From Frustration
to Innovation

🔍 The Root Cause

I discovered that Microsoft Excel is not fully compliant with RFC-4180, and provides no built-in mechanism to dump CSV content directly into a VBA array. Excel's legacy import tools, Power Query, and even Power BI each fail on files that deviate from their narrow assumptions — like files using the apostrophe as a text qualifier instead of double quotes.

🌐 Community Solutions

✅ My Solution

I built a complete, RFC-4180-compliant CSV parser in pure VBA with configurable text qualifiers, delimiters, escape characters, and direct array import — the capability Excel itself lacks.

CSV Interface became the foundation from which every subsequent project emerged.

🔗 VBA CSV Interface on GitHub →

🧠 Mindset: Challenge the Platform, Not the User

When told my tool was poorly explained, I didn't argue — I showed a side-by-side comparison where CSV Interface produced the correct output and every Microsoft tool failed. Let the results do the talking.

🔍 The Root Cause

CSV Interface needed to automatically detect the dialect of unknown files. Existing tools treated this as character-level pattern matching — counting delimiter frequencies. But that's fundamentally the wrong approach when a file like 1,5;33,33;15,55 makes commas and semicolons genuinely ambiguous.

✅ My Solution: The Table Uniformity Method

Instead of asking "which character appears most consistently?", I asked: "which candidate delimiter produces the most uniform table?" This reframed dialect detection from signal processing to structural inference.

🔗 CSVsniffer on GitHub →

🧠 Mindset: The Empiricist Who Reframes the Question

The community dismissed the problem because they were solving the wrong one. I didn't accept their framing. I asked "what defines a correct parse?" and the answer — table uniformity — shifted the entire field.

🔍 The Root Cause

CSV Interface needed users to define computed fields dynamically. VBA has no native string-based expression evaluation, so I needed a library. Volpi MathParser was abandoned. stdLambda was well-crafted but carried two architectural limits:

⏱️ ~50x performance cliff on math functions (sin, cos, tan) — not a tuning issue, an architectural one.

🔢 Positional variables ($1, $2) — incompatible with programmatic variable injection from another library.

✅ My Solution

Phase 1 — VBA Expressions: Named variables with order-independent assignment: Run("x = 1; y = 2; z = 3"). "Analyze once, evaluate many" architecture.

Phase 2 — ASF: The evaluator naturally extended into a full JavaScript-like scripting language in pure VBA — with parser, compiler, VM, closures, classes with inheritance, module system, and VS Code tooling with 181 snippets.

🔗 ASF on GitHub →

🧠 Mindset: Follow the Architecture, Not the Scope

This isn't scope creep — it's scope discovery. Each limitation pointed to a deeper need. Once you have a proper parser, you're one step from closures; one step from there to first-class functions; one step from there to a complete language. I chose the overwhelming path because it was the correct one.

🔍 The Root Cause

VBA is a language frozen in time — no closures, no first-class functions, no module system. Millions of enterprise workbooks depend on it, but the language hasn't evolved in decades.

🌐 Alternatives & Their Limits

twinBASIC requires a new toolchain — not feasible in locked-down enterprises. stdLambda is valuable but constrained by VBA's grammar. Python/COM bridges add deployment complexity.

✅ My Solution: ASF as a Language Platform

ASF implements a new language on top of VBA rather than trying to extend VBA's syntax. This means zero external dependencies, no migration required, and modern features running on decades-old infrastructure.

🔌 Pure VBA · 🔄 Coexists with existing code · ✨ Closures, classes, modules · ⚡ VM-optimized · 🛠️ VS Code tooling

🔗 ASF on GitHub →

🧠 Mindset: Bridge Between Eras

Where others see VBA as a dead language to escape from, I see an ecosystem to elevate. I don't abandon users stuck on legacy platforms — I bring the future to them.