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Introducing Linting Into the Chip Design Flow
A Methodological Pillar for Quality-Driven RTL Development
In today’s increasingly complex ASIC and FPGA designs, quality cannot be postponed to simulation. Design issues that are introduced during RTL design phases compound downstream—bloating verification cycles, consuming costly engineering time, and risking expensive silicon re-spins.
Linting is not an optional cleanup step anymore, it has to be an early design methodology that sits at the heart of a quality-focused RTL workflow. It’s not just about “style”: intelligent, well-configured linting ensures good design practices and early identifies architectural flaws, logic mismatches, and synthesis issues even before simulation begins.
At Sigasi, we provide you with the tools to introduce linting at the point of code creation with context-aware checks that scale from building blocks to complete complex designs. To facilitate engineering teams structure their thinking, we have positioned our (early) linting methodology around several core categories, each directly tied to one specific type of design quality or downstream value.
🔁 1. Finite State Machine Integrity Checks
Avoid hidden hazards in FSMs before they reach synthesis.
State machines are a core control element in most digital designs, but they are also fragile. Small omissions or poor structuring can easily introduce unreachable states or incomplete transitions but Sigasi Visual HDL catches them first.
🔍 Typical issues detected:
- Missing, unused, or unreachable states
- Incomplete state transitions
- Missing
othersor default clauses
💡 Linting with Sigasi:
- Reduced simulation debugging
- Safer synthesis
- More robust behavior under corner-case stimuli.
⚙️ 2. RTL Semantics & Synthesis Readiness
Align early design with synthesis.
This category focuses on making sure the RTL is not just logically sound but also synthesizable, deterministic, and robust. If left unchecked, even well-structured code can yield incomplete sensitivity lists, vector size mismatches, or missing resets for registers.
🔍 Typical issues detected:
- Incomplete reset branch
- Clock signal not used as clock
- Inconsistent reset style
- Inconsistent clock edge usage
- Incorrect array size in assignment
- Index out of range
- Incomplete sensitivity list
💡 Linting with Sigasi helps with:
- Logic equivalence
- Synthesized netlists
- Avoiding possible hardware issues
📐 3. Design Style & Maintainability Checks
Promote consistency across teams and future-proof your codebase. Code quality is not just about correctness—it’s about readability, collaboration, and long-term maintainability. This category includes checks that promote naming conventions, maintainability, and readability—especially valuable for distributed teams or long-lifecycle projects.
🔍 Common checks:
- Naming conventions
- Proper order of port and generic/parameter associations
- Duplication of logic or unused declarations
- Maximum line length check
- Magic number check
💡 Linting with Sigasi provides:
- Better quality
- Faster code reviews
- Easier code and naming compliance
- Shorter onboarding times
🧱 4. Configurable Scope of Rule Checks
Control the scope of each rule.
Each rule has a scope where its check is activated. Sigasi Visual HDL’s linter provides three levels of granularity. The levels are “project”, “folder”, and “file”, going from top to bottom. This provides the user with flexibility when defining different rules with different severity levels for specific projects, folders, and files.
💡 Linting with Sigasi ensures:
- Precise rule application
- Optimized project adaptation
⚡ 5. Live Coding Feedback for Rapid Iteration
Shift-left moves quality right into the developer’s editor. Traditional linting happens ex post facto, after the code is written. Sigasi offers on-the-fly linting: live, intelligent and interactive feedback as the engineer types. This creates a continuous virtuous cycle: developers catch mistakes early, learn best practices while coding, and write better RTL from the start.
💡 Linting with Sigasi:
- Shorter debug cycles
- Higher first-pass correctness
- A built-in training loop for engineers
📈 Conclusion: Sigasi Linting is a Strategic Enabler
Adopting Sigasi as a comprehensive (early) linting methodology isn’t merely about defect prevention; it’s a strategic shift-left towards a more efficient, predictable, and high-quality RTL development process. In a world of shrinking tapeout windows and rising complexity, you can’t afford to push quality downstream. By embedding intelligent, real-time feedback and addressing design issues across multiple categories —from state machine integrity to coding style— teams can significantly reduce verification cycles, improve collaboration, and achieve silicon success with greater confidence. Linting with Sigasi Visual HDL, therefore, emerges as an indispensable enabler for modern chip design, ensuring quality is designed in, not debugged in.
Quality by design!
Important remark: Sigasi Visual HDL doesn’t aim to replace your $100,000 power lint checker with CDC (clock domain crossing) checks. Linting with Sigasi Visual HDL rather helps you catch many issues early and get the coding conventions first time right. The result of using Sigasi Visual HDL is an average time saving of 20% to 25% on a project, as reported by our users.
Free Linting webinar
You can learn more about linting with Sigasi Visual HDL for free from our experts! Join our webinar on October 15th at 9AM CET or at 9AM PDT. You will learn how to (better) use the linting tools in Sigasi and save valuable time and money. You can also ask questions after the webinar.
Linting with Sigasi Visual HDL
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2025-09-16, last modified on 2025-09-16