CodeLogician Documentation
CodeLogician helps AI coding agents reason about complex software using math and logic.
Instead of only generating code and explanations, CodeLogician forces the agent to build a mathematical mental model of the system and uses automated reasoning to uncover:
- edge cases
- decision boundaries
- invariants
- hidden behavioral interactions
before software is deployed.
What CodeLogician Adds to AI Coding
LLM-based coding assistants are extremely good at generating code, but their reasoning is fundamentally statistical.
CodeLogician introduces a logic-first reasoning layer that systematically analyzes software behavior.
Instead of sampling possible executions, CodeLogician:
- builds a formal behavioral model
- explores the full decision space
- proves correctness properties
- produces concrete counterexamples when assumptions fail
This transforms AI-assisted development from:
"looks correct"
into
"behavior understood"
How CodeLogician Works
LLM-only workflow
AI coding assistants typically operate like this:
- The user asks for code
- The LLM generates an implementation
- The user reviews the result manually
Edge cases and behavioral boundaries are often missed because the model only samples likely paths.
Logic-first workflow
CodeLogician augments the workflow by introducing a formal reasoning step.
The LLM produces a structured model of the system, which is then analyzed by the ImandraX reasoning engine.
This produces artifacts such as:
- counterexamples
- verified invariants
- behavioral decompositions
- high‑coverage test cases
The result is evidence-backed reasoning, not just generated output.
Where CodeLogician Helps Most
CodeLogician is most valuable when software encodes complex behavior, not just simple transformations.
Examples include:
- state machines
- distributed systems
- payment and pricing logic
- access control systems
- compliance and risk rules
- workflow orchestration
These systems often contain combinatorial behavioral complexity that traditional testing or LLM reasoning alone cannot fully explore.
| Reasoning domains | Examples | Software Abstraction High | CodeLogician applicability |
|---|---|---|---|
Architectural designs | SysML v2 modeling, verification and testing | ||
Multi-system integration testing | Integration testing | ||
Functional requirements | Requirements modeling and functional testing | ||
Low-level application-specific | SQL injection issues | ||
Hardware-related concerns | Memory allocation in C++ | ||
Low | |||
Powered by ImandraX
CodeLogician is built on ImandraX, a high‑performance automated reasoning engine used to analyze complex real‑world systems.
ImandraX enables CodeLogician to:
- systematically explore behavioral state spaces
- prove logical properties of systems
- synthesize executable counterexamples
- reason about complex numerical and structural constraints
This allows AI-generated software to be evaluated with mathematical rigor rather than probability.
Getting Started
To run CodeLogician, obtain an Imandra Universe API key (free tier available) from:
Make sure it is available in your environment as IMANDRA_UNI_KEY.
Typical CodeLogician Workflows
1. Direct CLI workflow
Invoke reasoning tools directly from the command line.
Typical steps:
- Use
codelogician docto explore the IML language and reference materials - Convert source code into formal models
- Run
evalcommands to analyze behavior and verify properties - Inspect counterexamples and generated tests
2. Agent‑assisted formalization
CodeLogician includes an autoformalization agent that converts source code into analyzable models.
Common usage:
codelogician agent PATH_TO_FILEcodelogician multiagent PATH_TO_DIRECTORY
This allows coding agents to iteratively improve formal models and reasoning results.
3. Interactive reasoning server
The CodeLogician server provides a live environment for multi‑agent reasoning.
Features include:
- continuous model updates
- interactive analysis
- integration with the terminal UI (TUI)
This mode is useful for complex projects where models evolve continuously.
Getting Started
New to CodeLogician? Start here:
- Get your Imandra Universe API key
- Getting Started — install CodeLogician and run your first reasoning example
Tutorials
Step‑by‑step walkthroughs for common workflows:
- CLI Tutorial — working with the CodeLogician CLI
- TUI Tutorial — using the terminal interface
Real‑World Examples
Explore production‑style analyses demonstrating CodeLogician capabilities:
Highlighted examples:
- Algorithmic trading rules analysis
- Financial market infrastructure verification
- workflow reasoning and system integration analysis
These examples include formal models, reasoning artifacts, and visual workflow diagrams.
Further Help
Need assistance or want to explore enterprise deployments?