YODA

Projects that follow the best practices below can voluntarily self-certify and show that they've achieved an Open Source Security Foundation (OpenSSF) best practices badge.

There is no set of practices that can guarantee that software will never have defects or vulnerabilities; even formal methods can fail if the specifications or assumptions are wrong. Nor is there any set of practices that can guarantee that a project will sustain a healthy and well-functioning development community. However, following best practices can help improve the results of projects. For example, some practices enable multi-person review before release, which can both help find otherwise hard-to-find technical vulnerabilities and help build trust and a desire for repeated interaction among developers from different companies. To earn a badge, all MUST and MUST NOT criteria must be met, all SHOULD criteria must be met OR be unmet with justification, and all SUGGESTED criteria must be met OR unmet (we want them considered at least). If you want to enter justification text as a generic comment, instead of being a rationale that the situation is acceptable, start the text block with '//' followed by a space. Feedback is welcome via the GitHub site as issues or pull requests There is also a mailing list for general discussion.

We gladly provide the information in several locales, however, if there is any conflict or inconsistency between the translations, the English version is the authoritative version.
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These are the Passing level criteria. You can also view the Silver or Gold level criteria.

Baseline Series: Baseline Level 1 Baseline Level 2 Baseline Level 3

        

 Basics 13/13

  • General

    Note that other projects may use the same name.

    YODA ("Yet more Objects for Data Analysis") is a general-purpose
    C++17 library, with a full Python interface, for statistical data
    objects: histograms, profile histograms, scatters, and binned estimates
    with structured uncertainty breakdowns. It was developed in a collider
    physics context, but designed from the outset to be domain-agnostic.

    The design centres on a small set of composable analysis-object types
    sharing a common AnalysisObject base, with support for continuous,
    integer and categorical bin axes, multi-component systematic uncertainty
    breakdowns, and lossless serialisation to the plain-text .yoda format.
    Objects can be rebinned, merged, normalised and converted between
    representations without discarding statistical information.

    YODA is the data model underlying Rivet,
    the community-standard toolkit for validating Monte Carlo event
    generators against published measurements, and is deployed across the LHC
    experiments and the wider phenomenology community. It is developed as
    part of the MCnet software suite and
    distributed under the GPL-3.0.

    Please use SPDX license expression format; examples include "Apache-2.0", "BSD-2-Clause", "BSD-3-Clause", "GPL-2.0+", "LGPL-3.0+", "MIT", and "(BSD-2-Clause OR Ruby)". Do not include single quotes or double quotes.
    If there is more than one language, list them as comma-separated values (spaces optional) and sort them from most to least used. If there is a long list, please list at least the first three most common ones. If there is no language (e.g., this is a documentation-only or test-only project), use the single character "-". Please use a conventional capitalization for each language, e.g., "JavaScript".
    The Common Platform Enumeration (CPE) is a structured naming scheme for information technology systems, software, and packages. It is used in a number of systems and databases when reporting vulnerabilities.

    YODA is developed as part of the MCnet
    suite of Monte Carlo tools, alongside Rivet,
    and is hosted on GitLab.

    The library is an offline data-analysis and I/O component: it performs no
    network communication, requires no elevated privileges, and handles no
    credentials or personal data. Its principal security-relevant surface is
    the parsing of input files (.yoda), which may
    originate from untrusted sources, since users routinely exchange and
    download data files. Testing and hardening effort is concentrated
    accordingly.

    Development is led by a small team of physicists and research software
    engineers across Glasgow and UCL. Contributions
    are welcome via merge requests on the GitLab repository, and the
    development mailing list is at yoda-support@cern.ch.

  • Basic project website content


    The project website MUST succinctly describe what the software does (what problem does it solve?). [description_good]
    This MUST be in language that potential users can understand (e.g., it uses minimal jargon).

    The project website MUST provide information on how to: obtain, provide feedback (as bug reports or enhancements), and contribute to the software. [interact]

    https://yoda.hepforge.org/ (navigator contains GitLab repo link)



    The information on how to contribute MUST explain the contribution process (e.g., are pull requests used?) (URL required) [contribution]
    We presume that projects on GitHub use issues and pull requests unless otherwise noted. This information can be short, e.g., stating that the project uses pull requests, an issue tracker, or posts to a mailing list (which one?)

