Android Performance

This is the eleventh article in the Systrace series, providing a brief introduction to Triple Buffer within Systrace. It covers how to identify jank in Systrace, perform preliminary localization and analysis, and explains the impact of Triple Buffer on performance.

The purpose of this series is to view the overall operation of the Android system from a different perspective using Systrace, while also providing an alternative angle for learning the Framework. Perhaps you’ve read many articles about the Framework but can never remember the code, or you’re unclear about the execution flow. Maybe from Systrace’s graphical perspective, you can gain a deeper understanding.

This is the tenth article in the Systrace series, primarily providing a brief introduction to Binder and lock information in Systrace. It covers the basic situation of Binder, the representation of Binder communication in Systrace, how to view Binder information, and analysis of lock contention in SystemServer.

The purpose of this series is to view the overall operation of the Android system from a different perspective using Systrace, while also providing an alternative angle for learning the Framework. Perhaps you’ve read many articles about the Framework but can never remember the code, or you’re unclear about the execution flow. Maybe from Systrace’s graphical perspective, you can gain a deeper understanding.

The content of this blog mainly focuses on Android development and optimization-related topics, including the use of performance tools, Android App optimization knowledge, Android Framework explanations, and performance theory. Here is an organized directory for your reference. You can choose the parts you are interested in. This directory includes not only blog content but also some of my answers on Zhihu or the Knowledge Planet - The Performance. This directory lists my original blog posts. Additionally, I have collected some excellent articles in Must-Knows for Android Performance Optimization, which I update periodically.

This is the seventh article in the Systrace series, primarily introducing the Vsync mechanism in Android. This article examines the display of each frame in the Android system from the perspective of Systrace. Vsync is a critical mechanism in Systrace. Although invisible and intangible when operating a phone, we can see in Systrace how the Android system, guided by Vsync signals, orderly performs rendering and composition for each frame, ensuring stable frame rates.

The purpose of this series is to view the overall operation of the Android system from a different perspective using Systrace, while also providing an alternative angle for learning the Framework. Perhaps you’ve read many articles about the Framework but can never remember the code, or you’re unclear about the execution flow. Maybe from Systrace’s graphical perspective, you can gain a deeper understanding.

This article compiles most current Android app startup optimization solutions. If you need optimization guidance, simply reference this article to review others’ approaches and identify gaps. Many solutions require business-specific adjustments, so this article doesn’t detail every method—when you need a particular solution, search online for its specific implementation. This serves as a comprehensive reference.

I’ve also included some system manufacturer optimizations related to startup, though I’ve only listed those I’m aware of. Some manufacturers have proprietary technologies not discussed here. Understanding manufacturer practices may help you—for example, contacting manufacturers for whitelisting or integrating their SDKs.

This article summarizes major Android app startup optimization strategies available today. If you need to optimize your app’s launch performance, use this as a checklist to identify gaps in your current implementation. Since many solutions depend on specific business requirements, I focus on presenting the options rather than deep-diving into every implementation detail. You can easily find specific technical guides for each method online.

I’ve also included some optimizations performed by system manufacturers. Understanding what happens at the OS level can help you make better decisions, such as requesting whitelisting or integrating manufacturer SDKs.

This is the ninth article in the Systrace series, primarily introducing the MainThread and RenderThread in Android Apps—commonly known as the Main Thread and Rendering Thread. This article examines their workflows from the perspective of Systrace and covers related topics: jank, software rendering, and dropped frame calculation.

The purpose of this series is to view the overall operation of the Android system from a different perspective using Systrace, while also providing an alternative angle for learning the Framework. Perhaps you’ve read many articles about the Framework but can never remember the code, or you’re unclear about the execution flow. Maybe from Systrace’s graphical perspective, you can gain a deeper understanding.

This is the sixth article in the Systrace series, primarily providing a brief introduction to Input in Systrace. It covers the Input workflow, how Input information is represented in Systrace, and how to combine Input info to analyze related performance issues.

