Apply new optimal set of settings after tuning

WebFuzzing / EvoMaster

The first open-source AI-driven tool for automatically generating system-level test cases (also known as fuzzing) for web/enterprise applications. Currently targeting whitebox and blackbox testing of Web APIs, like REST, GraphQL and RPC (e.g., gRPC and Thrift).

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Apply new optimal set of settings after tuning #955

Closed amidgol closed 3 months ago

amidgol commented 5 months ago

This change is based on the results of the tuning paper. We found a new set of configs to be optimal, detecting a higher number of faults while keeping a competitive degree of line and branch coverage. This setting is referred to as "best faults" in the paper.

arcuri82 commented 5 months ago

@amidgol some E2E tests fail after the change of parameters. This shouldn't really happen (but might be issue with the E2E). Few seem related to AdaptiveHypermutation, so you might need to have a chat or help from @man-zhang for looking into it