didi/booster

🚀Optimizer for mobile applications

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Summary Information

Updated 43 minutes ago
Added to GitGenius on September 13th, 2026
Created on April 23rd, 2019
Open Issues & Pull Requests: 52 (+0)
GitHub issues: Enabled
Number of forks: 592
Total Stargazers: 5,070 (+0)
Total Subscribers: 113 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.2 days
Mean response time: 100.4 days
90th percentile: 360.1 days
Tracked items: 24

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Issue Activity (beta)

Open issues: 14
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 765 days
Stale 30+ days: 14
Stale 90+ days: 14

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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  • feature (1)

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Detailed Description

Booster is a Gradle plugin and bytecode manipulation framework that optimizes mobile applications for performance, stability, and package size.

Booster addresses quality problems that emerge as Android applications grow in complexity by operating at the bytecode level during the build process. It detects potential performance issues such as blocking I/O operations on the UI thread, optimizes thread management to prevent excessive thread creation from third-party SDKs, fixes system-level bugs like crashes in specific Android versions, and reduces package size through techniques like resource index inlining. The toolkit works as a collection of modular transformers that intercept and modify application bytecode before compilation completes.

Teams building Android applications should consider Booster if they face performance bottlenecks, stability issues, or need to reduce APK size. It suits projects where third-party SDK integration creates threading challenges or where systematic performance detection across a large codebase is needed. The framework is designed to be lightweight and extensible, allowing teams to enable only the optimization modules relevant to their application. Booster requires Gradle 4.10 or later and Android Gradle Plugin 3.3 or later, with JDK 1.8 as the minimum though JDK 11 is recommended.

The project maintains active development with regular updates to its transformation modules and documentation. The codebase is written primarily in Kotlin and demonstrates ongoing refinement of its optimization capabilities. The toolkit includes well-documented modules for specific optimization domains, suggesting sustained investment in both breadth of features and clarity for adopters.