Evidence

Evidence by Category

The findings are grouped by workflow stage. Source labels are kept explicit so every assumption is traceable.

Research and case evidence are blended to separate validated results from scenario assumptions.

Duplicate Detection

Source-backed

This directly reduces triage queue churn and duplicated investigator time.

Mozilla ~30%

Eclipse ~20%

General 20-30% duplicate range

2.8 hours/duplicate caught

Validity Filtering

Source-backed

Filtering invalid and non-actionable items improves triage signal quality.

up to 70% invalid in selected literature

36% invalid+duplicate combined sample window

5.14 comments on WontFix issues

Automated Reproduction

Source-backed

Higher-quality S2R and behavior context enables automation-driven reproduction workflows.

ReBL: 90.63% success / 74.98s

AdbGPT: 81.3% / 253.6s

BugCraft: strong reduction vs 3.41-day manual baseline

BugScribe supports better reproducibility capture

Comparison table

Tool / StudySuccessAvg. timeEvidence note
ReBL90.63%74.98sPublished benchmark.
AdbGPT81.3%253.6sPrompt-driven Android replay benchmark.
BugCraftN/Aminutes (from baseline 3.41 days)LLM-agent reproduction in Minecraft setting.
EBugN/AN/AResearch focuses on guided report quality + construction speed.
BugScribeN/AN/AProject materials: automated structure and writing-time reduction context.

Clarification Overhead

Source-backed

Less back-and-forth accelerates fix entry and reduces idle delays.

~2.7 rounds/report

8-12 hours per round (case context)

18-22 hrs/week clarification burden

35% sprint-time waste estimate