Pacemaker Development

Working with the Pacemaker Code Base

Abstract

This document has guidelines and tips for developers interested in editing Pacemaker source code and submitting changes for inclusion in the project. Start with the FAQ; the rest is optional detail.

Table of Contents

1. Frequently Asked Questions

Q:Who is this document intended for?
A:Anyone who wishes to read and/or edit the Pacemaker source code. Casual contributors should feel free to read just this FAQ, and consult other chapters as needed.

Q:Where is the source code for Pacemaker?
A:The source code for Pacemaker is kept on GitHub, as are all software projects under the ClusterLabs umbrella. Pacemaker uses Git for source code management. If you are a Git newbie, the gittutorial(7) man page is an excellent starting point. If you’re familiar with using Git from the command line, you can create a local copy of the Pacemaker source code with: git clone https://github.com/ClusterLabs/pacemaker.git

Q:

What are the different Git branches and repositories used for?

A:
  • The master branch is the primary branch used for development.
  • The 2.1 branch is the current release branch. Normally, it does not receive any changes, but during the release cycle for a new release, it will contain release candidates. During the release cycle, certain bug fixes will go to the 2.1 branch first (and be pulled into master later).
  • The 2.0 branch, 1.1 branch, and separate 1.0 repository are frozen snapshots of earlier release series, no longer being developed.
  • Messages will be posted to the developers@ClusterLabs.org mailing list during the release cycle, with instructions about which branches to use when submitting requests.

Q:How do I build from the source code?
A:See INSTALL.md in the main checkout directory.

Q:What coding style should I follow?
A:You’ll be mostly fine if you simply follow the example of existing code. When unsure, see the relevant chapter of this document for language-specific recommendations. Pacemaker has grown and evolved organically over many years, so you will see much code that doesn’t conform to the current guidelines. We discourage making changes solely to bring code into conformance, as any change requires developer time for review and opens the possibility of adding bugs. However, new code should follow the guidelines, and it is fine to bring lines of older code into conformance when modifying that code for other reasons.

Q:

How should I format my Git commit messages?

A:

An example is “Feature: scheduler: wobble the frizzle better”.

  • The first part is the type of change, used to automatically generate the change log for the next release. Commit messages with the following will be included in the change log:

    • Feature for new features
    • Fix for bug fixes (Bug or High also work)
    • API for changes to the public API

    Everything else will not automatically be in the change log, and so don’t really matter, but types commonly used include:

    • Log for changes to log messages or handling
    • Doc for changes to documentation or comments
    • Test for changes in CTS and regression tests
    • Low, Med, or Mid for bug fixes not significant enough for a change log entry
    • Refactor for refactoring-only code changes
    • Build for build process changes
  • The next part is the name of the component(s) being changed, for example, controller or libcrmcommon (it’s more free-form, so don’t sweat getting it exact).

  • The rest briefly describes the change. The git project recommends the entire summary line stay under 50 characters, but more is fine if needed for clarity.

  • Except for the most simple and obvious of changes, the summary should be followed by a blank line and a longer explanation of why the change was made.


Q:How can I test my changes?
A:The source repository has some unit tests for simple functions, though this is a recent effort without much coverage yet. Pacemaker’s Cluster Test Suite (CTS) has regression tests for most major components; these will automatically be run for any pull requests submitted through GitHub, and are sufficient for most changes. Additionally, CTS has a lab component that can be used to set up a test cluster and run a wide variety of complex tests, for testing major changes. See cts/README.md in the source repository for details.

Q:What is Pacemaker’s license?
A:Except where noted otherwise in the file itself, the source code for all Pacemaker programs is licensed under version 2 or later of the GNU General Public License (GPLv2+), its headers and libraries under version 2.1 or later of the less restrictive GNU Lesser General Public License (LGPLv2.1+), its documentation under version 4.0 or later of the Creative Commons Attribution-ShareAlike International Public License (CC-BY-SA-4.0), and its init scripts under the Revised BSD license. If you find any deviations from this policy, or wish to inquire about alternate licensing arrangements, please e-mail the developers@ClusterLabs.org mailing list. Licensing issues are also discussed on the ClusterLabs wiki.

Q:How can I contribute my changes to the project?
A:Contributions of bug fixes or new features are very much appreciated! Patches can be submitted as pull requests via GitHub (the preferred method, due to its excellent features), or e-mailed to the developers@ClusterLabs.org mailing list as an attachment in a format Git can import. Authors may only submit changes that they have the right to submit under the open source license indicated in the affected files.

Q:What if I still have questions?
A:Ask on the developers@ClusterLabs.org mailing list for development-related questions, or on the users@ClusterLabs.org mailing list for general questions about using Pacemaker. Developers often also hang out on the [ClusterLabs IRC channel](https://wiki.clusterlabs.org/wiki/ClusterLabs_IRC_channel).

2. General Guidelines for All Languages

3. Python Coding Guidelines

3.1. Python Boilerplate

If a Python file is meant to be executed (as opposed to imported), it should have a .in extension, and its first line should be:

#!@PYTHON@

which will be replaced with the appropriate python executable when Pacemaker is built. To make that happen, add an entry to CONFIG_FILES_EXEC() in configure.ac, and add the file name without .in to .gitignore (see existing examples).

After the above line if any, every Python file should start like this:

""" <BRIEF-DESCRIPTION>
"""

__copyright__ = "Copyright <YYYY[-YYYY]> the Pacemaker project contributors"
__license__ = "<LICENSE> WITHOUT ANY WARRANTY"

<BRIEF-DESCRIPTION> is obviously a brief description of the file’s purpose. The string may contain any other information typically used in a Python file docstring.

<LICENSE> should follow the policy set forth in the COPYING file, generally one of “GNU General Public License version 2 or later (GPLv2+)” or “GNU Lesser General Public License version 2.1 or later (LGPLv2.1+)”.

3.2. Python Version Compatibility

Pacemaker targets compatibility with Python 3.4 and later.

Do not use features not available in all targeted Python versions. An example is the subprocess.run() function.

3.3. Formatting Python Code

  • Indentation must be 4 spaces, no tabs.
  • Do not leave trailing whitespace.
  • Lines should be no longer than 80 characters unless limiting line length significantly impacts readability. For Python, this limitation is flexible since breaking a line often impacts readability, but definitely keep it under 120 characters.
  • Where not conflicting with this style guide, it is recommended (but not required) to follow PEP 8.
  • It is recommended (but not required) to format Python code such that pylint --disable=line-too-long,too-many-lines,too-many-instance-attributes,too-many-arguments,too-many-statements produces minimal complaints (even better if you don’t need to disable all those checks).

