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PROJECT DOSSIER // Algorithm analysis playground

Big O Lab

TECHNICAL OVERVIEW

Big O Lab is an interactive algorithm analysis playground that lets users write Python code, run experiments across different input sizes, and visualize runtime complexity directly from the browser.

ARCHITECTURE DETAILS

A browser-based workspace for learning and exploring algorithmic performance. Users can write or select algorithms, configure input profiles, run empirical experiments, inspect line-level runtime behavior, compare experiments, and generate complexity explanations using heuristic analysis or optional LLM support.

FIG 01 // SYSTEM DIAGRAM SCHEMATIC
PLAYGROUNDMonaco EditorRecharts / UIZustand StoreFRONTENDFASTAPI APIPydantic / CORSRate Limits / AuthROUTINGEXEC RUNNERPython SandboxTime InstrumentsINSTRUMENTCOMPLEXITY ENGEmpirical HeuristicsBig O AnalysisPERSIST / AIPostgreSQL (DB)Redis CacheOllama Cloud (LLM)
PROJECT SPECS
CategoryCOMPUTER SCIENCE / DEV TOOLING
StatusACTIVE
UpdatedJUN 2026
LAUNCH CODE REPO
SYSTEM DESIGN NOTE

Combines algorithms, execution instrumentation, backend systems, charts, sandboxing, rate limits, database persistence, and optional AI explanations.

TECHNOLOGY STACK
Next.jsMonaco EditorRechartsZustandFastAPIPostgreSQLRedisOllama Cloud
METADATA TAGS
#algorithms#developertools#fastapi#next.js#runtimeanalysis#llmexplanations