🚀 In this hands-on coding experiment, we use GitHub Copilot 🤖 inside VS Code to enhance a TCL log-parsing script for real engineering workflows!
Starting from a basic TCL script that scans an error.log file for warnings, we prompt Copilot to intelligently modify the program to also detect and print critical tool messages like:
✅ samopen
✅ bam_header_read
✅ warning messages
✅ tool Message outputs
Using AI-assisted development, we extend the script by adding multiple parsing blocks.
This demonstrates how engineers can rapidly build EDA log analyzers using simple prompts and AI coding assistance.
💡 What This Experiment Shows
🔹 TCL scripting for automation
🔹 Parsing large tool log files efficiently
🔹 Using regexp -nocase for flexible pattern matching
🔹 File read/write operations in TCL
🔹 AI prompt engineering with GitHub Copilot
🔹 Practical debugging workflow used in semiconductor design environments
📌 What You’ll Learn
✅ TCL file handling (open, gets, close)
✅ Regular expressions in TCL
✅ Case-insensitive log parsing
✅ Writing filtered outputs to files
✅ AI-assisted script enhancement using Copilot
✅ Semiconductor workflow automation concepts
👨💻 Useful For
⚡ VLSI Engineers
📐 Physical Design & Verification Engineers
🧪 EDA Tool Users
🔧 CAD & Automation Engineers
🎓 Students learning TCL for chip design flows
Log parsing is a critical skill in RTL-to-GDSII flows, simulation debugging, and backend automation — and AI tools now make development significantly faster 🚀.
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Credits:
Image by Gerd Altmann from Pixabay
Music by YouTube Music
Image by pngegg.com, pngaaa.com
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