Adding upstream version 6.1.76.upstream/6.1.76

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 180 insertions, 0 deletions

diff --git a/Documentation/dev-tools/testing-overview.rst b/Documentation/dev-tools/testing-overview.rst
new file mode 100644
index 000000000..0aaf6ea53
--- /dev/null
+++ b/Documentation/dev-tools/testing-overview.rst
@@ -0,0 +1,180 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+====================
+Kernel Testing Guide
+====================
+
+
+There are a number of different tools for testing the Linux kernel, so knowing
+when to use each of them can be a challenge. This document provides a rough
+overview of their differences, and how they fit together.
+
+
+Writing and Running Tests
+=========================
+
+The bulk of kernel tests are written using either the kselftest or KUnit
+frameworks. These both provide infrastructure to help make running tests and
+groups of tests easier, as well as providing helpers to aid in writing new
+tests.
+
+If you're looking to verify the behaviour of the Kernel — particularly specific
+parts of the kernel — then you'll want to use KUnit or kselftest.
+
+
+The Difference Between KUnit and kselftest
+------------------------------------------
+
+KUnit (Documentation/dev-tools/kunit/index.rst) is an entirely in-kernel system
+for "white box" testing: because test code is part of the kernel, it can access
+internal structures and functions which aren't exposed to userspace.
+
+KUnit tests therefore are best written against small, self-contained parts
+of the kernel, which can be tested in isolation. This aligns well with the
+concept of 'unit' testing.
+
+For example, a KUnit test might test an individual kernel function (or even a
+single codepath through a function, such as an error handling case), rather
+than a feature as a whole.
+
+This also makes KUnit tests very fast to build and run, allowing them to be
+run frequently as part of the development process.
+
+There is a KUnit test style guide which may give further pointers in
+Documentation/dev-tools/kunit/style.rst
+
+
+kselftest (Documentation/dev-tools/kselftest.rst), on the other hand, is
+largely implemented in userspace, and tests are normal userspace scripts or
+programs.
+
+This makes it easier to write more complicated tests, or tests which need to
+manipulate the overall system state more (e.g., spawning processes, etc.).
+However, it's not possible to call kernel functions directly from kselftest.
+This means that only kernel functionality which is exposed to userspace somehow
+(e.g. by a syscall, device, filesystem, etc.) can be tested with kselftest.  To
+work around this, some tests include a companion kernel module which exposes
+more information or functionality. If a test runs mostly or entirely within the
+kernel, however,  KUnit may be the more appropriate tool.
+
+kselftest is therefore suited well to tests of whole features, as these will
+expose an interface to userspace, which can be tested, but not implementation
+details. This aligns well with 'system' or 'end-to-end' testing.
+
+For example, all new system calls should be accompanied by kselftest tests.
+
+Code Coverage Tools
+===================
+
+The Linux Kernel supports two different code coverage measurement tools. These
+can be used to verify that a test is executing particular functions or lines
+of code. This is useful for determining how much of the kernel is being tested,
+and for finding corner-cases which are not covered by the appropriate test.
+
+Documentation/dev-tools/gcov.rst is GCC's coverage testing tool, which can be
+used with the kernel to get global or per-module coverage. Unlike KCOV, it
+does not record per-task coverage. Coverage data can be read from debugfs,
+and interpreted using the usual gcov tooling.
+
+Documentation/dev-tools/kcov.rst is a feature which can be built in to the
+kernel to allow capturing coverage on a per-task level. It's therefore useful
+for fuzzing and other situations where information about code executed during,
+for example, a single syscall is useful.
+
+
+Dynamic Analysis Tools
+======================
+
+The kernel also supports a number of dynamic analysis tools, which attempt to
+detect classes of issues when they occur in a running kernel. These typically
+each look for a different class of bugs, such as invalid memory accesses,
+concurrency issues such as data races, or other undefined behaviour like
+integer overflows.
