Improving AST Parsing & Self-Healing Test Loops in LuxurAI Coder

What We Built Today

Today, we enhanced LuxurAI Coder’s AST parsing and self-healing test loops to make code generation more reliable. LuxurAI Coder is an autonomous software engineering agent designed to work directly inside real codebases, planning multi-file changes, executing diffs, and self-healing test failures.

The Problem We Solved

One of the biggest challenges in autonomous code generation is ensuring reliability across large, complex codebases. Traditional methods often fail to handle multi-file dependencies and runtime errors effectively.

How The Architecture Works

Our pipeline combines hybrid model orchestration with local AST parsers and verification tooling. The 5-layer accuracy booster ensures clean, reliable code generation:

1. SelfHealingValidator: Runs tests in an isolated sandbox.
2. PromptOptimizer: Enriches vague prompts with codebase context.
3. EnsembleVoter: Selects the cleanest implementation from parallel model outputs.
4. StructureCheck: Guards against accidental deletion of critical classes.
5. IndentationNormalizer & AST Validator: Ensures syntax integrity.

Transparent Economics

LuxurAI operates on a pay-as-you-go credit model priced at ₹0.25 per credit (25 paise/credit). No subscriptions, no hidden fees.

How We Can Make This Better

This is still an experimental beta, and we’re actively debugging edge cases. We’d love feedback from Python developers on improving AST-diff accuracy and test-healing reliability.

Try it out and let us know what you think: LuxurAI Coder

What do you feel? How can we make this better? Would love your honest thoughts!