Abstract

Runtime verification is a research area that is concerned with monitoring and dynamic analysis of evolving executions with respect to precisely specified properties. The primary motivation for this field of study, at its inception over a decade ago, was to overcome the scalability limitations of exhaustive design-time formal verification. Traditionally, model checking techniques suffer from state explosion that limits the size of systems that can be verified. Moreover, model checkers operate on models and thus introduce additional proof obligations on the correctness of abstraction or model creation. On the other hand, verification based on theorem proving usually involves a significant amount of manual effort that, effectively, limits the size of the system that can be verified. By concentrating on the current execution of the actual system, runtime verification techniques allow us to have automatic analysis that is less dependent on the size of the system and, at the same time, does not require as much abstraction. Early efforts in the runtime verification community focused on characterizing properties suitable for checking at run time [2], on the generation of efficient monitors for properties specified in a variety of formal languages [7, 8] and on improving efficiency of monitoring by static analysis [3]. These efforts led to the development of mature tools, such as the MOP framework [9], within less than one decade of runtime verification research. A somewhat separate line of research was concerned with “specification-less” monitoring, which targets runtime checking algorithms for a set of common and well-defined problems. Typically, these algorithms are related to concurrency within the system, such as freedom from race conditions [5], atomicity [11], serializability [4], etc. The runtime verification domain has seen an increased interest over the recent years, generating enough traction for the community to form its own international conference. This

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