iOS/Android应用崩溃分析指南：降低崩溃率，提升App Store排名与评分

crash-analytics by eronred/aso-skills

81 周安装量

597 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/eronred/aso-skills --skill crash-analytics

iOS 数据分析性能优化

🇨🇳中文介绍

崩溃分析

您可以帮助分类、确定优先级并减少应用崩溃——同时了解崩溃率如何影响 App Store 的可发现性和评分。

为什么崩溃率是 ASO 信号

App Store 排名 — Apple 的算法会惩罚崩溃率高的应用
App Store 推荐 — 高崩溃率会失去编辑推荐资格
评分 — 崩溃是导致一星评价的首要原因
用户留存 — 首次会话中的崩溃会彻底破坏首日留存率

目标： 无崩溃会话 > 99.5% | 无崩溃用户 > 99%

工具

工具	提供内容	设置步骤
Firebase Crashlytics	实时崩溃、ANR、符号化堆栈跟踪	添加 `FirebaseCrashlytics` pod/SPM 包
App Store Connect	崩溃率趋势、每次会话的崩溃数	内置，无需代码
Xcode Organizer	来自 TestFlight 和 App Store 的聚合崩溃日志	Xcode → Window → Organizer → Crashes

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非致命错误（追踪而不导致崩溃）

// 记录一个非致命错误
Crashlytics.crashlytics().record(error: error)

// 记录自定义键值用于调试上下文
Crashlytics.crashlytics().setCustomValue(userId, forKey: "user_id")
Crashlytics.crashlytics().setCustomValue(screenName, forKey: "current_screen")

// build.gradle (app)
implementation("com.google.firebase:firebase-crashlytics:18.x.x")

// 无需额外代码 —— 自动捕获未处理的异常
// 对于非致命错误：
FirebaseCrashlytics.getInstance().recordException(throwable)

并非所有崩溃都同等重要。根据影响程度确定优先级：

优先级分数 = 崩溃频率 × 受影响用户数 × 用户群体权重

优先级	标准	响应时间
P0 — 严重	启动/结账/核心功能时崩溃；影响 >1% 的会话	今日修复
P1 — 高	常见流程中崩溃；影响 >0.1% 的会话	本次发布修复
P2 — 中	边缘情况崩溃；影响 <0.1% 的会话	下次发布修复
P3 — 低	罕见、非阻塞性崩溃；影响 <0.01% 的会话	待办事项

Crashlytics 仪表板分类

按 "影响"（受影响的独立用户数）排序，而非频率
分组：onboarding、checkout、core feature、background、launch
将 P0/P1 优先级分配给前 3–5 个问题
在 Crashlytics 中为任何影响 >0.5% 用户的问题设置 速率警报

Fatal Exception: com.example.NullPointerException
  at com.example.UserProfileVC.loadData:87
  at com.example.HomeVC.viewDidLoad:45

Keys:
  user_id: 12345
  current_screen: "home"
  app_version: "2.3.1"
  os_version: "iOS 17.3"

在 Xcode 中打开文件和行号 (UserProfileVC.swift:87)
检查该位置可能为 nil 的内容
使用用户上下文（操作系统版本、设备、屏幕）复现问题
修复前编写一个失败的测试用例

如果您上传了 dSYM 文件，Crashlytics 会自动进行符号化。如果看到未符号化的堆栈跟踪：

# 手动上传 dSYM 文件
./Pods/FirebaseCrashlytics/upload-symbols -gsp GoogleService-Info.plist -p ios MyApp.app.dSYM

对于启用了 Bitcode 的构建，从 App Store Connect → Activity → Build → dSYMs 下载 dSYM 文件。

App Store Connect 崩溃数据

App Store Connect → App Analytics → Crashes — 每个版本的崩溃率趋势
比较每次发布前后的崩溃率
特定版本出现峰值 = 该版本存在回归问题

崩溃率公式： 崩溃次数 / 会话次数 × 100

最小化影响范围的发布策略

使用分阶段发布，以便在全面推出前捕获崩溃：

iOS： App Store Connect → Version → Phased Release (7 天推出：1% → 2% → 5% → 10% → 20% → 50% → 100%)

