A runtime map of your codebase.
Atlas turns per-test coverage into a navigable map of the behavior a codebase actually exhibits under test—so engineers can see which code runs together, what a change may touch, and where the available runtime evidence is thin.
Generated code got faster. Code comprehension did not.
When people write code, they build a runtime mental model by running it, inspecting failures, and tracing state through the system. Generated code can arrive without anyone having walked the same execution paths. The result is more code whose local shape looks plausible while its wider runtime effects remain difficult to review.
Language servers, type checkers, static analyzers, and LLMs remain useful. They are strongest around the code being inspected. Behavior established earlier in a run, observed by another component, or created through state and concurrency only becomes concrete when the program executes.
Atlas treats tests as repeatable execution probes. It records what each test executes and turns those observations into a living behavioral map. As tests run, the map can stay current with the execution paths the suite exercises instead of leaving those paths implicit in raw coverage.
From test runs to observed behavior.
- tests
- per-test coverage
- code ranges
- observed behaviors
- navigable topology
- Observe
- Run tests separately and record the code each test executes. The result is a binary relationship between tests and code.
- Compress
- Combine consecutive lines in a file when the same set of tests executes them. Each maximal run becomes a code range without discarding the underlying line relationship.
- Group
- Apply Formal Concept Analysis to identify maximal groupings of code ranges and tests defined by the execution data. Atlas calls each grouping an observed behavior.
- Navigate
- Organize large results as Project → Cluster → Group → File so a visitor can move from system-level structure to exact code and tests.
The technical article explains the coverage matrix, FCA, code-range model, AOC-poset, and topology in detail.
Navigate and change the codebase with runtime evidence.
Behavioral navigation over string searching
Text searches find names and IDEs find callers. Atlas lets developers move from a test to its execution footprint across the codebase, or from a code range to the tests and shared paths that reached it.
Surgical impact analysis
Before editing a large file, Atlas reveals whether the target range belongs to an isolated feature or shared substrate exercised across many scenarios. This gives the team an empirical baseline of risk before the change.
Exposing test-suite debt
Atlas surfaces ranges protected by only one observed test and tests that add no unique execution footprint to the collected dataset, making fragile and redundant coverage visible.
Detecting architectural drift
Directory structure shows how developers intended to organize code. Shared test execution shows how code interacts at runtime. Atlas highlights coupling that crosses the intended package and directory boundaries.
Ground coding agents in runtime behavior.
Coding agents are good at following names, imports, types, and nearby call sites. They should not have to simulate a large, stateful execution in a context window. Atlas compresses raw coverage into structured, high-density units of observed behavior, giving agents exact execution boundaries instead of forcing them to guess from source text alone.
Explore real repositories.
At publication, the public Atlas catalog contains several open-source repository analyses across Go, TypeScript, and Python. Each catalog entry identifies a pinned repository revision so the displayed analysis has an explicit source version. The Temporal Server entry is a partial analysis built from unit and integration test coverage; its full CI matrix is not included.
Bring Atlas to your codebase.
Atlas is an early solo project being shaped in the open. I am looking for design partners who want to run it on a real repository, test whether the map answers useful review and architecture questions, and influence what the product becomes.
I am also available for consulting and engineering contracts around codebase comprehension, test-derived analysis, and agentic development workflows.