How DoorDash optimizes iOS performance
Showing 15 of 15 articles (Page 1 of 1)
DoorDash uses deep learning to nail ETA predictions with precision.
DoorDash rolls out updates with an eye on metrics to keep their app healthy.
DoorDash’s iOS team handles big releases with calm and precision.
DoorDash's approach to managing and coordinating mobile app releases across platforms.
DoorDash uses Flink to spot user sessions and send timely notifications.
DoorDash built a WebView-based FAQ hub for their Dasher app, using server-driven UI content and a promise-based communication protocol between native iOS/Android apps and web. This approach enables rapid conten...
DoorDash adopted XcodeGen to manage their Xcode project configuration in human-readable YAML files, eliminating pbxproj merge conflicts that plagued their 100+ engineer iOS team. The tool reduced merge conflict...
DoorDash reduced their iOS app launch time by 60% through three optimizations: replacing String(describing:) with ObjectIdentifier for type identification (22% gain), eliminating unnecessary AnyHashable convers...
DoorDash slashed iOS startup time by 60% with some smart moves.
DoorDash open-sourced PreviewSnapshots, a tool that eliminates code duplication between Xcode Previews and SnapshotTesting by allowing developers to define view configurations once and reuse them for both previ...
A topic of great debate among many engineers is whether or not SwiftUI is ready for enterprise. It’s no secret that DoorDash has fully embraced it in our Consumer app
Technical implementation guide for handling programmatic scroll behavior in SwiftUI.
DoorDash caches on the client side to make their app feel faster.
DoorDash tunes OpenTelemetry for fast tracing with low lag overhead.
Architecture and modularization strategies for sharing code across multiple iOS applications.