Android： Play Console → Production → Managed publishing → Rollout percentage

规则： 在每个阶段监控 Crashlytics 24 小时。如果崩溃率增长 >0.2%，则暂停发布。

应对由崩溃引发的一星评价

识别出现崩溃相关一星评价的应用版本
修复该崩溃问题
回复每条与崩溃相关的评价："已在 X.X 版本修复 —— 请更新应用"
更新发布后，使用 rating-prompt-strategy 来恢复评分

Stability Report — [App Name] v[version] ([period])

Crash-free sessions: [X]%  (target: >99.5%)
Crash-free users:    [X]%  (target: >99%)
Top crash issues:

P0 Issues (fix immediately):
  #1 [Exception type] — [X] users, [X]% of sessions
     File: [filename:line]
     Cause: [hypothesis]
     Fix: [specific action]

P1 Issues (this release):
  #2 [Exception type] — [X] users, [X]% of sessions
     ...

Action Plan:
  Today:     Fix P0 issue #1 → release hotfix
  This week: Fix P1 issues #2, #3 → include in v[X.X]
  Monitoring: Set velocity alert at 0.5% session threshold

app-analytics — 完整的分析栈；Crashlytics 是其中一部分
rating-prompt-strategy — 修复由崩溃引发的一星评价后恢复评分
review-management — 回应与崩溃相关的评价
retention-optimization — 首日崩溃会破坏留存指标
app-store-featured — 崩溃率 > 2% 将失去编辑推荐资格

🇺🇸English

Crash Analytics

You help triage, prioritize, and reduce app crashes — and understand how crash rate affects App Store discoverability and ratings.

Why Crash Rate Is an ASO Signal

App Store ranking — Apple's algorithm penalizes apps with high crash rates
App Store featuring — High crash rate disqualifies editorial consideration
Ratings — Crashes are the #1 cause of 1-star reviews
Retention — A crash in the first session destroys Day 1 retention

Target: crash-free sessions > 99.5% | crash-free users > 99%

Tools

Tool	What it provides	Setup
Firebase Crashlytics	Real-time crashes, ANRs, symbolicated stack traces	Add `FirebaseCrashlytics` pod/SPM package
App Store Connect	Crash rate trend, crashes per session	Built-in, no code needed
Xcode Organizer	Aggregated crash logs from TestFlight + App Store	Xcode → Window → Organizer → Crashes
MetricKit	On-device diagnostics, hang rate, launch time	iOS 13+, automatic

Recommended: Crashlytics (real-time alerts + search) + App Store Connect (trend validation)

Crashlytics Setup

iOS (Swift)

// AppDelegate or @main App struct
import FirebaseCore
import FirebaseCrashlytics

@main
struct MyApp: App {
    init() {
        FirebaseApp.configure()
        // Crashlytics is auto-initialized
    }
}

Non-fatal errors (track without crashing)

// Log a non-fatal error
Crashlytics.crashlytics().record(error: error)

// Log a custom key for debugging context
Crashlytics.crashlytics().setCustomValue(userId, forKey: "user_id")
Crashlytics.crashlytics().setCustomValue(screenName, forKey: "current_screen")

Android (Kotlin)

// build.gradle (app)
implementation("com.google.firebase:firebase-crashlytics:18.x.x")

// No additional code needed — auto-captures unhandled exceptions
// For non-fatal:
FirebaseCrashlytics.getInstance().recordException(throwable)

Triage Framework

Not all crashes are equal. Prioritize by impact:

Priority Score = Crash Frequency × Affected Users × User Segment Weight

Priority	Criteria	Response time
P0 — Critical	Crashes on launch / checkout / core feature; >1% of sessions	Fix today
P1 — High	Crashes in common flows; >0.1% of sessions	Fix this release
P2 — Medium	Edge case crashes; <0.1% of sessions	Fix next release
P3 — Low	Rare, non-blocking crashes; <0.01% of sessions	Backlog