4. C Coding Guidelines

Pacemaker is a large project accepting contributions from developers with a wide range of skill levels and organizational affiliations, and maintained by multiple people over long periods of time. Following consistent guidelines makes reading, writing, and reviewing code easier, and helps avoid common mistakes.

Some existing Pacemaker code does not follow these guidelines, for historical reasons and API backward compatibility, but new code should.

4.1. Code Organization

Pacemaker’s C code is organized as follows:

Directory Contents
daemons the Pacemaker daemons (pacemakerd, pacemaker-based, etc.)
include header files for library APIs
lib libraries
tools command-line tools

Source file names should be unique across the entire project, to allow for individual tracing via PCMK_trace_files.

4.2. Pacemaker Libraries

Library Symbol prefix Source location API Headers Description
libcib cib lib/cib
include/crm/cib.h
include/crm/cib/*

API for pacemaker-based IPC and the CIB

libcrmcluster pcmk lib/cluster
include/crm/cluster.h
include/crm/cluster/*

Abstract interface to underlying cluster layer

libcrmcommon pcmk lib/common
include/crm/common/*
some of include/crm/*

Everything else

libcrmservice svc lib/services
include/crm/services.h

Abstract interface to supported resource types (OCF, LSB, etc.)

liblrmd lrmd lib/lrmd
include/crm/lrmd*.h

API for pacemaker-execd IPC

libpacemaker pcmk lib/pacemaker
include/pacemaker*.h
include/pcmki/*

High-level APIs equivalent to command-line tool capabilities (and high-level internal APIs)

libpe_rules pe lib/pengine
include/crm/pengine/*

Scheduler functionality related to evaluating rules

libpe_status pe lib/pengine
include/crm/pengine/*

Low-level scheduler functionality

libstonithd stonith lib/fencing
include/crm/stonith-ng.h
include/crm/fencing/*

API for pacemaker-fenced IPC

4.2.1. Public versus Internal APIs

Pacemaker libraries have both internal and public APIs. Internal APIs are those used only within Pacemaker; public APIs are those offered (via header files and documentation) for external code to use.

Generic functionality needed by Pacemaker itself, such as string processing or XML processing, should remain internal, while functions providing useful high-level access to Pacemaker capabilities should be public. When in doubt, keep APIs internal, because it’s easier to expose a previously internal API than hide a previously public API.

Internal APIs can be changed as needed.

The public API/ABI should maintain a degree of stability so that external applications using it do not need to be rewritten or rebuilt frequently. Many OSes/distributions avoid breaking API/ABI compatibility within a major release, so if Pacemaker breaks compatibility, that significantly delays when OSes can package the new version. Therefore, changes to public APIs should be backward-compatible (as detailed throughout this chapter), unless we are doing a (rare) release where we specifically intend to break compatibility.

External applications known to use Pacemaker’s public C API include sbd and dlm_controld.

4.2.2. API Documentation

Pacemaker uses Doxygen to automatically generate its online API documentation, so all public API (header files, functions, structs, enums, etc.) should be documented with Doxygen comment blocks. Other code may be documented in the same way if desired, with an \internal tag in the Doxygen comment.

Simple example of an internal function with a Doxygen comment block:

/*!
 * \internal
 * \brief Return string length plus 1
 *
 * Return the number of characters in a given string, plus one.
 *
 * \param[in] s  A string (must not be NULL)
 *
 * \return The length of \p s plus 1.
 */
static int
f(const char *s)
{
   return strlen(s) + 1;
}
4.2.3. API Header File Naming
  • Internal API headers should be named ending in _internal.h, in the same location as public headers, with the exception of libpacemaker, which for historical reasons keeps internal headers in include/pcmki/pcmki_*.h).
  • If a library needs to share symbols just within the library, header files for these should be named ending in _private.h and located in the library source directory (not include). Such functions should be declared as G_GNUC_INTERNAL, to aid compiler efficiency (glib defines this symbol appropriately for the compiler).

Header files that are not library API are located in the same locations as other source code.

4.2.4. API Symbol Naming

Exposed API symbols (non-static function names, struct and typedef names in header files, etc.) must begin with the prefix appropriate to the library (shown in the table at the beginning of this section). This reduces the chance of naming collisions when external software links against the library.

The prefix is usually lowercase but may be all-caps for some defined constants and macros.

Public API symbols should follow the library prefix with a single underbar (for example, pcmk_something), and internal API symbols with a double underbar (for example, pcmk__other_thing).

File-local symbols (such as static functions) and non-library code do not require a prefix, though a unique prefix indicating an executable (controld, crm_mon, etc.) can be helpful to indicate symbols shared between multiple source files for the executable.

4.2.5. Public API Deprecation

Public APIs may not be removed in most Pacemaker releases, but they may be deprecated.

When a public API is deprecated, it is moved to a header whose name ends in compat.h. The original header includes the compatibility header only if the PCMK_ALLOW_DEPRECATED symbol is undefined or defined to 1. This allows external code to continue using the deprecated APIs, but internal code is prevented from using them because the crm_internal.h header defines the symbol to 0.

4.3. C Boilerplate

Every C file should start with a short copyright and license notice:

/*
 * Copyright <YYYY[-YYYY]> the Pacemaker project contributors
 *
 * The version control history for this file may have further details.
 *
 * This source code is licensed under <LICENSE> WITHOUT ANY WARRANTY.
 */

<LICENSE> should follow the policy set forth in the COPYING file, generally one of “GNU General Public License version 2 or later (GPLv2+)” or “GNU Lesser General Public License version 2.1 or later (LGPLv2.1+)”.

Header files should additionally protect against multiple inclusion by defining a unique symbol of the form PCMK__<capitalized_header_name>__H. For example:

#ifndef PCMK__MY_HEADER__H
#  define PCMK__MY_HEADER__H

// header code here

#endif // PCMK__MY_HEADER__H

Public API header files should additionally declare “C” compatibility for inclusion by C++, and give a Doxygen file description. For example:

#ifdef __cplusplus
extern "C" {
#endif

/*!
 * \file
 * \brief My brief description here
 * \ingroup core
 */

// header code here

#ifdef __cplusplus
}
#endif

4.4. Line Formatting

  • Indentation must be 4 spaces, no tabs.
  • Do not leave trailing whitespace.
  • Lines should be no longer than 80 characters unless limiting line length hurts readability.

