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Context: Championed by IBM's vision of autonomic computing paper in 2003, theautonomic computing research field has seen increased research activity overthe last 20 years. Several conferences and workshops have been established andhave contributed to the autonomic computing knowledge base in search of a newkind of system -- a self-adaptive system (SAS). These systems are characterizedby being context-aware and can act on that awareness. The actions carried outcould be on the system or on the context (or environment). The underlying goalof a SAS is the sustained achievement of its goals despite changes in itsenvironment.  Objective: Despite a number of literature reviews on specific aspects of SASsranging from their requirements to quality attributes, we lack a systematicunderstanding of the current state of the art.  Method: This paper contributes a systematic literature review intoself-adaptive systems using the dblp computer science bibliography as adatabase. We filtered the records systematically in successive steps to arriveat 293 relevant papers. Each paper was critically analyzed and categorized intoan attribute matrix. This matrix consisted of five categories, with eachcategory having multiple attributes. The attributes of each paper, along withthe summary of its contents formed the basis of the literature review thatspanned 30 years.  Results: We characterize the maturation process of the research area fromtheoretical papers over practical implementations to more holistic and genericapproaches, frameworks, and exemplars, applied to areas such as networking, webservices, and robotics, with much of the recent work focusing on IoT and IaaS.  Conclusion: While there is an ebb and flow of application domains, domainslike bio-inspired approaches, security, and cyber physical systems showedpromise to grow heading into the 2020s.

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains