Runtime verification is a computing system analysis and execution approach based on extracting information from a running system and using it to detect and possibly react to observed behaviors satisfying or violating certain properties. Some very particular properties, such as datarace and deadlock freedom, are typically desired to be satisfied by all systems and may be best implemented algorithmically. Other properties can be more conveniently captured as formal specifications. Runtime verification specifications are typically expressed in trace predicate formalisms, such as finite-state machines, regular expressions, context-free patterns, linear temporal logics, etc., or extensions of these. This allows for a less ad-hoc approach than normal testing. However, any mechanism for monitoring an executing system is considered runtime verification, including verifying against test oracles and reference implementations . When formal requirements specifications are provided, monitors are synthesized from them and infused within the system by means of instrumentation. Runtime verification can be used for many purposes, such as security or safety policy monitoring, debugging, testing, verification, validation, profiling, fault protection, behavior modification (e.g., recovery), etc. Runtime verification avoids the complexity of traditional formal verification techniques, such as model checking and theorem proving, by analyzing only one or a few execution traces and by working directly with the actual system, thus scaling up relatively well and giving more confidence in the results of the analysis (because it avoids the tedious and error-prone step of formally modelling the system), at the expense of less coverage. Moreover, through its reflective capabilities runtime verification can be made an integral part of the target system, monitoring and guiding its execution during deployment.
History and context Checking formally or informally specified properties against executing systems or programs is an old topic (notable examples are dynamic typing in software, or fail-safe devices or watchdog timers in hardware), whose precise roots are hard to identify. The terminology runtime verification was formally introduced as the name of a 2001 workshop aimed at addressing problems at the boundary between formal verification and testing. For large code bases, manually writing test cases turns out to be very time consuming. In addition, not all errors can be detected during development. Early contributions to automated verification were made at the NASA Ames Research Center by Klaus Havelund and Grigore Rosu to archive high safety standards in spacecraft, rovers and avionics technology. They proposed a tool to verify specifications in temporal logic and to detect race conditions and deadlocks in Java programs by analyzing single execution paths. Currently, runtime verification techniques are often presented with various alternative names, such as runtime monitoring, runtime checking, runtime reflection, runtime analysis, dynamic analysis, runtime/dynamic symbolic analysis, trace analysis, log file analysis, etc., all referring to instances of the same high-level concept applied either to different areas or by scholars from different communities. Runtime verification is intimately related to other well-established areas, such as testing (particularly model-based testing) when used before deployment and fault-tolerant systems when used during deployment. Within the broad area of runtime verification, one can distinguish several categories, such as:
"specification-less" monitoring that targets a fixed set of mostly concurrency-related properties such as atomicity. The pioneering work in this area is by Savage et al. with the Eraser algorithm monitoring with respect to temporal logic specifications; early contributions in this direction has been made by Lee, Kannan, and their collaborators, and Havelund and Rosu,.
Basic approaches
The broad field of runtime verification methods can be classified by three dimensions:
The system can be monitored during the execution itself (online) or after the execution e.g. in form of log analysis (offline). The verifying code is integrated into the system (as done in Aspect-oriented Programming) or is provided as an external entity. The monitor can report violation or validation of the desired specification. Nevertheless, the basic process in runtime verification remains similar:
A monitor is created from some formal specification. This process usually can be done automatically if there are equivalent automata for the formulas of the formal language the property is specified in. To transform a regular expression, a finite-state machine can be used; a property in linear temporal logic can be transformed into a Büchi automaton (see also Linear temporal logic to Büchi automaton). The system is instrumented to send events concerning its execution state to the monitor. The system is executed and gets verified by the monitor. The monitor verifies the received event trace and produces a verdict whether the specification is satisfied. Additionally, the monitor sends feedback to the system to possibly correct false behaviour. When using offline monitoring the system of cause cannot receive any feedback, as the verification is done at a later point in time.
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