4.5. Comments

/* Single-line comments may look like this */

// ... or this

/* Multi-line comments should start immediately after the comment opening.
 * Subsequent lines should start with an aligned asterisk. The comment
 * closing should be aligned and on a line by itself.
 */

4.6. Variables

  • Pointers:
/* (1) The asterisk goes by the variable name, not the type;
 * (2) Avoid leaving pointers uninitialized, to lessen the impact of
 *     use-before-assignment bugs
 */
char *my_string = NULL;

// Use space before asterisk and after closing parenthesis in a cast
char *foo = (char *) bar;
  • Global variables should be avoided in libraries when possible. State information should instead be passed as function arguments (often as a structure). This is not for thread safety – Pacemaker’s use of forking ensures it will never be threaded – but it does minimize overhead, improve readability, and avoid obscure side effects.
  • Time intervals are sometimes represented in Pacemaker code as user-defined text specifications (for example, “10s”), other times as an integer number of seconds or milliseconds, and still other times as a string representation of an integer number. Variables for these should be named with an indication of which is being used (for example, use interval_spec, interval_ms, or interval_ms_s instead of interval).

4.7. Operators

// Operators have spaces on both sides
x = a;

/* (1) Do not rely on operator precedence; use parentheses when mixing
 *     operators with different priority, for readability.
 * (2) No space is used after an opening parenthesis or before a closing
 *     parenthesis.
 */
x = a + b - (c * d);

4.8. Control Statements (if, else, while, for, switch)

/*
 * (1) The control keyword is followed by a space, a left parenthesis
 *     without a space, the condition, a right parenthesis, a space, and the
 *     opening bracket on the same line.
 * (2) Always use braces around control statement blocks, even if they only
 *     contain one line. This makes code review diffs smaller if a line gets
 *     added in the future, and avoids the chance of bad indenting making a
 *     line incorrectly appear to be part of the block.
 * (3) The closing bracket is on a line by itself.
 */
if (v < 0) {
    return 0;
}

/* "else" and "else if" are on the same line with the previous ending brace
 * and next opening brace, separated by a space. Blank lines may be used
 * between blocks to help readability.
 */
if (v > 0) {
    return 0;

} else if (a == 0) {
    return 1;

} else {
    return 2;
}

/* Do not use assignments in conditions. This ensures that the developer's
 * intent is always clear, makes code reviews easier, and reduces the chance
 * of using assignment where comparison is intended.
 */
// Do this ...
a = f();
if (a) {
    return 0;
}
// ... NOT this
if (a = f()) {
    return 0;
}

/* It helps readability to use the "!" operator only in boolean
 * comparisons, and explicitly compare numeric values against 0,
 * pointers against NULL, etc. This helps remind the reader of the
 * type being compared.
 */
int i = 0;
char *s = NULL;
bool cond = false;

if (!cond) {
    return 0;
}
if (i == 0) {
    return 0;
}
if (s == NULL) {
    return 0;
}

/* In a "switch" statement, indent "case" one level, and indent the body of
 * each "case" another level.
 */
switch (expression) {
    case 0:
        command1;
        break;
    case 1:
        command2;
        break;
    default:
        command3;
        break;
}

4.9. Structures

Changes to structures defined in public API headers (adding or removing members, or changing member types) are generally not possible without breaking API compatibility. However, there are exceptions:

  • Public API structures can be designed such that they can be allocated only via API functions, not declared directly or allocated with standard memory functions using sizeof.
    • This can be enforced simply by documentating the limitation, in which case new struct members can be added to the end of the structure without breaking compatibility.
    • Alternatively, the structure definition can be kept in an internal header, with only a pointer type definition kept in a public header, in which case the structure definition can be changed however needed.

4.10. Enumerations

  • Enumerations should not have a typedef, and do not require any naming convention beyond what applies to all exposed symbols.
  • New values should usually be added to the end of public API enumerations, because the compiler will define the values to 0, 1, etc., in the order given, and inserting a value in the middle would change the numerical values of all later values, breaking code compiled with the old values. However, if enum numerical values are explicitly specified rather than left to the compiler, new values can be added anywhere.
  • When defining constant integer values, enum should be preferred over #define or const when possible. This allows type checking without consuming memory.
4.10.1. Flag groups

Pacemaker often uses flag groups (also called bit fields or bitmasks) for a collection of boolean options (flags/bits).

This is more efficient for storage and manipulation than individual booleans, but its main advantage is when used in public APIs, because using another bit in a bitmask is backward compatible, whereas adding a new function argument (or sometimes even a structure member) is not.

#include <stdint.h>

/* (1) Define an enumeration to name the individual flags, for readability.
 *     An enumeration is preferred to a series of "#define" constants
 *     because it is typed, and logically groups the related names.
 * (2) Define the values using left-shifting, which is more readable and
 *     less error-prone than hexadecimal literals (0x0001, 0x0002, 0x0004,
 *     etc.).
 * (3) Using a comma after the last entry makes diffs smaller for reviewing
 *     if a new value needs to be added or removed later.
 */
enum pcmk__some_bitmask_type {
    pcmk__some_value    = (1 << 0),
    pcmk__other_value   = (1 << 1),
    pcmk__another_value = (1 << 2),
};

/* The flag group itself should be an unsigned type from stdint.h (not
 * the enum type, since it will be a mask of the enum values and not just
 * one of them). uint32_t is the most common, since we rarely need more than
 * 32 flags, but a smaller or larger type could be appropriate in some
 * cases.
 */
uint32_t flags = pcmk__some_value|pcmk__other_value;

/* If the values will be used only with uint64_t, define them accordingly,
 * to make compilers happier.
 */
enum pcmk__something_else {
    pcmk__whatever    = (UINT64_C(1) << 0),
};

We have convenience functions for checking flags (see pcmk_any_flags_set(), pcmk_all_flags_set(), and pcmk_is_set()) as well as setting and clearing them (see pcmk__set_flags_as() and pcmk__clear_flags_as(), usually used via wrapper macros defined for specific flag groups). These convenience functions should be preferred to direct bitwise arithmetic, for readability and logging consistency.

4.11. Booleans

4.11.1. Boolean Types

Booleans in C can be represented by an integer type, bool, or gboolean.

Integers are sometimes useful for storing booleans when they must be converted to and from a string, such as an XML attribute value (for which crm_element_value_int() can be used). Integer booleans use 0 for false and nonzero (usually 1) for true.

gboolean should be used with glib APIs that specify it. gboolean should always be used with glib’s TRUE and FALSE constants.

Otherwise, bool should be preferred. bool should be used with the true and false constants from the stdbool.h header.

4.11.2. Testing Booleans

Do not use equality operators when testing booleans. For example:

// Do this
if (bool1) {
    fn();
}
if (!bool2) {
    fn2();
}

// Not this
if (bool1 == true) {
    fn();
}
if (bool2 == false) {
    fn2();
}

// Otherwise there's no logical end ...
if ((bool1 == false) == true) {
    fn();
}

Conversely, equality operators should be used with non-boolean variables, even when just testing zero or nonzero:

int var1 = fn();

// Prefer this, because it gives a hint to the type when reading it
if (var1 == 0) {
    fn2();
}

// Not this, because a reader could mistakenly assume it is a boolean
if (!var1) {
    fn2();
}

4.12. Functions

Function names should be unique across the entire project, to allow for individual tracing via PCMK_trace_functions, and make it easier to search code and follow detail logs.