    The information on how to contribute SHOULD include the requirements for acceptable contributions (e.g., a reference to any required coding standard). (URL required) [contribution_requirements]
  • FLOSS license


    The software produced by the project MUST be released as FLOSS. [floss_license]
    FLOSS is software released in a way that meets the Open Source Definition or Free Software Definition. Examples of such licenses include the CC0, MIT, BSD 2-clause, BSD 3-clause revised, Apache 2.0, Lesser GNU General Public License (LGPL), and the GNU General Public License (GPL). For our purposes, this means that the license MUST be: The software MAY also be licensed other ways (e.g., "GPLv2 or proprietary" is acceptable).

    It is SUGGESTED that any required license(s) for the software produced by the project be approved by the Open Source Initiative (OSI). [floss_license_osi]
    The OSI uses a rigorous approval process to determine which licenses are OSS.

    The GPL-3.0 license is approved by the Open Source Initiative (OSI).



    The project MUST post the license(s) of its results in a standard location in their source repository. (URL required) [license_location]
    One convention is posting the license as a top-level file named LICENSE or COPYING, which MAY be followed by an extension such as ".txt" or ".md". An alternative convention is to have a directory named LICENSES containing license file(s); these files are typically named as their SPDX license identifier followed by an appropriate file extension, as described in the REUSE Specification. Note that this criterion is only a requirement on the source repository. You do NOT need to include the license file when generating something from the source code (such as an executable, package, or container). For example, when generating an R package for the Comprehensive R Archive Network (CRAN), follow standard CRAN practice: if the license is a standard license, use the standard short license specification (to avoid installing yet another copy of the text) and list the LICENSE file in an exclusion file such as .Rbuildignore. Similarly, when creating a Debian package, you may put a link in the copyright file to the license text in /usr/share/common-licenses, and exclude the license file from the created package (e.g., by deleting the file after calling dh_auto_install). We encourage including machine-readable license information in generated formats where practical.
  • Documentation


    The project MUST provide basic documentation for the software produced by the project. [documentation_basics]
    This documentation must be in some media (such as text or video) that includes: how to install it, how to start it, how to use it (possibly with a tutorial using examples), and how to use it securely (e.g., what to do and what not to do) if that is an appropriate topic for the software. The security documentation need not be long. The project MAY use hypertext links to non-project material as documentation. If the project does not produce software, choose "not applicable" (N/A).

    The project MUST provide reference documentation that describes the external interface (both input and output) of the software produced by the project. [documentation_interface]
    The documentation of an external interface explains to an end-user or developer how to use it. This would include its application program interface (API) if the software has one. If it is a library, document the major classes/types and methods/functions that can be called. If it is a web application, define its URL interface (often its REST interface). If it is a command-line interface, document the parameters and options it supports. In many cases it's best if most of this documentation is automatically generated, so that this documentation stays synchronized with the software as it changes, but this isn't required. The project MAY use hypertext links to non-project material as documentation. Documentation MAY be automatically generated (where practical this is often the best way to do so). Documentation of a REST interface may be generated using Swagger/OpenAPI. Code interface documentation MAY be generated using tools such as JSDoc (JavaScript), ESDoc (JavaScript), pydoc (Python), devtools (R), pkgdown (R), and Doxygen (many). Merely having comments in implementation code is not sufficient to satisfy this criterion; there needs to be an easy way to see the information without reading through all the source code. If the project does not produce software, choose "not applicable" (N/A).
  • Other


    The project sites (website, repository, and download URLs) MUST support HTTPS using TLS. [sites_https]
    This requires that the project home page URL and the version control repository URL begin with "https:", not "http:". You can get free certificates from Let's Encrypt. Projects MAY implement this criterion using (for example) GitHub pages, GitLab pages, or SourceForge project pages. If you support HTTP, we urge you to redirect the HTTP traffic to HTTPS.

