Robustness assessment through iterative statistical fault injection: LEON3 processor as a case study

Dataset exemplifies an approach of iterative statistical fault injection to assess the robustness of HDL models. Contents: 1. Results of exhaustive fault injection experiments (bit-flip faults) into LEON3 processor model; 2. Interactive querying interface, allowing to obtain custom samples from exhaustive results, and visualize them; 3. Python scripts simulating 3 approaches to statistical fault injection: conservative, error-driven, time-driven. Installation guide: 1. Ensure to have python ver. 2.x installed. Type in terminal (cmd console in Windows): “python --version” – if the output looks like > Python 2.x.x – python is installed. Otherwise download and install 2.x.x distribution: https://www.python.org/ Add python installation path to environment path variable. 2. Ensure to have Web-Server installed (Apache preferable). For instance, XAMPP: https://www.apachefriends.org/index.html 3. Ensure that Web-server is configured to execute CGI scripts, particularly python-scripts: In the 'httpd.conf' file (XAMMP control panel – button config in front of apache module): – search for line Options Indexes FollowSymLinks and add ExecCGI, so the resulting line looks like this: Options Indexes FollowSymLinks ExecCGI – search for #AddHandler cgi-script .cgi, uncomment (remove #), and append “.py” to this line, so the results looks like: AddHandler cgi-script .cgi .pl .asp .py 4. Unpack the contents of *.zip package into the folder on the Web Server. For instance into 'Web-server root folder'/Dataset. The Web-Server root can be configured in the ‘httpd.conf’ file in the DocumentRoot section, for instance: DocumentRoot "F:/HTWEB" <Directory "F:/HTWEB"> ... 5. In the web-browser navigate to the root directory of extracted package: http://localhost/Dataset/index.html