4.12.1. Function Definitions
/*
 * (1) The return type goes on its own line
 * (2) The opening brace goes by itself on a line
 * (3) Use "const" with pointer arguments whenever appropriate, to allow the
 *     function to be used by more callers.
 */
int
my_func1(const char *s)
{
    return 0;
}

/* Functions with no arguments must explicitly list them as void,
 * for compatibility with strict compilers
 */
int
my_func2(void)
{
    return 0;
}

/*
 * (1) For functions with enough arguments that they must break to the next
 *     line, align arguments with the first argument.
 * (2) When a function argument is a function itself, use the pointer form.
 * (3) Declare functions and file-global variables as ``static`` whenever
 *     appropriate. This gains a slight efficiency in shared libraries, and
 *     helps the reader know that it is not used outside the one file.
 */
static int
my_func3(int bar, const char *a, const char *b, const char *c,
         void (*callback)())
{
    return 0;
}
4.12.2. Return Values

Functions that need to indicate success or failure should follow one of the following guidelines. More details, including functions for using them in user messages and converting from one to another, can be found in include/crm/common/results.h.

  • A standard Pacemaker return code is one of the pcmk_rc_* enum values or a system errno code, as an int.
  • crm_exit_t (the CRM_EX_* enum values) is a system-independent code suitable for the exit status of a process, or for interchange between nodes.
  • Other special-purpose status codes exist, such as enum ocf_exitcode for the possible exit statuses of OCF resource agents (along with some Pacemaker-specific extensions). It is usually obvious when the context calls for such.
  • Some older Pacemaker APIs use the now-deprecated “legacy” return values of pcmk_ok or the positive or negative value of one of the pcmk_err_* constants or system errno codes.
  • Functions registered with external libraries (as callbacks for example) should use the appropriate signature defined by those libraries, rather than follow Pacemaker guidelines.

Of course, functions may have return values that aren’t success/failure indicators, such as a pointer, integer count, or bool.

4.12.3. Public API Functions

Unless we are doing a (rare) release where we break public API compatibility, new public API functions can be added, but existing function signatures (return type, name, and argument types) should not be changed. To work around this, an existing function can become a wrapper for a new function.

4.13. Memory Management

  • Always use calloc() rather than malloc(). It has no additional cost on modern operating systems, and reduces the severity and security risks of uninitialized memory usage bugs.
  • Ensure that all dynamically allocated memory is freed when no longer needed, and not used after it is freed. This can be challenging in the more event-driven, callback-oriented sections of code.
  • Free dynamically allocated memory using the free function corresponding to how it was allocated. For example, use free() with calloc(), and g_free() with most glib functions that allocate objects.

4.14. Logging and Output

4.14.1. Logging Vs. Output

Log messages and output messages are logically similar but distinct. Oversimplifying a bit, daemons log, and tools output.

Log messages are intended to help with troubleshooting and debugging. They may have a high level of technical detail, and are usually filtered by severity – for example, the system log by default gets messages of notice level and higher.

Output is intended to let the user know what a tool is doing, and is generally terser and less technical, and may even be parsed by scripts. Output might have “verbose” and “quiet” modes, but it is not filtered by severity.

4.14.2. Common Guidelines for All Messages
  • When format strings are used for derived data types whose implementation may vary across platforms (pid_t, time_t, etc.), the safest approach is to use %lld in the format string, and cast the value to long long.
  • Do not rely on %s handling NULL values properly. While the standard library functions might, not all Pacemaker API using them does, and it’s safest to get in the habit of always ensuring format values are non-NULL. For debug and trace messages, the crm_str() macro is sufficient and will map NULL to the string “<null>”, but for other messages an understandable string appropriate to the context should be used when the value is NULL.
  • The convenience macros pcmk__plural_s() and pcmk__plural_alt() are handy when logging a word that may be singular or plural.
4.14.3. Logging

Pacemaker uses libqb for logging, but wraps it with a higher level of functionality (see include/crm/common/logging*h).

A few macros crm_err(), crm_warn(), etc. do most of the heavy lifting.

By default, Pacemaker sends logs at notice level and higher to the system log, and logs at info level and higher to the detail log (typically /var/log/pacemaker/pacemaker.log). The intent is that most users will only ever need the system log, but for deeper troubleshooting and developer debugging, the detail log may be helpful, at the cost of being more technical and difficult to follow.

The same message can have more detail in the detail log than in the system log, using libqb’s “extended logging” feature:

/* The following will log a simple message in the system log, like:

       warning: Action failed: Node not found

   with extra detail in the detail log, like:

       warning: Action failed: Node not found | rc=-1005 id=hgjjg-51006
*/
crm_warn("Action failed: %s " CRM_XS " rc=%d id=%s",
         pcmk_rc_str(rc), rc, id);
4.14.4. Output

Pacemaker has a somewhat complicated system for tool output. The main benefit is that the user can select the output format with the --output-as option (usually “text” for human-friendly output or “xml” for reliably script-parsable output, though crm_mon additionally supports “console” and “html”).

A custom message can be defined with a unique string identifier, plus implementation functions for each supported format. The caller invokes the message using the identifier. The user selects the output format via --output-as, and the output code automatically calls the appropriate implementation function.

The interface (most importantly pcmk__output_t) is declared in include/crm/common/output*h. See the API comments and existing tools for examples.

4.15. String Handling

4.15.1. Define Constants for Magic Strings

A “magic” string is one used for control purposes rather than human reading, and which must be exactly the same every time it is used. Examples would be configuration option names, XML attribute names, or environment variable names.

These should always be defined constants, rather than using the string literal everywhere. If someone mistypes a defined constant, the code won’t compile, but if they mistype a literal, it could go unnoticed until a user runs into a problem.

4.15.2. Library Functions

Pacemaker’s libcrmcommon has a large number of functions to assist in string handling. The most commonly used ones are:

  • pcmk__str_eq() tests string equality (similar to strcmp()), but can handle NULL, and takes options for case-insensitive, whether NULL should be considered a match, etc.
  • crm_strdup_printf() takes printf()-style arguments and creates a string from them (dynamically allocated, so it must be freed with free()). It asserts on memory failure, so the return value is always non-NULL.

String handling functions should almost always be internal API, since Pacemaker isn’t intended to be used as a general-purpose library. Most are declared in include/crm/common/strings_internal.h. util.h has some older ones that are public API (for now, but will eventually be made internal).

