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Zero Code Test Automation Platform

for Java/Kotlin/Spring

Validate every code change automatically. BitDive turns real application behavior into reliable, self-updating autotests, eliminating the need to write and maintain test code.

Zero-Code AutomationNo scripts, no maintenance, no technical debt
Log-less DebuggingSee errors, SQL, and method-level call chains
Smart VirtualizationAuto-mocks or real Testcontainers for integration
Executable Bug ReportsDebug production bugs locally with real data
Performance ProfilingDetect N+1 queries & bottlenecks in real-time
Ready for ProductionLow Overhead ~0.1-5% CPU. Runs in any environment
Zero Code Test Creation Animation
BitDive Zero Code Architecture Diagram

Scale Your Test Coverage, Not Your Codebase

Stop writing test code to test code

BitDive converts real executions into deterministic replay tests in a few clicks and without AI slop. True Zero-Code means no manual mock maintenance, no "code bloat," and less surface area for bugs in your tests.

  • Tests in Clicks: Record real application behavior and select captured calls and traces to build replay suites.
  • Maven and JUnit Native: Tests run as standard Maven and JUnit tests, but the logic comes from observed runtime behavior and a replay plan, not handwritten automation.
  • Deterministic, Not AI Hallucinations: Replay tests are derived from real captured executions, not invented by AI. Same inputs, same behavior, repeatable results.
  • Less Flakiness, Less Maintenance: No fragile scripts, no hand made mocks, fewer test only bugs and less QA automation tech debt.
Book a Demo

Watch BitDive Turn Application Behavior into Automated Tests

Complete workflow: Capture live scenarios → Inspect runtime behavior → Generate Zero-Code tests → Replay in CI/CD.

Watch BitDive Video Walkthrough

See Zero-Code Test Automation in Action

BitDive Log-less Debugging and Tracing

Log-Less Debugging and Root Cause Analysis

Production bugs run locally with full context

A developer takes a callId from production or a test environment and replays it locally in debug mode with the same inputs and the same execution chain, down to each method call. The exact scenario that happened, made reproducible.

  • White Box, No Log Guessing: The failure shows up immediately in the call tree, down to the exact method, exception, and SQL query. No log archaeology required.
  • Shared Reality: QA and Dev see the same execution facts, including parameters, downstream responses, and the full chain across services.
  • Fastest Repro: Turn “not reproducible” into an executable failure path. Fix it, then replay the same callId to validate.
  • Painless Setup in 15 Minutes: Add the BitDive libraries, paste a short UI generated config, and you are live. Auto instrumentation by default. No code changes, no annotations.
Explore Method-Level Observability
System Health and Profiling

Performance and System Health for Microservices

Find bottlenecks, fix them, verify speed and correctness

BitDive surfaces performance issues directly in the UI, combining distributed traces across services with method level chains and SQL patterns. The same context is available to AI via MCP, so fixes are guided by real executions.

  • Distributed tracing, end to end: Follow a request across microservices, then drill down to the exact method chain and SQL burst.
  • Detect N+1 and hotspots: Heatmaps and traces expose query explosions, slow paths, and the exact endpoint that triggers them.
  • Pinpoint root cause in code: See the exact method chain and SQL pattern causing the degradation, not static analysis guesses.
  • Validate fix: Compare before and after traces on the same scenario. Clear deltas in latency and query count.
Explore Code-Level Observability
AI Code Validation with Runtime Context

Runtime Intelligence for Humans and AI Agents

Equipping AI with tools to analyze execution and verify fixes

BitDive bridges the gap between static code analysis and real system behavior. It supercharges RAG pipelines and AI coding assistants with actual execution data and enables deterministic verification, so you ship only what is proven.

  • Runtime Context via MCP: Enable AI agents to retrieve runtime context on demand. Access call chains, parameters, results, SQL, latencies, and cross-service flows instantly.
  • Runtime-Grounded Code Generation: AI generates code based on the actual execution graph and object states, eliminating hallucinations and aligning logic with real system behavior.
  • Real Error Understanding for Surgical Fixes: Analyze the exact failure path, exception flow, and SQL bursts to enable precise, surgical remediation instead of trial-and-error debugging.
  • Deterministic Verification with Replay: Replay the same captured scenario to compare behavior before and after changes, validating both correctness and performance.
Supercharge AI with Runtime Context

How It Works: Capture, Replay, Validate

Real Zero Code: From traffic to test in 3 steps

01

Capture: Real Application Behavior

From Any Environment

The platform agent runs in your Java/Kotlin services, capturing complete execution context without code changes.

  • Method calls with parameters and return values
  • SQL queries with actual parameters and results
  • HTTP requests and responses (REST, gRPC, Kafka)
  • Cross-service distributed traces
  • Exception stack traces with full context
Result: Zero performance impact. Zero code changes. Complete behavioral record.
02

Replay: Executable Test Scenarios

Auto-mocked, deterministic, isolated

The platform transforms captured traces into executable test scenarios with automatic dependency isolation.

  • Auto-generates mocks for databases, APIs, and message queues
  • Recreates exact execution context from the recording
  • Runs in any environment (local, CI, staging) without external dependencies
  • Deterministic execution—same inputs always produce same outputs
  • No test code to write or maintain
Result: Regression tests that reflect reality, not assumptions.
03

Verify: Semantic Drift Detection

Behavior validation, not just status checks

BitDive compares execution behavior before and after code changes to detect regressions.

  • Compares SQL query patterns and results
  • Validates HTTP response bodies and structures
  • Detects changes in method call sequences
  • Identifies performance regressions
  • Distinguishes bug fixes from breaking changes
Result: Catch regressions in logic, not just broken mocks.

Measurable Impact

For Business

75%
Fewer Production Incidents
Catch regressions before deployment
3x
Faster Release Cycles
Eliminate slow, flaky test suites
60%
Reduced QA Tech Debt
No test framework maintenance

For QA & Development

80%
Less Time on Test Maintenance
Focus on analysis, not infrastructure
90%
Faster Root Cause Identification
See exact failing method instantly, not log archaeology
100%
Behavioral Coverage
Tests based on real application behavior, not assumptions

Integrate with Your Development & AI Stack

JavaJava
KotlinKotlin
SpringSpring
PostgreSQLPostgreSQL
MySQLMySQL
MariaDBMariaDB
MongoDBMongoDB
RedisRedis
Model Context ProtocolModel Context Protocol
OllamaOllama
CursorCursor
WindsurfWindsurf
OpenAIOpenAI
GitHub CopilotGitHub Copilot
AnthropicAnthropic
ClaudeClaude
GeminiGemini
GrokGrok
Mistral AIMistral AI
DeepSeekDeepSeek
PerplexityPerplexity
v0v0
CodyCody
VS CodeVS Code
Visual StudioVisual Studio
IntelliJ IDEAIntelliJ IDEA
DockerDocker
KubernetesKubernetes
AzureAzure
GitHubGitHub
GitLabGitLab
KeycloakKeycloak

Ready to Stop Writing Tests?

Transform QA from manual effort to autonomous runtime intelligence. Capture reality, replay anywhere, and deploy with confidence.