Here's an example of a detailed QA bug report I've created in the past (for a music streaming app similar to Echo, anonymized and formatted as it would appear in Jira or a similar tool). This one was for a crash issue that affected user retention.

Bug ID: ECHO-247

Title: iOS app crashes when adding a track to playlist from search results on iPhone 15 Pro (iOS 18.1)

Project/Component: Echo Mobile / Playlist Feature

Type: Bug

Severity: Critical (crashes core user flow)

Priority: High (impacts sharing and discovery features, reported by multiple beta users)

Reported By: Olaiya (QA)

Environment:

- Device: iPhone 15 Pro

- OS: iOS 18.1

- App Version: 2.3.4 (build 456)

- Account: Premium (free also reproduces)

- Network: WiFi / 5G (consistent)

Steps to Reproduce:

1. Launch the Echo app and log in.

2. Tap the search icon in the bottom nav.

3. Search for "Afrobeats mix 2025".

4. Tap the first track result to open the track player screen.

5. Tap the "+" add to playlist button.

6. Select "New Playlist" or an existing one from the list.

Actual Result: App crashes immediately after tapping to confirm/add the track. No error message; returns to home screen or forces close. Crash occurs 10/10 times.

Expected Result: Track adds successfully to the playlist, shows confirmation toast ("Added to [Playlist Name]"), and returns to track screen or playlist view without crashing.

Attachments:

- Screen recording: [attached video showing full repro + crash]

- Console logs: extracted via Xcode (crash log points to null pointer in PlaylistService.addTrack())

- Annotated screenshot of search and add flow just before crash

I approach bug identification and documentation systematically: catch issues early via planning reviews, then use exploratory testing on edge cases, devices, interruptions, and accessibility, plus automated regressions, analytics and replays, and beta feedback, always prioritizing crashes and core flows first. For docs, I write dev ready reports with a precise title (platform plus feature plus issue), environment details, numbered minimal repro steps, actual versus expected results, severity and priority with impact, annotated screenshots and recordings, logs, and frequency notes, ensuring they are clear, searchable, and reproducible for fast fixes.

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