4.15.3. char*, gchar*, and GString

When using dynamically allocated strings, be careful to always use the appropriate free function.

  • char* strings allocated with something like calloc() must be freed with free(). Most Pacemaker library functions that allocate strings use this implementation.
  • glib functions often use gchar* instead, which must be freed with g_free().
  • Occasionally, it’s convenient to use glib’s flexible GString* type, which must be freed with g_string_free().

4.16. Regular Expressions

  • Use REG_NOSUB with regcomp() whenever possible, for efficiency.
  • Be sure to use regfree() appropriately.

4.17. Makefiles

Pacemaker uses automake for building, so the Makefile.am in each directory should be edited rather than Makefile.in or Makefile, which are automatically generated.

  • Public API headers are installed (by adding them to a HEADERS variable in Makefile.am), but internal API headers are not (by adding them to noinst_HEADERS).

4.18. vim Settings

Developers who use vim to edit source code can add the following settings to their ~/.vimrc file to follow Pacemaker C coding guidelines:

" follow Pacemaker coding guidelines when editing C source code files
filetype plugin indent on
au FileType c   setlocal expandtab tabstop=4 softtabstop=4 shiftwidth=4 textwidth=80
autocmd BufNewFile,BufRead *.h set filetype=c
let c_space_errors = 1

5. Coding Particular Pacemaker Components

The Pacemaker code can be intricate and difficult to follow. This chapter has some high-level descriptions of how individual components work.

5.1. Fencer

pacemaker-fenced is the Pacemaker daemon that handles fencing requests. In the broadest terms, fencing works like this:

  1. The initiator (an external program such as stonith_admin, or the cluster itself via the controller) asks the local fencer, “Hey, could you please fence this node?”
  2. The local fencer asks all the fencers in the cluster (including itself), “Hey, what fencing devices do you have access to that can fence this node?”
  3. Each fencer in the cluster replies with a list of available devices that it knows about.
  4. Once the original fencer gets all the replies, it asks the most appropriate fencer peer to actually carry out the fencing. It may send out more than one such request if the target node must be fenced with multiple devices.
  5. The chosen fencer(s) call the appropriate fencing resource agent(s) to do the fencing, then reply to the original fencer with the result.
  6. The original fencer broadcasts the result to all fencers.
  7. Each fencer sends the result to each of its local clients (including, at some point, the initiator).

A more detailed description follows.

5.1.1. Initiating a fencing request

A fencing request can be initiated by the cluster or externally, using the libstonithd API.

  • The cluster always initiates fencing via daemons/controld/controld_fencing.c:te_fence_node() (which calls the fence() API method). This occurs when a transition graph synapse contains a CRM_OP_FENCE XML operation.
  • The main external clients are stonith_admin and cts-fence-helper. The DLM project also uses Pacemaker for fencing.

Highlights of the fencing API:

  • stonith_api_new() creates and returns a new stonith_t object, whose cmds member has methods for connect, disconnect, fence, etc.
  • the fence() method creates and sends a STONITH_OP_FENCE XML request with the desired action and target node. Callers do not have to choose or even have any knowledge about particular fencing devices.
5.1.2. Fencing queries

The function calls for a fencing request go something like this:

The local fencer receives the client’s request via an IPC or messaging layer callback, which calls

  • stonith_command(), which (for requests) calls
    • handle_request(), which (for STONITH_OP_FENCE from a client) calls
      • initiate_remote_stonith_op(), which creates a STONITH_OP_QUERY XML request with the target, desired action, timeout, etc. then broadcasts the operation to the cluster group (i.e. all fencer instances) and starts a timer. The query is broadcast because (1) location constraints might prevent the local node from accessing the stonith device directly, and (2) even if the local node does have direct access, another node might be preferred to carry out the fencing.

Each fencer receives the original fencer’s STONITH_OP_QUERY broadcast request via IPC or messaging layer callback, which calls:

  • stonith_command(), which (for requests) calls

    • handle_request(), which (for STONITH_OP_QUERY from a peer) calls
    • stonith_query(), which calls
      • get_capable_devices() with stonith_query_capable_device_db() to add device information to an XML reply and send it. (A message is considered a reply if it contains T_STONITH_REPLY, which is only set by fencer peers, not clients.)

The original fencer receives all peers’ STONITH_OP_QUERY replies via IPC or messaging layer callback, which calls:

  • stonith_command(), which (for replies) calls
    • handle_reply() which (for STONITH_OP_QUERY) calls
      • process_remote_stonith_query(), which allocates a new query result structure, parses device information into it, and adds it to the operation object. It increments the number of replies received for this operation, and compares it against the expected number of replies (i.e. the number of active peers), and if this is the last expected reply, calls
        • call_remote_stonith(), which calculates the timeout and sends STONITH_OP_FENCE request(s) to carry out the fencing. If the target node has a fencing “topology” (which allows specifications such as “this node can be fenced either with device A, or devices B and C in combination”), it will choose the device(s), and send out as many requests as needed. If it chooses a device, it will choose the peer; a peer is preferred if it has “verified” access to the desired device, meaning that it has the device “running” on it and thus has a monitor operation ensuring reachability.
5.1.3. Fencing operations

Each STONITH_OP_FENCE request goes something like this:

The chosen peer fencer receives the STONITH_OP_FENCE request via IPC or messaging layer callback, which calls:

  • stonith_command(), which (for requests) calls
    • handle_request(), which (for STONITH_OP_FENCE from a peer) calls
      • stonith_fence(), which calls
        • schedule_stonith_command() (using supplied device if F_STONITH_DEVICE was set, otherwise the highest-priority capable device obtained via get_capable_devices() with stonith_fence_get_devices_cb()), which adds the operation to the device’s pending operations list and triggers processing.

The chosen peer fencer’s mainloop is triggered and calls

  • stonith_device_dispatch(), which calls
    • stonith_device_execute(), which pops off the next item from the device’s pending operations list. If acting as the (internally implemented) watchdog agent, it panics the node, otherwise it calls
      • stonith_action_create() and stonith_action_execute_async() to call the fencing agent.

The chosen peer fencer’s mainloop is triggered again once the fencing agent returns, and calls

  • stonith_action_async_done() which adds the results to an action object then calls its
    • done callback (st_child_done()), which calls schedule_stonith_command() for a new device if there are further required actions to execute or if the original action failed, then builds and sends an XML reply to the original fencer (via stonith_send_async_reply()), then checks whether any pending actions are the same as the one just executed and merges them if so.
5.1.4. Fencing replies

The original fencer receives the STONITH_OP_FENCE reply via IPC or messaging layer callback, which calls:

  • stonith_command(), which (for replies) calls

    • handle_reply(), which calls

      • process_remote_stonith_exec(), which calls either call_remote_stonith() (to retry a failed operation, or try the next

        device in a topology is appropriate, which issues a new

        STONITH_OP_FENCE request, proceeding as before) or remote_op_done() (if the operation is definitively failed or successful).

