Bug Dedup Engine

Links duplicate bug reports and similar stack traces.

Industry	Level	Difficulty	Recommended mode
Software engineering	3 of 5	Advanced	flat

Coming soon

A complete, runnable Bug Dedup Engine reference implementation is in progress. The architecture and core code below already work with SrvDB 0.3.

The problem

• Duplicate bugs waste triage time.
• Stack traces vary slightly.
• Flaky tests hide patterns.

How SrvDB powers Bug Dedup Engine

1. Bug texts and traces are embedded.
2. New bugs retrieve likely duplicates.
3. Flaky failures cluster.
4. Batch processing for CI runs.

What changes

Today	With Bug Dedup Engine on SrvDB
Manual dedup	Suggested duplicates
Scattered traces	Grouped traces
Flaky noise	Clustered flakes

How it works

1. Embed bugs and traces.
2. Match new ones.
3. Suggest duplicates.
4. Cluster flakes.
5. Close duplicates.

SrvDB features it uses

• True cosine scores: scores in [-1, 1] mean the same in every mode, so thresholds are stable.
• search_batch: runs many queries at once, in parallel inside Rust.
• upsert: inserts new items and replaces changed ones, so the knowledge base stays current.
• Crash-safe persist(): after it returns, data survives a crash or power loss and reopens exactly as committed.

Use cases

• Duplicate bugs
• Crash grouping
• Flaky tests
• Log anomalies
• Support escalations
• Release triage

Core code

embed() is your embedding model (for example sentence-transformers, or a function that turns your records into feature vectors).

import json
import srvdb

db = srvdb.Database("./bug-dedup-engine-db", dimension=384)

def ingest(items):
    """items: list of (id, text, metadata dict)"""
    db.upsert(
        ids=[i for i, _, _ in items],
        embeddings=[embed(t) for _, t, _ in items],
        metadatas=[json.dumps(m) for _, _, m in items],
    )
    db.persist()                      # crash-safe checkpoint

def likely_duplicates(bug_report, k=5):
    hits = db.search(embed(bug_report), k)
    return [(json.loads(db.get(i)), round(score, 3)) for i, score in hits]

Limits and honest notes

• Triage leads confirm duplicates.

Build roadmap

1. Prototype: load a sample of real data with flat mode and check that searches return what an expert expects.
2. Measure: if you move to an approximate mode, compare its results with flat on the same queries (recall).
3. Pipeline: add continuous upsert and decide when to call persist().
4. Harden: test restarts and crashes, add logging, review every output path with domain experts.
5. Deploy: ship the database directory with the application or service.

All Software engineering projects

Level	Project	What it does
1 · Beginner	Code Search	Find code by what it does.
2 · Intermediate	Codebase Q&A	Ask how the system works and get answers citing files.
3 · Advanced	Bug Dedup Engine (this page)	Links duplicate bug reports and similar stack traces.
4 · Expert	Coding Agent Memory	Long-term, crash-safe memory for autonomous coding agents.
5 · Frontier	Air-gapped Dev Copilot	A self-hosted developer assistant for isolated environments.

See also: Use cases · Live examples (coming soon)