ENTER COUNTEREXAMPLE · RUN WITNESS · READ MONOGRAPH · OPEN PROOFGRAPH · OPEN ENGINEERING OS · TAKE A PROOF TOUR · RÉSUMÉ · EVIDENCE MANIFEST
WITNESS verifies eight canonical receipts, runs each pinned C++/WebAssembly, TypeScript, or Python implementation inside the browser, compares the observed trace with its oracle, and emits a local run receipt. The local receipt is explicitly unattested; release provenance remains bound to COUNTEREXAMPLE.
Read the 23-page technical monograph · Inspect the GitHub edition · Download the Word edition
The publication formalizes WITNESS as an executable-evidence system through a threat model, eight capsule studies, eleven original diagrams, artifact-review readiness, explicit limitations, and a pinned identity register. It is independent technical documentation, not an awarded degree or peer-reviewed thesis.
Each route is a short, role-specific path through live systems, source, tests, measured evidence, and the regime where the result stops holding.
PROOFGRAPH is the interactive router across those routes: choose a hiring lens, then traverse one claim through its attack, oracle, measurement, boundary, exact source revision, and signed receipt.
Twelve losing regimes from eight public engines live in one constrained failure register. Each capsule binds the mechanism, attack, oracle, limitation, exact source revision, downloadable receipt, and GitHub-signed stable release.
Operate the register · Inspect the source · Verify the release · Submit a bounded counterexample
FaultGraph is a causal incident analysis workbench for operating on evidence rather than decorating a postmortem. It combines a FastAPI service, typed event contracts, checksum-addressed SQLite experiments, server-sent events, and a React/TypeScript forensic console.
| surface | released evidence |
|---|---|
| Model | transparent dynamic linear influence model with documented assumptions and bounded do(source=0) counterfactuals |
| Workbench | dependency graph, event timeline, ranked evidence, competing hypotheses, replay ledger, and keyboard command palette |
| Verification | 11 backend + 4 frontend tests, strict type/lint gates, container build, CodeQL, and zero open security alerts at release |
| Supply chain | signed v0.1.0 wheel, workbench archive, checksums, and GitHub attestations |
The model is deliberately bounded: it ranks evidence and executes explicit interventions; it does not claim unrestricted causal discovery from arbitrary observational logs.
Inspect the workbench · Read the architecture · Audit the research protocol · Verify CI
| system | mechanism | measured proof | reproduce |
|---|---|---|---|
| raft-mvcc | Raft + serializable MVCC + linearizability checking | 598 assertions across seeded faults; 11-tick five-node failover | make test |
| edgar-mcp | bounded SEC tools + cache validation + global pacing | 32 tests; 138× warm 10-K read; SEC ceiling enforced | make test |
| track-fusion | IMM + JPDA + track scoring + OSPA | 47% lower localization error in the published winning regime; failure sweep included | python -m pytest -q |
Clone and run all three
git clone https://github.com/asp53826/raft-mvcc && cd raft-mvcc && make test
git clone https://github.com/asp53826/edgar-mcp && cd edgar-mcp && make test
git clone https://github.com/asp53826/track-fusion && cd track-fusion && python -m pip install -e '.[dev]' && python -m pytest -qBuild the mechanism. Attack the assumption. Measure against a named baseline. Publish the boundary. Bind the evidence to source.
The portfolio is organized as an engineering laboratory, not a gallery of screenshots. The interactive pages expose controls; the repositories expose implementation and tests; the evidence manifest records commands, units, and limitations.
| instrument | what it exposes |
|---|---|
| FAULTLINE | a real C++17 Raft + MVCC engine in WebAssembly, including minority leaders, conflict repair, and passing or failing histories |
| KERNELARENA | typed tensor IR, fusion, liveness-aware memory reuse, generated WGSL, and a browser-local oracle |
| SIGNALROOM | truth, measurements, residuals, uncertainty, and the manoeuvre regime where an estimator loses |
| MARKETWIRE | toxicity, quote age, inventory control, deterministic shocks, and a committed 20,000-step benchmark |
| WITNESS | receipt hashing, pinned browser execution, deterministic oracles, tamper detection, and local run receipts |
| Benchmark Observatory | exact commits, commands, environments, units, baselines, and limitations |
| Demo Cinema | four captioned engineering films under one minute with direct routes into the running system |
Open the complete source catalog
faultgraph · counterexample · portfolio-ops · witness · proofgraph
raft-mvcc · dst-harness · hotstuff-bft · wal-recovery · lsm-tree · columnar-engine · query-planner · cdcl-sat
tensorforge-webgpu · vllm-lite · annlite · dist-train · feature-store · rag-eval · grammar-decode · ptq-budget · agent-harness · codebase-qa
sdr-receiver · sar-focus · track-fusion · vio-nav
edgar-mcp · xbrl-normalize · lob-market-making · aad-greeks · backtest-honest
Inspect source-backed telemetry and delivery
The daily workflow reads public source and counts test functions without a
third-party stats card or page-load API call. Parametrized and looped suites
execute more checks than the function count—for example, raft-mvcc alone
executes 598 assertions.
Portfolio Ops maintains the public systems through eight auditable roles: repository verification, benchmark evidence, dependency care, documentation checks, demo monitoring, verified releases, achievement-state monitoring, and profile curation. Automation uses the GitHub Actions bot identity, retains raw evidence, and does not manufacture human contributions or interact with third-party repositories.
Patch dependency updates may auto-merge only after repository checks pass. Source changes, major upgrades, external contributions, benchmark claims, and account or legal decisions remain outside the autonomous boundary.
| Project | Primary language | Latest release | Latest completed workflow |
|---|---|---|---|
| faultgraph | Python | v0.1.0 | CI: success |
| raft-mvcc | C++ | v1.0.0 | Autonomous Engineering Lab: success |
| edgar-mcp | Python | v0.1.0 | Autonomous Engineering Lab: success |
| track-fusion | Python | No published release | Autonomous Engineering Lab: success |
| tensorforge-webgpu | TypeScript | No published release | Autonomous Engineering Lab: success |
| columnar-engine | C++ | No published release | Autonomous Engineering Lab: success |
| lsm-tree | C++ | No published release | Autonomous Engineering Lab: success |
| counterexample | CSS | v1.0.0 | OpenSSF Scorecard: success |
| portfolio-ops | Python | No published release | Control Plane CI: success |
This block is regenerated only when GitHub's repository, release, or workflow data changes.
aaryansp26@gmail.com · Systems résumé · Systems Observatory · LinkedIn
UGA computer science, December 2026. Industrial data engineering at MP Equipment. Every system above is MIT licensed: clone one, run the benchmark, and inspect the regime where it breaks.
All profile visuals are first-party SVGs generated in this repository.
Motion is limited to signal flow and respects prefers-reduced-motion.


