Model checking for distributed application validation

Abstract

A model checking system is described herein that more effectively verifies and validates the design of distributed applications by providing a model and a generic framework to check application invariant properties, detect anomaly behaviors, and monitor application health. The model checking system checks on-line application behavior against application models derived from formal descriptions of the application. The system formulates the concrete application as an abstract model and a number of rules or properties that are expected to hold for the application under all conditions. The model checker compares the actual application execution with the models and either confirms that the properties hold true or reports that the properties are violated. Thus, the model checking system provides more efficient and thorough validation of distributed applications under more realistic production conditions.

Description

technical field [0001] The invention relates to the field of computer applications, in particular to distributed applications. Background technique [0002] The complexity of distributed systems and their testing mechanisms have been extensively explored for many years. There are many challenges inherent in distributed systems, such as latency of asynchronous communication, error recovery, clock drift, and service partitioning, leading to numerous problems including deadlocks, race conditions, and many other difficulties. Testing such complex systems presents enormous challenges. Over the years, many automated test generation, deployment, and execution methods have been investigated and implemented. However, considerable effort is still required in the field of automated system validation and verification. [0003] Due to the complexity of event sequence control and the proliferation of test scenarios as the system scale increases, the vast majority of testing methods are...

AI Technical Summary

Problems solved by technology

Limited automated monitoring checks for certain factors such as availability, service switching, and monitoring errors, but individuals only check a host of other metrics if something goes wrong; otherwise, the information is simply logged and ignored

In addition, certain abnormal behaviors may not manifest themselves as or cause obvious application errors, or may not be permanently stored in a manner required by automatic monitoring

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