+
+Some of these tools are listed below:
+
+* kmemleak detects possible memory leaks. See
+  Documentation/dev-tools/kmemleak.rst
+* KASAN detects invalid memory accesses such as out-of-bounds and
+  use-after-free errors. See Documentation/dev-tools/kasan.rst
+* UBSAN detects behaviour that is undefined by the C standard, like integer
+  overflows. See Documentation/dev-tools/ubsan.rst
+* KCSAN detects data races. See Documentation/dev-tools/kcsan.rst
+* KFENCE is a low-overhead detector of memory issues, which is much faster than
+  KASAN and can be used in production. See Documentation/dev-tools/kfence.rst
+* lockdep is a locking correctness validator. See
+  Documentation/locking/lockdep-design.rst
+* There are several other pieces of debug instrumentation in the kernel, many
+  of which can be found in lib/Kconfig.debug
+
+These tools tend to test the kernel as a whole, and do not "pass" like
+kselftest or KUnit tests. They can be combined with KUnit or kselftest by
+running tests on a kernel with these tools enabled: you can then be sure
+that none of these errors are occurring during the test.
+
+Some of these tools integrate with KUnit or kselftest and will
+automatically fail tests if an issue is detected.
+
+Static Analysis Tools
+=====================
+
+In addition to testing a running kernel, one can also analyze kernel source code
+directly (**at compile time**) using **static analysis** tools. The tools
+commonly used in the kernel allow one to inspect the whole source tree or just
+specific files within it. They make it easier to detect and fix problems during
+the development process.
+
+Sparse can help test the kernel by performing type-checking, lock checking,
+value range checking, in addition to reporting various errors and warnings while
+examining the code. See the Documentation/dev-tools/sparse.rst documentation
+page for details on how to use it.
+
+Smatch extends Sparse and provides additional checks for programming logic
+mistakes such as missing breaks in switch statements, unused return values on
+error checking, forgetting to set an error code in the return of an error path,
+etc. Smatch also has tests against more serious issues such as integer
+overflows, null pointer dereferences, and memory leaks. See the project page at
+http://smatch.sourceforge.net/.
+
+Coccinelle is another static analyzer at our disposal. Coccinelle is often used
+to aid refactoring and collateral evolution of source code, but it can also help
+to avoid certain bugs that occur in common code patterns. The types of tests
+available include API tests, tests for correct usage of kernel iterators, checks
+for the soundness of free operations, analysis of locking behavior, and further
+tests known to help keep consistent kernel usage. See the
+Documentation/dev-tools/coccinelle.rst documentation page for details.
+
+Beware, though, that static analysis tools suffer from **false positives**.
+Errors and warns need to be evaluated carefully before attempting to fix them.
+
+When to use Sparse and Smatch
+-----------------------------
+
+Sparse does type checking, such as verifying that annotated variables do not
+cause endianness bugs, detecting places that use ``__user`` pointers improperly,
+and analyzing the compatibility of symbol initializers.
+
+Smatch does flow analysis and, if allowed to build the function database, it
+also does cross function analysis. Smatch tries to answer questions like where
+is this buffer allocated? How big is it? Can this index be controlled by the
+user? Is this variable larger than that variable?
+
+It's generally easier to write checks in Smatch than it is to write checks in
+Sparse. Nevertheless, there are some overlaps between Sparse and Smatch checks.
+
+Strong points of Smatch and Coccinelle
+--------------------------------------
+
+Coccinelle is probably the easiest for writing checks. It works before the
+pre-processor so it's easier to check for bugs in macros using Coccinelle.
+Coccinelle also creates patches for you, which no other tool does.
+
+For example, with Coccinelle you can do a mass conversion from
+``kmalloc(x * size, GFP_KERNEL)`` to ``kmalloc_array(x, size, GFP_KERNEL)``, and
+that's really useful. If you just created a Smatch warning and try to push the
+work of converting on to the maintainers they would be annoyed. You'd have to
+argue about each warning if can really overflow or not.
+
+Coccinelle does no analysis of variable values, which is the strong point of
+Smatch. On the other hand, Coccinelle allows you to do simple things in a simple
+way.