periphery VS bloaty

While I’m unsure I’ll be using Swift for the rest of my life, I’ll continue to work on my little tool to detect unused code for as long as I can. It’s my most popular open-source contribution, and it brings me joy knowing others find it useful.

https://github.com/peripheryapp/periphery

It is not that hard. Just generate constants from all assets and use https://github.com/peripheryapp/periphery to detect unused variables

I was wondering, do you usually use tool like periphery (https://github.com/peripheryapp/periphery), to ensure your release built app is optimized?

I also asked this here but I want to get it working ASAP so I was wondering if one of you got it working: https://github.com/peripheryapp/periphery/issues/502.

There is a nice Package: https://github.com/peripheryapp/periphery#how-to-use that can find dead code in a Project. You can install it via SPM or Homebrew or Pods. Is there a way to run the scan every time i build the Project on its own ?

ESP32s aren't really ‘lower level’ in the sense that anyone is likely to write assembly code for them (compared to, say, 8051 or PIC), other than maybe some driver author at Espressif. The big win from using RISC-V, other than name recognition, is mainstream compiler support (which is nothing to sneeze at, especially when it's largely funded by someone else).

When I worked on Matter¹, the Xtensa and RISC-V versions were basically fungible from the software point of view. (And really, so were other vendors' various ARMs.) We did find that Bloaty McBloatface² didn't support Xtensa, so I had to write an alternative.

¹ https://github.com/project-chip/connectedhomeip/

² https://github.com/google/bloaty

I’ve gotten good insight into what takes up space in binaries by profiling with Bloaty (https://github.com/google/bloaty). My last profiling session showed that clang’s ThinLTO was inlining too aggressively in some cases, causing functions that should be tiny to be 75 kB+.

I'm surprised they didn't go for the binary size analysis tools like

https://github.com/google/bloaty

Or goweight.

I was able to shave a few % off our app binary with Bloaty. It’s pretty hard to use but once you figure out how to make regular expressions to properly classify things from your codebase, you can really visually analyze what your binary is composed of.

Bloaty