| commit | b0598497afde60146fe8480331c9f96e7a79475a | [log] [tgz] |
|---|---|---|
| author | Steven <sluong@cisco.com> | Wed Oct 24 21:15:45 2018 -0700 |
| committer | Dave Barach <dave@barachs.net> | Sun Dec 02 08:47:46 2018 -0500 |
| tree | a3d9f454195cb9317fceb29efe62f5b62de89dea | |
| parent | e7f61d1db511b9b09c7771c5851eaaf95a2fc7fe [diff] |
vppinfra: c11 safe string functions Add memcmp_s, strcmp_s, strncmp_s, strcpy_s, strncpy_s, strcat_s, strncat_s, strtok_s, strnlen_s, and strstr_s C11 safe string API. For migrating extant unsafe API, add also the corresponding macro version of each safe API, clib_memcmp, clib_strcmp, etc. In general, the benefits of the safe string APIs are to provide null pointer checks, add additional argument to specify the string length of the passed string rather than relying on the null terminated character, and src/dest overlap checking for the the string copy operations. The macro version of the API takes the same number of arguments as the unsafe API to provide easy migration. However, it does not usually provide the full aformentioned benefits. In some cases, it is necessary to move to the safe API rather than using the macro in order to avoid some unpredictable problems such as accessing memory beyond what it is intended due to the lack of the passed string length. dbarach: add a "make test" vector, and a doxygen file header cookie. Change-Id: I5cd79b8928dcf76a79bf3f0b8cbc1a8f24942f4c Signed-off-by: Steven <sluong@cisco.com> Signed-off-by: Dave Barach <dave@barachs.net>
The VPP platform is an extensible framework that provides out-of-the-box production quality switch/router functionality. It is the open source version of Cisco's Vector Packet Processing (VPP) technology: a high performance, packet-processing stack that can run on commodity CPUs.
The benefits of this implementation of VPP are its high performance, proven technology, its modularity and flexibility, and rich feature set.
For more information on VPP and its features please visit the FD.io website and What is VPP? pages.
Details of the changes leading up to this version of VPP can be found under @ref release_notes.
| Directory name | Description |
|---|---|
| build-data | Build metadata |
| build-root | Build output directory |
| doxygen | Documentation generator configuration |
| dpdk | DPDK patches and build infrastructure |
| @ref extras/libmemif | Client library for memif |
| @ref src/examples | VPP example code |
| @ref src/plugins | VPP bundled plugins directory |
| @ref src/svm | Shared virtual memory allocation library |
| src/tests | Standalone tests (not part of test harness) |
| src/vat | VPP API test program |
| @ref src/vlib | VPP application library |
| @ref src/vlibapi | VPP API library |
| @ref src/vlibmemory | VPP Memory management |
| @ref src/vnet | VPP networking |
| @ref src/vpp | VPP application |
| @ref src/vpp-api | VPP application API bindings |
| @ref src/vppinfra | VPP core library |
| @ref src/vpp/api | Not-yet-relocated API bindings |
| test | Unit tests and Python test harness |
In general anyone interested in building, developing or running VPP should consult the VPP wiki for more complete documentation.
In particular, readers are recommended to take a look at [Pulling, Building, Running, Hacking, Pushing](https://wiki.fd.io/view/VPP/Pulling,_Building,_Run ning,_Hacking_and_Pushing_VPP_Code) which provides extensive step-by-step coverage of the topic.
For the impatient, some salient information is distilled below.
To install system dependencies, build VPP and then install it, simply run the build script. This should be performed a non-privileged user with sudo access from the project base directory:
./extras/vagrant/build.sh
If you want a more fine-grained approach because you intend to do some development work, the Makefile in the root directory of the source tree provides several convenience shortcuts as make targets that may be of interest. To see the available targets run:
make
The directory extras/vagrant contains a VagrantFile and supporting scripts to bootstrap a working VPP inside a Vagrant-managed Virtual Machine. This VM can then be used to test concepts with VPP or as a development platform to extend VPP. Some obvious caveats apply when using a VM for VPP since its performance will never match that of bare metal; if your work is timing or performance sensitive, consider using bare metal in addition or instead of the VM.
For this to work you will need a working installation of Vagrant. Instructions for this can be found [on the Setting up Vagrant wiki page] (https://wiki.fd.io/view/DEV/Setting_Up_Vagrant).
Several modules provide documentation, see @subpage user_doc for more end-user-oriented information. Also see @subpage dev_doc for developer notes.
Visit the VPP wiki for details on more advanced building strategies and other development notes.
There is PyDoc generated documentation available for the VPP test framework. See @ref test_framework_doc for details.