GSPLIT DWARF FULL
GSPLIT DWARF CODE

Duplicate information gets removed, and the merged debug information is written to the generated binary. Note that the linker also needs to process all debug information contained in the object files. Although a smarter approach seems possible, in most build systems this means recreating these binaries from scratch.

All other binaries which are depending on binaries that were rebuilt must also be relinked.

All the contained objects need to be read again, even if unchanged, then processed by the linker, and the new binary must be written to disk.

The libraries or executables containing the changed source files need to be rebuilt.

Most of the time is spent linking the application. More recent versions are recommended, especially for gdb.Р”Р‡or an incremental build, only a few source files have to be recompiled. The versions below are the absolute minimum.

You should have a somewhat recent toolchain supporting split DWARF (introduced below) across the board.

But a large overhead here means your developers are already wasting time. Sometimes this is not easy to achieve, and if the redundant actions only take a short time it is tolerable. A repeated build without any changes should not perform any actions at all.

Your incremental build should be РІР‚СљminimalРІР‚Сњ: No unneeded steps should be performed when invoking the build.

You donРІР‚в„ўt have to switch to other tasks while the build runs, but can keep your focus on the problem at hand. The goal is to increase developer productivity: Shorter turnaround times allow for quicker iterations. In this article we will be discussing a great way of speeding up incremental builds which also benefits scratch makes. Compared to scripting languages, the turnaround time for making a change and testing it is quite long for C++. This is much less work than a scratch make, but since you are doing it many times a day, it is even more critical to get it fast. Such an incremental build compiles only a handful of source files and then links the libraries and the application.

GSPLIT DWARF FULL

You already have done a full build, then you make a small change to one file to fix a bug or do an enhancement, and you build and test it.

Compile clusters can speed things up by distributing the compile jobs across multiple machines. Therefore, each source file will take seconds to compile, and a large application can have thousands of source files.

GSPLIT DWARF CODE

To a large extent this is caused by the insufficient module concept of C++: Each source includes a lot of headers, so after preprocessing, there can be thousands or even millions of lines of C++ code the compiler has to process. We can distinguish these two scenarios:Р”Р„fter pulling in the latest changes from upstream, or after a major refactoring that affects central headers, a lot of source files need to be rebuilt.

Large- and medium-sized C++ projects often suffer from long build times.

Gsplit-dwarf