        • remote_op_done() broadcasts the result to all peers.

Finally, all peers receive the broadcast result and call

  • remote_op_done(), which sends the result to all local clients.

5.2. Scheduler

pacemaker-schedulerd is the Pacemaker daemon that runs the Pacemaker scheduler for the controller, but “the scheduler” in general refers to related library code in libpe_status and libpe_rules (lib/pengine/*.c), and some of libpacemaker (lib/pacemaker/pcmk_sched_*.c).

The purpose of the scheduler is to take a CIB as input and generate a transition graph (list of actions that need to be taken) as output.

The controller invokes the scheduler by contacting the scheduler daemon via local IPC. Tools such as crm_simulate, crm_mon, and crm_resource can also invoke the scheduler, but do so by calling the library functions directly. This allows them to run using a CIB_file without the cluster needing to be active.

The main entry point for the scheduler code is lib/pacemaker/pcmk_sched_messages.c:pcmk__schedule_actions(). It sets defaults and calls a bunch of “stage N” functions. Yes, there is a stage 0 and no stage 1. :) The code has evolved over time to where splitting the stages up differently and renumbering them would make sense.

  • stage0() “unpacks” most of the CIB XML into data structures, and determines the current cluster status. It also creates implicit location constraints for the node health feature.
  • stage2() applies factors that make resources prefer certain nodes (such as shutdown locks, location constraints, and stickiness).
  • stage3() creates internal constraints (such as the implicit ordering for group members, or start actions being implicitly ordered before promote actions).
  • stage4() “checks actions”, which means processing resource history entries in the CIB status section. This is used to decide whether certain actions need to be done, such as deleting orphan resources, forcing a restart when a resource definition changes, etc.
  • stage5() allocates resources to nodes and creates actions (which might or might not end up in the final graph).
  • stage6() creates implicit ordering constraints for resources running across remote connections, and schedules fencing actions and shutdowns.
  • stage7() “updates actions”, which means applying ordering constraints in order to modify action attributes such as optional or required.
  • stage8() creates the transition graph.
5.2.1. Challenges

Working with the scheduler is difficult. Challenges include:

  • It is far too much code to keep more than a small portion in your head at one time.
  • Small changes can have large (and unexpected) effects. This is why we have a large number of regression tests (cts/cts-scheduler), which should be run after making code changes.
  • It produces an insane amount of log messages at debug and trace levels. You can put resource ID(s) in the PCMK_trace_tags environment variable to enable trace-level messages only when related to specific resources.
  • Different parts of the main pe_working_set_t structure are finalized at different points in the scheduling process, so you have to keep in mind whether information you’re using at one point of the code can possibly change later. For example, data unpacked from the CIB can safely be used anytime after stage0(), but actions may become optional or required anytime before stage8(). There’s no easy way to deal with this.
  • Many names of struct members, functions, etc., are suboptimal, but are part of the public API and cannot be changed until an API backward compatibility break.
5.2.2. Cluster Working Set

The main data object for the scheduler is pe_working_set_t, which contains all information needed about nodes, resources, constraints, etc., both as the raw CIB XML and parsed into more usable data structures, plus the resulting transition graph XML. The variable name is usually data_set.

5.2.3. Resources

pe_resource_t is the data object representing cluster resources. A resource has a variant: primitive (a.k.a. native), group, clone, or bundle.

The resource object has members for two sets of methods, resource_object_functions_t from the libpe_status public API, and resource_alloc_functions_t whose implementation is internal to libpacemaker. The actual functions vary by variant.

The object functions have basic capabilities such as unpacking the resource XML, and determining the current or planned location of the resource.

The allocation functions have more obscure capabilities needed for scheduling, such as processing location and ordering constraints. For example, stage3(), which creates internal constraints, simply calls the internal_constraints() method for each top-level resource in the working set.

5.2.4. Nodes

Allocation of resources to nodes is done by choosing the node with the highest score for a given resource. The scheduler does a bunch of processing to generate the scores, then the actual allocation is straightforward.

Node lists are frequently used. For example, pe_working_set_t has a nodes member which is a list of all nodes in the cluster, and pe_resource_t has a running_on member which is a list of all nodes on which the resource is (or might be) active. These are lists of pe_node_t objects.

The pe_node_t object contains a struct pe_node_shared_s *details member with all node information that is independent of resource allocation (the node name, etc.).

The working set’s nodes member contains the original of this information. All other node lists contain copies of pe_node_t where only the details member points to the originals in the working set’s nodes list. In this way, the other members of pe_node_t (such as weight, which is the node score) may vary by node list, while the common details are shared.

5.2.5. Actions

pe_action_t is the data object representing actions that might need to be taken. These could be resource actions, cluster-wide actions such as fencing a node, or “pseudo-actions” which are abstractions used as convenient points for ordering other actions against.

It has a flags member which is a bitmask of enum pe_action_flags. The most important of these are pe_action_runnable (if not set, the action is “blocked” and cannot be added to the transition graph) and pe_action_optional (actions with this set will not be added to the transition graph; actions often start out as optional, and may become required later).

5.2.6. Orderings

Ordering constraints are simple in concept, but they are one of the most important, powerful, and difficult to follow aspects of the scheduler code.

pe__ordering_t is the data object representing an ordering, better thought of as a relationship between two actions, since the relation can be more complex than just “this one runs after that one”.

For an ordering “A then B”, the code generally refers to A as “first” or “before”, and B as “then” or “after”.

Much of the power comes from enum pe_ordering, which are flags that determine how an ordering behaves. There are many obscure flags with big effects. A few examples:

  • pe_order_none means the ordering is disabled and will be ignored. It’s 0, meaning no flags set, so it must be compared with equality rather than pcmk_is_set().
  • pe_order_optional means the ordering does not make either action required, so it only applies if they both become required for other reasons.
  • pe_order_implies_first means that if action B becomes required for any reason, then action A will become required as well.

6. C Development Helpers

6.1. Refactoring

Pacemaker uses an optional tool called coccinelle to do automatic refactoring. coccinelle is a very complicated tool that can be difficult to understand, and the existing documentation makes it pretty tough to get started. Much of the documentation is either aimed at kernel developers or takes the form of grammars.

