But in last few days this one guy started adding support for the missing gcc warnings. I also found out that printf() warnings were added within last few months also. So it looks like clang is finally potentially usable! I still have to actually start developing with it, but it looks promising.
This picture shows how much better clang's error and warning handling is compared to gcc.
I also did a few benchmarks with Dovecot:
- Dovecot compiled about 10% faster with clang. Based on clang's web page I expected much more, but I guess it's better than nothing.. (I used configure --enable-optimizations, didn't change anything else)
- Dovecot ran about 7% faster when I/O wasn't the limit (SSD disk, fsync_disable=yes).
Here's how I tested the 7% speed improvement (Dovecot v2.0 hg, Maildir):
imaptest seed=123 secs=300 msgs=100 delete=10 expunge=10 logout=1
1)
gcc version 4.4.3 20100108 (prerelease) (Debian 4.4.2-9)
Logi List Stat Sele Fetc Fet2 Stor Dele Expu Appe Logo
100% 50% 50% 100% 100% 100% 50% 10% 10% 100% 1%
30% 5%
674 31545 31442 674 63169 90559 30029 5419 6332 19773 1348
646 31725 31640 646 63270 90160 29987 5403 6163 20224 1292
2)
clang version 1.5 (trunk 98979)
Target: x86_64-unknown-linux-gnu
Logi List Stat Sele Fetc Fet2 Stor Dele Expu Appe Logo
100% 50% 50% 100% 100% 100% 50% 10% 10% 100% 1%
30% 5%
693 33927 33765 693 68032 96951 32356 5691 6786 21034 1386
674 33990 34027 674 68018 97428 32101 5823 6863 21260 1348
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To test the 7% speed improvement in Dovecot when I/O wasn't a limiting factor, follow these steps: Set up Dovecot v2.0 with Maildir. Prepare the testing environment by using an SSD disk and setting fsync_disable=yes in the Dovecot configuration. Run a benchmark to establish a baseline performance measurement without modifications. Apply changes, such as using clang instead of gcc for compilation, and recompile Dovecot with clang and other optimizations enabled. Repeat testing and measure performance metrics under the same conditions used for the baseline. Compare results and compare performance metrics. Validate and iterate the results by comparing the percentage improvement in key metrics. Monitor system resource usage during testing to identify bottlenecks or limitations. This approach ensures that performance gains are accurately assessed and can guide future decisions regarding development tools and configurations. It is important to keep track of any other system changes or configurations that could impact performance and monitor system resource usage during testing to identify bottlenecks or limitations. abogado de bienes cerca de mí virginia
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