DirectFuzz: Automated Test Generation for RTL Designs using Directed Graybox Fuzzing - Canakci, Sadullah; Delshadtehrani, Leila; Eris, Furkan; Taylor, Michael Bedford; Egele, Manuel; Joshi, Ajay (2021 58th ACM/IEEE Design Automation Conference (DAC), 2021)
A critical challenge in RTL verification is to generate effective test inputs. Recently, RFUZZ proposed to use an automated software testing technique, namely Graybox Fuzzing, to effectively generate test inputs to maximize the coverage of the whole hardware design. For a scenario where a tiny fraction of a large hardware design needs to be tested, the RFUZZ approach is extremely time consuming. In this work, we present DirectFuzz, a directed test generation mechanism. DirectFuzz uses Directed Graybox Fuzzing to generate test inputs targeted towards a module instance, which enables targeted testing. Our experimental results show that DirectFuzz covers the target sites up to 17.5 × faster (2.23 × on average) than RFUZZ on a variety of RTL designs.