That’s why we recommend this cleaning app. This application is also called in-depth cleaning of junk files. In the next part of this blog, we will talk about the best practices on Startup latency, app size and the tools used by Google apps to identify and fix performance issues.SD Maid is the most popular and also underrated phone cleaner app. Recap This part of the blog outlines why developers should consider building for Android (Go edition), a standard approach to follow while optimizing their apps and some recommendations & learnings from Google apps to improve their app memory and appropriately allocate resources. The Draw 9-patch tool is a WYSIWYG editor included in Android Studio that allows you to create bitmap images that automatically resize to accommodate the contents of the view and the size of the screen. All of these tools can reduce PNG file size while preserving the perceptive image quality. You can reduce PNG file sizes without losing image quality using tools like pngcrush, pngquant, or zopflipng.Doing so results in an image of equal quality but a smaller memory footprint. For example, the aapt tool can convert a true-color PNG that does not require more than 256 colors to an 8-bit PNG with a color palette. The aapt tool can optimize the image resources placed in res/drawable/ with lossless compression during the build process.Try to choose other options for GIFs in your app when building for Android (Go edition) as GIFs take a lot of memory.Configure and use cache wisely when using a 3P lib like Glide for image rendering.Whether you need alpha values or not, try to fit your case accordingly. Memory footprint gets reduced to half when RGB_565 format is used but using lower bitmap quality comes with a price too. The ARGB_8888 format has 4 bytes/pixel consumption while RGB_565 has 2 bytes/pixel.This saved them a couple of MBs (per screen size/density). Check and only set the alpha channel for the bitmap for complex custom views used in the app.Decide on how often tests should run? What should be the optimal frequency for your app?.Try to invest in building a regression infrastructure to deal with such issues in early stages.Don’t allow the changes that fail the KPI goals unless the decision is to update the KPI targets. It is more difficult to debug and find sources of regressions or bugs than to not allow them to get into the codebase. That either runs for every change or in some frequency to identify regressions in KPIs. If not → identify the bottlenecks by looking at the individual breakdowns.Īfter optimizing a certain bottleneck go back and benchmark the metrics again to see if the KPI targets are met.
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