However, it can apply very complex transformations across an entire source tree. This is useful for tasks like code refactoring, changing APIs (number or type of arguments, etc.), catching functions that should not be called, and changing existing patterns.

coccinelle is driven by input scripts called semantic patches written in its own language. These scripts bear a passing resemblance to source code patches and tell coccinelle how to match and modify a piece of source code. They are stored in devel/coccinelle and each script either contains a single source transformation or several related transformations. In general, we try to keep these as simple as possible.

In Pacemaker development, we use a couple targets in devel/Makefile.am to control coccinelle. The cocci target tries to apply each script to every Pacemaker source file, printing out any changes it would make to the console. The cocci-inplace target does the same but also makes those changes to the source files. A variety of warnings might also be printed. If you aren’t working on a new script, these can usually be ignored.

If you are working on a new coccinelle script, it can be useful (and faster) to skip everything else and only run the new script. The COCCI_FILES variable can be used for this:

$ make -C devel COCCI_FILES=coccinelle/new-file.cocci cocci

This variable is also used for preventing some coccinelle scripts in the Pacemaker source tree from running. Some scripts are disabled because they are not currently fully working or because they are there as templates. When adding a new script, remember to add it to this variable if it should always be run.

One complication when writing coccinelle scripts is that certain Pacemaker source files may not use private functions (those whose name starts with pcmk__). Handling this requires work in both the Makefile and in the coccinelle scripts.

The Makefile deals with this by maintaining two lists of source files: those that may use private functions and those that may not. For those that may, a special argument (-D internal) is added to the coccinelle command line. This creates a virtual dependency named internal.

In the coccinelle scripts, those transformations that modify source code to use a private function also have a dependency on internal. If that dependency was given on the command line, the transformation will be run. Otherwise, it will be skipped.

This means that not all instances of an older style of code will be changed after running a given transformation. Some developer intervention is still necessary to know whether a source code block should have been changed or not.

Probably the easiest way to learn how to use coccinelle is by following other people’s scripts. In addition to the ones in the Pacemaker source directory, there’s several others on the coccinelle website.

6.2. Unit Testing

Where possible, changes to the C side of Pacemaker should be accompanied by unit tests. Much of Pacemaker cannot effectively be unit tested (and there are other testing systems used for those parts), but the lib subdirectory is pretty easy to write tests for.

Pacemaker uses the cmocka unit testing framework which looks a lot like other unit testing frameworks for C and should be fairly familiar. In addition to regular unit tests, cmocka also gives us the ability to use mock functions for unit testing functions that would otherwise be difficult to test.

6.2.1. Organization

Pay close attention to the organization and naming of test cases to ensure the unit tests continue to work as they should.

Tests are spread throughout the source tree, alongside the source code they test. For instance, all the tests for the source code in lib/common/ are in the lib/common/tests directory. If there is no tests subdirectory, there are no tests for that library yet.

Under that directory, there is a Makefile.am and additional subdirectories. Each subdirectory contains the tests for a single library source file. For instance, all the tests for lib/common/strings.c are in the lib/common/tests/strings directory. Note that the test subdirectory does not have a .c suffix. If there is no test subdirectory, there are no tests for that file yet.

Finally, under that directory, there is a Makefile.am and then various source files. Each of these source files tests the single function that it is named after. For instance, lib/common/tests/strings/pcmk__btoa_test.c tests the pcmk__btoa_test() function in lib/common/strings.c. If there is no test source file, there are no tests for that function yet.

The _test suffix on the test source file is important. All tests have this suffix, which means all the compiled test cases will also end with this suffix. That lets us ignore all the compiled tests with a single line in .gitignore:

/lib/*/tests/*/*_test
6.2.2. Adding a test
6.2.2.1. Testing a new function in an already testable source file

Follow these steps if you want to test a function in a source file where there are already other tested functions. For the purposes of this example, we will add a test for the pcmk__scan_port() function in lib/common/strings.c. As you can see, there are already tests for other functions in this same file in the lib/common/tests/strings directory.

  • cd into lib/common/tests/strings

  • Add the new file to the the check_PROGRAMS variable in Makefile.am, making it something like this:

    check_PROGRAMS = \
           pcmk__add_word_test             \
           pcmk__btoa_test                 \
           pcmk__scan_port_test
    
  • Create a new pcmk__scan_port_test.c file, copying the copyright and include boilerplate from another file in the same directory.

  • Continue with the steps in Writing the test.

6.2.2.2. Testing a function in a source file without tests

Follow these steps if you want to test a function in a source file where there are not already other tested functions, but there are tests for other files in the same library. For the purposes of this example, we will add a test for the pcmk_acl_required() function in lib/common/acls.c. At the time of this documentation being written, no tests existed for that source file, so there is no lib/common/tests/acls directory.

  • Add to AC_CONFIG_FILES in the top-level configure.ac file so the build process knows to use directory we’re about to create. That variable would now look something like:

    dnl Other files we output
    AC_CONFIG_FILES(Makefile                                            \
                    ...
                    lib/common/tests/Makefile                           \
                    lib/common/tests/acls/Makefile                      \
                    lib/common/tests/agents/Makefile                    \
                    ...
    )
    
  • cd into lib/common/tests

  • Add to the SUBDIRS variable in Makefile.am, making it something like:

    SUBDIRS = agents acls cmdline flags operations strings utils xpath results
    
  • Create a new acls directory, copying the Makefile.am from some other directory.

  • cd into acls

  • Get rid of any existing values for check_PROGRAMS and set it to pcmk_acl_required_test like so:

    check_PROGRAMS = pcmk_acl_required_test
    
  • Follow the steps in Testing a new function in an already testable source file to create the new pcmk_acl_required_test.c file.

6.2.2.3. Testing a function in a library without tests

Adding a test case for a function in a library that doesn’t have any test cases to begin with is only slightly more complicated. In general, the steps are the same as for the previous section, except with an additional layer of directory creation.

For the purposes of this example, we will add a test case for the lrmd_send_resource_alert() function in lib/lrmd/lrmd_alerts.c. Note that this may not be a very good function or even library to write actual unit tests for.

  • Add to AC_CONFIG_FILES in the top-level configure.ac file so the build process knows to use directory we’re about to create. That variable would now look something like:

    dnl Other files we output
    AC_CONFIG_FILES(Makefile                                            \
                    ...
                    lib/lrmd/Makefile                                   \
                    lib/lrmd/tests/Makefile                             \
                    lib/services/Makefile                               \
                    ...
    )
    
  • cd into lib/lrmd

  • Create a SUBDIRS variable in Makefile.am if it doesn’t already exist. Most libraries should not have this variable already.

    SUBDIRS = tests
    
  • Create a new tests directory and add a Makefile.am with the following contents:

    SUBDIRS = lrmd_alerts
    
  • Follow the steps in Testing a function in a source file without tests to create the rest of the new directory structure.

