{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T08:10:12Z","timestamp":1770883812840,"version":"3.50.1"},"reference-count":77,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T00:00:00Z","timestamp":1770854400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Comput. Sci."],"abstract":"<jats:p>\n                    How can algorithms continue to function when confronted with faults, noise, and malicious behavior? This question lies at the heart of resilient computation, a challenge addressed by multiple traditions but rarely examined through a unified lens. In this article, we introduce the concept of\n                    <jats:italic>algorithmic self-repair<\/jats:italic>\n                    as a framework for understanding how algorithms detect, mitigate, and recover from failures. We compare five major classes of algorithmic self-repair: (1) self-stabilizing algorithms that guarantee convergence from arbitrary states; (2) self-healing graph algorithms that preserve connectivity under dynamic failures; (3) error-resilient online algorithms that sustain competitiveness despite uncertain or corrupted inputs; (4) redundancy-based and probabilistic repair techniques that achieve robustness through replication or stochastic correction; and (5) Byzantine fault-tolerant algorithms that maintain correctness even in the presence of adversarial participants. By consolidating these approaches into a shared taxonomy, we highlight their guiding principles, strengths, and trade-offs. The result is not merely a survey but a structured foundation and roadmap for advancing resilient computation, positioning algorithmic self-repair as a frontier where fault tolerance becomes a defining design principle of algorithms.\n                  <\/jats:p>","DOI":"10.3389\/fcomp.2026.1717711","type":"journal-article","created":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T07:26:59Z","timestamp":1770881219000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Algorithmic self-repair: frontiers in fault-tolerant computation"],"prefix":"10.3389","volume":"8","author":[{"given":"Christine","family":"Markarian","sequence":"first","affiliation":[{"name":"College of Engineering and Information Technology, University of Dubai","place":["Dubai, United Arab Emirates"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alavikunhu","family":"Panthakkan","sequence":"additional","affiliation":[{"name":"College of Engineering and Information Technology, University of Dubai","place":["Dubai, United Arab Emirates"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,2,12]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"4025","DOI":"10.1002\/ese3.1264","article-title":"Optimal scheduling of DG and EV parking lots simultaneously with demand response based on self-adjusted pso and k-means clustering","volume":"10","author":"Abo-Elyousr","year":"2022","journal-title":"Energy Sci. 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