The purpose of this series is to view the overall operation of the Android system from a different perspective using Systrace, while also providing an alternative angle for learning the Framework. Perhaps you’ve read many articles about the Framework but can never remember the code, or you’re unclear about the execution flow. Maybe from Systrace’s graphical perspective, you can gain a deeper understanding.

When an Android app moves to the background, it’s not unusual for it to keep performing work as long as the process isn’t killed—that’s just the nature of Android. However, some apps continue to run “zombie animations”—animations that are completely invisible to the user yet consume precious CPU cycles and battery. When users discover this, the result is often a manual kill, an OS-level background restriction, or an outright uninstallation.

Most developers never notice this issue. However, if you use Systrace regularly, you can easily spot it. If you open several apps, return to the home screen, and capture a trace while swiping between launcher pages, you’ll often see background apps still firing animation callbacks.

“Zombie animations” occur when an app, despite being invisible, continues to push CALLBACK_ANIMATION requests to the Choreographer. Every app is different, but the root cause is usually a missing pause or stop call.

This article introduces Choreographer, a class that app developers rarely encounter but is crucial in the Android Framework rendering pipeline. It covers the background of Choreographer‘s introduction, an overview, source code analysis, its relationship with MessageQueue, its use in APM, and optimization ideas from mobile manufacturers.

Choreographer was introduced to coordinate with Vsync, providing a stable timing for handling Messages in app rendering. When Vsync arrives, the system adjusts the Vsync signal period to control the timing of drawing operations for each frame. Most phones currently have a 60Hz refresh rate (16.6ms). To match this, the system sets the Vsync period to 16.6ms, waking Choreographer every period to perform app drawing—this is its primary role. Understanding Choreographer also helps developers grasp the principles of frame execution and deepens knowledge of Message, Handler, Looper, MessageQueue, Measure, Layout, and Draw.

In the Overview of Jank and Frame Drops in Android - System Layer article, we touched upon jank cases caused by low system memory. Since low memory has a significant impact on overall device performance, I’m dedicating this article to exploring those effects in depth.

As Android versions evolve and apps become more feature-heavy, their memory requirements increase. However, many devices with 4GB of RAM or less are still in use. These users are prone to low memory situations, especially after major system updates or as they install more apps.

Low memory triggers performance issues categorized by slow responsiveness and jank. Examples include longer app launch times, more frame drops in scrolling, more frequent cold starts as background processes are killed, and increased device temperature. Below, I’ll outline the causes, debugging methods, and potential optimizations for these issues.

This article was inspired by a real-world bug I encountered. While the issue itself wasn’t particularly “hard,” the analysis process—the tools used, the investigative logic, and some clever tips I learned from a colleague—made it a perfect candidate for a case study.

I’ve used a variety of tools mentioned in my Android Performance Optimization Methodology, including:

• Reproduction Video
• Event Log
• AS Source/Debug
• AS Profiler
• Systrace
• Dumpsys
• Unix ps utility

My goal is to document this process for myself and to share a universal troubleshooting workflow that might help others. If you have your own debugging tips, feel free to join our discussion group!

In the Overview of Jank and Frame Drops in Android - System Layer article, we listed causes of jank originating from the system. In this article, we focus on causes stemming from the App itself. When you encounter lag, before blaming the phone manufacturer, consider if it’s the App’s own inefficiency.

In the Overview of Jank and Frame Drops in Android - Application Layer article, we listed causes of jank originating from the app itself. In this article, we focus on causes stemming from the Android platform. Due to differences in hardware performance, feature implementations, and engineering capabilities among Android OEMs, system quality varies significantly. Here, we’ll categorize performance issues caused by system hardware and software.

Jank issues in Android are taken very seriously by both smartphone manufacturers and app developers. Internal teams, often called “Performance” or “Stability” groups, are typically dedicated to optimizing these experiences.

Currently, excellent third-party performance monitoring tools like Tencent’s Matrix are available. Phone manufacturers also have proprietary solutions. Since they can modify source code and bypass certain permission hurdles, manufacturers can access deeper system data, making analysis more efficient.