  • Follow the steps in Testing a new function in an already testable source file to create the new lrmd_send_resource_alert_test.c file.

6.2.2.4. Adding to an existing test case

If all you need to do is add additional test cases to an existing file, none of the above work is necessary. All you need to do is find the test source file with the name matching your function and add to it and then follow the instructions in Writing the test.

6.2.3. Writing the test

A test case file contains a fair amount of boilerplate. For this reason, it’s usually easiest to just copy an existing file and adapt it to your needs. However, here’s the basic structure:

/*
 * Copyright 2021 the Pacemaker project contributors
 *
 * The version control history for this file may have further details.
 *
 * This source code is licensed under the GNU Lesser General Public License
 * version 2.1 or later (LGPLv2.1+) WITHOUT ANY WARRANTY.
 */

#include <crm_internal.h>

#include <stdarg.h>
#include <stddef.h>
#include <stdint.h>
#include <setjmp.h>
#include <cmocka.h>

/* Put your test-specific includes here */

/* Put your test functions here */

int
main(int argc, char **argv)
{
    /* Register your test functions here */

    cmocka_set_message_output(CM_OUTPUT_TAP);
    return cmocka_run_group_tests(tests, NULL, NULL);
}

Each test-specific function should test one aspect of the library function, though it can include many assertions if there are many ways of testing that one aspect. For instance, there might be multiple ways of testing regular expression matching:

static void
regex(void **state) {
    const char *s1 = "abcd";
    const char *s2 = "ABCD";

    assert_int_equal(pcmk__strcmp(NULL, "a..d", pcmk__str_regex), 1);
    assert_int_equal(pcmk__strcmp(s1, NULL, pcmk__str_regex), 1);
    assert_int_equal(pcmk__strcmp(s1, "a..d", pcmk__str_regex), 0);
}

Each test-specific function must also be registered or it will not be called. This is done with cmocka_unit_test() in the main function:

const struct CMUnitTest tests[] = {
    cmocka_unit_test(regex),
};
6.2.4. Running

If you had to create any new files or directories, you will first need to run ./configure from the top level of the source directory. This will regenerate the Makefiles throughout the tree. If you skip this step, your changes will be skipped and you’ll be left wondering why the output doesn’t match what you expected.

To run the tests, simply run make check after previously building the source with make. The test cases in each directory will be built and then run. This should not take long. If all the tests succeed, you will be back at the prompt. Scrolling back through the history, you should see lines like the following:

PASS: pcmk__strcmp_test 1 - same_pointer
PASS: pcmk__strcmp_test 2 - one_is_null
PASS: pcmk__strcmp_test 3 - case_matters
PASS: pcmk__strcmp_test 4 - case_insensitive
PASS: pcmk__strcmp_test 5 - regex
============================================================================
Testsuite summary for pacemaker 2.1.0
============================================================================
# TOTAL: 33
# PASS:  33
# SKIP:  0
# XFAIL: 0
# FAIL:  0
# XPASS: 0
# ERROR: 0
============================================================================
make[7]: Leaving directory '/home/clumens/src/pacemaker/lib/common/tests/strings'

The testing process will quit on the first failed test, and you will see lines like these:

PASS: pcmk__scan_double_test 3 - trailing_chars
FAIL: pcmk__scan_double_test 4 - typical_case
PASS: pcmk__scan_double_test 5 - double_overflow
PASS: pcmk__scan_double_test 6 - double_underflow
ERROR: pcmk__scan_double_test - exited with status 1
PASS: pcmk__starts_with_test 1 - bad_input
============================================================================
Testsuite summary for pacemaker 2.1.0
============================================================================
# TOTAL: 56
# PASS:  54
# SKIP:  0
# XFAIL: 0
# FAIL:  1
# XPASS: 0
# ERROR: 1
============================================================================
See lib/common/tests/strings/test-suite.log
Please report to users@clusterlabs.org
============================================================================
make[7]: *** [Makefile:1218: test-suite.log] Error 1
make[7]: Leaving directory '/home/clumens/src/pacemaker/lib/common/tests/strings'

The failure is in lib/common/tests/strings/test-suite.log:

ERROR: pcmk__scan_double_test
=============================

1..6
ok 1 - empty_input_string
PASS: pcmk__scan_double_test 1 - empty_input_string
ok 2 - bad_input_string
PASS: pcmk__scan_double_test 2 - bad_input_string
ok 3 - trailing_chars
PASS: pcmk__scan_double_test 3 - trailing_chars
not ok 4 - typical_case
FAIL: pcmk__scan_double_test 4 - typical_case
# 0.000000 != 3.000000
# pcmk__scan_double_test.c:80: error: Failure!
ok 5 - double_overflow
PASS: pcmk__scan_double_test 5 - double_overflow
ok 6 - double_underflow
PASS: pcmk__scan_double_test 6 - double_underflow
# not ok - tests
ERROR: pcmk__scan_double_test - exited with status 1

At this point, you need to determine whether your test case is incorrect or whether the code being tested is incorrect. Fix whichever is wrong and continue.

6.3. Debugging

6.3.1. gdb

If you use gdb for debugging, some helper functions are defined in devel/gdbhelpers, which can be given to gdb using the -x option.

From within the debugger, you can then invoke the pcmk command that will describe the helper functions available.

7. Evolution of the project

This section will not generally be of interest, but may occasionally shed light on why the current code is structured the way it is when investigating some thorny issue.

7.1. Origin in Heartbeat project

Pacemaker can be considered as a spin-off from Heartbeat, the original comprehensive high availability suite started by Alan Robertson. Some portions of code are shared, at least on the conceptual level if not verbatim, till today, even if the effective percentage continually declines.

Before Pacemaker 2.0, Pacemaker supported Heartbeat as a cluster layer alternative to Corosync. That support was dropped for the 2.0.0 release (see commit 55ab749bf).

An archive of a 2016 checkout of the Heartbeat code base is shared as a read-only repository. Notable commits include:

Regarding Pacemaker’s split from heartbeat, it evolved stepwise (as opposed to one-off cut), and the last step of full dependency is depicted in The Corosync Cluster Engine paper, fig. 10. This article also provides a good reference regarding wider historical context of the tangentially (and deeper in some cases) meeting components around that time.

7.1.1. Influence of Heartbeat on Pacemaker

On a closer look, we can identify these things in common:

  • extensive use of data types and functions of GLib
  • Cluster Testing System (CTS), inherited from initial implementation by Alan Robertson

7.2. Notable Restructuring Steps in the Codebase

File renames may not appear as notable … unless one runs into complicated git blame and git log scenarios, so some more massive ones may be stated as well.