing Conference (CCC) · doi:10.1109/columbiancc.2016.7750792 · Cited by 5
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Buga, A., Nemeş, S. T., & Schewe, K. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-69904-2_10 · Cited by 5
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Ismail, A. B., & Kwiatkowska, M. (2017) · Asia-Pacific Software Engineering Conference (APSEC) · doi:10.1109/apsec.2017.50 · Cited by 5
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Linkola, S., & Hantula, O. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-77583-8_14 · Cited by 5
Integrating Semantic Run-Time Modelsfor Adaptive Software Systems
Poggi, F., Rossi, D., & Ciancarini, P. (2019) · Journal of Web Engineering · doi:10.13052/jwe1540-9589.18131 · Cited by 5
Characterizing Architectural Drifts of Adaptive Systems
Martin, D., Siqueira, B. R., de Camargo, V. V., & Ferrari, F. C. (2020) · IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) · doi:10.1109/saner48275.2020.9054856 · Cited by 5
An Organizational Structure and Self-Adaptive Mechanism for Holonic Multi-Agent Systems
Wang, M., Li, Q., & Lin, Y. (2020) · IEEE Access · doi:10.1109/access.2020.3014694 · Cited by 5
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Cardozo, N., & Dusparić, I. (2023) · Information and Software Technology · doi:10.1016/j.infsof.2023.107308 · Cited by 5
On Adapting SNMP as Communication Protocol in Distributed Control Loops for Self-adaptive Systems
Shmelkin, I., & Springer, T. (2021) · IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS) · doi:10.1109/acsos52086.2021.00022 · Cited by 5
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Song, H., Soylu, A., & Roman, D. (2022) · IEEE/ACM International Conference on Utility and Cloud Computing (UCC) · doi:10.1109/ucc56403.2022.00055 · Cited by 5
Context-Aware Systems and Adaptive User Authentication
Halunen, K., & Evesti, A. (2013) · Communications in computer and information science · doi:10.1007/978-3-319-04406-4_24 · Cited by 5
Mulcahy, J. J., Huang, S., & Mahgoub, I. (2015) · IEEE SoutheastCon · doi:10.1109/secon.2015.7132919 · Cited by 5
Requirements Planning with Event Calculus for Runtime Self-Adaptive System
Liu, W., & Li, M. (2015) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac.2015.18 · Cited by 5
A Framework for Enhancing Performance and Handling Run-Time Uncertainty in Self-Adaptive Systems
Abufouda, M. (2014) · International Journal of Software Engineering & Applications · doi:10.5121/ijsea.2014.5106 · Cited by 5
Achieving self-aware parallelism in stream programs
Su, Y., Shi, F., Talpur, S., Wang, Y., Hu, S., & Wei, J. (2014) · Cluster Computing · doi:10.1007/s10586-014-0412-x · Cited by 5
Introduction to the special section on self-adaptive systems: Models and algorithms
Bouchachia, A., & Nedjah, N. (2012) · ACM Transactions on Autonomous and Adaptive Systems · doi:10.1145/2168260.2168273 · Cited by 5
LossEstimate: Distributed failure estimation in wireless networks
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da Silva, J. P. S., Ecar, M., Pimenta, M. S., Guedes, G. T. A., & Rodrigues, E. M. (2018) · Brazilian Symposium on Software Engineering · doi:10.1145/3266237.3266244 · Cited by 5
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Aßmann, U., Grzelak, D., Mey, J., Pukhkaiev, D., Schöne, R., Werner, C., & Püschel, G. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-10801-4_1 · Cited by 5
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Lee, E., Kim, Y., Seo, Y.-D., & Baik, D.-K. (2018) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon.2018.8650165 · Cited by 5
Li, N., Bai, D., Peng, Y., Yang, Z., & Jiao, W. (2018) · IEEE International Conference on Software Quality, Reliability and Security (QRS) · doi:10.1109/qrs.2018.00020 · Cited by 5
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Mahalle, P. N., & Dhotre, P. S. (2019) · Intelligent systems reference library · doi:10.1007/978-981-32-9952-8_3 · Cited by 5
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Kalantari, S., Nazemi, E., & Masoumi, B. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115187 · Cited by 5
Synthesis of self-adaptable energy aware software for heterogeneous multicore embedded systems
Deniziak, S. R., & Ciopiński, L. (2021) · Microelectronics Reliability · doi:10.1016/j.microrel.2021.114184 · Cited by 5
Lachner, C., Mann, Z. Á., & Dustdar, S. (2021) · IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW) · doi:10.1109/icdcsw53096.2021.00009 · Cited by 5
REACT-ION: A Model-based Runtime Environment for Situation-aware Adaptations
Pfannemüller, M., Breitbach, M., Weckesser, M., Becker, C., Schmerl, B. R., Schürr, A., & Krupitzer, C. (2020) · ACM Transactions on Autonomous and Adaptive Systems · doi:10.1145/3487919 · Cited by 5
Self-adaptive containers: Building resource-efficient applications with low programmer overhead
Huang, W., & Knottenbelt, W. J. (2013) · International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) · doi:10.1109/seams.2013.6595499 · Cited by 5
Fredericks, E. M., & Cheng, B. H. C. (2015) · IEEE/ACM International Workshop on Search-Based Software Testing (SBST) · doi:10.1109/sbst.2015.9 · Cited by 5
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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.