Crashlytics Dashboard Triage

Sort by "Impact" (unique users affected), not frequency
Group: onboarding, checkout, core feature, background, launch
Assign P0/P1 to the top 3–5 issues
Set a velocity alert in Crashlytics for any issue affecting >0.5% of users

Reading a Crash Report

Fatal Exception: com.example.NullPointerException
  at com.example.UserProfileVC.loadData:87
  at com.example.HomeVC.viewDidLoad:45

Keys:
  user_id: 12345
  current_screen: "home"
  app_version: "2.3.1"
  os_version: "iOS 17.3"

Steps to debug:

Open the file and line in Xcode (UserProfileVC.swift:87)
Check what can be nil at that point
Reproduce with the user context (OS version, device, screen)
Write a failing test before fixing

Symbolication

Crashlytics auto-symbolicates if you upload dSYMs. If you see unsymbolicated traces:

# Manually upload dSYMs
./Pods/FirebaseCrashlytics/upload-symbols -gsp GoogleService-Info.plist -p ios MyApp.app.dSYM

For Bitcode-enabled builds, download dSYMs from App Store Connect → Activity → Build → dSYMs.

App Store Connect Crash Data

App Store Connect → App Analytics → Crashes — Crash rate trend per version
Compare crash rate before and after each release
A spike on a specific version = regression in that release

Crash rate formula: Crashes / Sessions × 100

Release Strategy to Minimize Blast Radius

Use phased releases to catch crashes before full rollout:

iOS: App Store Connect → Version → Phased Release (7-day rollout: 1% → 2% → 5% → 10% → 20% → 50% → 100%)

Android: Play Console → Production → Managed publishing → Rollout percentage

Rule: Monitor Crashlytics for 24 hours at each phase. If crash rate increases >0.2%, pause rollout.

Responding to Crash-Driven 1-Star Reviews

Identify the app version where crash-related 1-stars appeared
Fix the crash
Reply to each crash-related review: "Fixed in version X.X — please update"
After update ships, use rating-prompt-strategy to recover rating

Output Format

Crash Audit Report

Stability Report — [App Name] v[version] ([period])

Crash-free sessions: [X]%  (target: >99.5%)
Crash-free users:    [X]%  (target: >99%)
Top crash issues:

P0 Issues (fix immediately):
  #1 [Exception type] — [X] users, [X]% of sessions
     File: [filename:line]
     Cause: [hypothesis]
     Fix: [specific action]

P1 Issues (this release):
  #2 [Exception type] — [X] users, [X]% of sessions
     ...

Action Plan:
  Today:     Fix P0 issue #1 → release hotfix
  This week: Fix P1 issues #2, #3 → include in v[X.X]
  Monitoring: Set velocity alert at 0.5% session threshold

Related Skills

app-analytics — Full analytics stack; Crashlytics is one piece
rating-prompt-strategy — Recover rating after fixing crash-driven 1-stars
review-management — Respond to crash-related reviews
retention-optimization — Crashes on Day 1 destroy retention metrics
app-store-featured — Crash rate > 2% disqualifies editorial featuring

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iOS/Android应用崩溃分析指南：降低崩溃率，提升App Store排名与评分

🇨🇳中文介绍

崩溃分析

为什么崩溃率是 ASO 信号

工具

相关 Skills

Crashlytics 设置

iOS (Swift)

非致命错误（追踪而不导致崩溃）

Android (Kotlin)

分类框架

Crashlytics 仪表板分类

阅读崩溃报告

符号化

App Store Connect 崩溃数据

最小化影响范围的发布策略

应对由崩溃引发的一星评价

输出格式

崩溃审计报告

相关技能

🇺🇸English

Crash Analytics

Why Crash Rate Is an ASO Signal

Tools

Crashlytics Setup

iOS (Swift)

Non-fatal errors (track without crashing)

Android (Kotlin)

Triage Framework

Crashlytics Dashboard Triage

Reading a Crash Report

Symbolication

App Store Connect Crash Data

Release Strategy to Minimize Blast Radius

Responding to Crash-Driven 1-Star Reviews

Output Format

Crash Audit Report

Related Skills

最新 Skills