    The project MUST have one or more mechanisms for discussion (including proposed changes and issues) that are searchable, allow messages and topics to be addressed by URL, enable new people to participate in some of the discussions, and do not require client-side installation of proprietary software. [discussion]
    Examples of acceptable mechanisms include archived mailing list(s), GitHub issue and pull request discussions, Bugzilla, Mantis, and Trac. Asynchronous discussion mechanisms (like IRC) are acceptable if they meet these criteria; make sure there is a URL-addressable archiving mechanism. Proprietary JavaScript, while discouraged, is permitted.

    Issues and proposed changes are discussed in the project's GitLab issue
    tracker and merge requests at
    https://gitlab.com/hepcedar/yoda/-/work_items, which are publicly readable,
    full-text searchable, and individually addressable by URL (both issues
    and individual comments). Anyone with a free GitLab account can open an
    issue or comment on an existing one, and no client-side proprietary
    software is required. A user-support mailing list
    (yoda-support@cern.ch) is additionally available for questions, though
    development discussion takes place primarily in the tracker.



    The project SHOULD provide documentation in English and be able to accept bug reports and comments about code in English. [english]
    English is currently the lingua franca of computer technology; supporting English increases the number of different potential developers and reviewers worldwide. A project can meet this criterion even if its core developers' primary language is not English.

    All project documentation (including the manual, tutorials and Doxygen API reference), in-source code comments, and commit messages are written in English. Bug reports, merge requests and comments are accepted in English via the GitLab tracker and the support mailing list, and are handled in English by the maintainers.



    The project MUST be maintained. [maintained]
    As a minimum, the project should attempt to respond to significant problem and vulnerability reports. A project that is actively pursuing a badge is probably maintained. All projects and people have limited resources, and typical projects must reject some proposed changes, so limited resources and proposal rejections do not by themselves indicate an unmaintained project.

    When a project knows that it will no longer be maintained, it should set this criterion to "Unmet" and use the appropriate mechanism(s) to indicate to others that it is not being maintained. For example, use “DEPRECATED” as the first heading of its README, add “DEPRECATED” near the beginning of its home page, add “DEPRECATED” to the beginning of its code repository project description, add a no-maintenance-intended badge in its README and/or home page, mark it as deprecated in any package repositories (e.g., npm deprecate), and/or use the code repository's marking system to archive it (e.g., GitHub's "archive" setting, GitLab’s "archived" marking, Gerrit's "readonly" status, or SourceForge’s "abandoned" project status). Additional discussion can be found here.

    YODA is under active development and maintenance. Releases are made
    regularly, with a maintained changelog at https://gitlab.com/hepcedar/yoda/-/blob/release-2-1-x/ChangeLog; the most recent
    release was 2.1.3 in May 2026. The GitLab issue tracker is monitored by
    the maintainers, and significant problem reports are responded to.
    Development is ongoing as part of the MCnet suite, with a funded team of
    maintainers across [institutions].


 Change Control 9/9

  • Public version-controlled source repository


    The project MUST have a version-controlled source repository that is publicly readable and has a URL. [repo_public]
    The URL MAY be the same as the project URL. The project MAY use private (non-public) branches in specific cases while the change is not publicly released (e.g., for fixing a vulnerability before it is revealed to the public).

    The project's source repository MUST track what changes were made, who made the changes, and when the changes were made. [repo_track]

    To enable collaborative review, the project's source repository MUST include interim versions for review between releases; it MUST NOT include only final releases. [repo_interim]
    Projects MAY choose to omit specific interim versions from their public source repositories (e.g., ones that fix specific non-public security vulnerabilities, may never be publicly released, or include material that cannot be legally posted and are not in the final release).

    Development takes place in the open on GitLab at
    https://gitlab.com/hepcedar/yoda. The repository contains the full commit
    history, not only tagged releases: individual commits, feature branches
    and merge requests are publicly visible and reviewable as work
    progresses. Tagged releases are cut from this same public history.



    It is SUGGESTED that common distributed version control software be used (e.g., git) for the project's source repository. [repo_distributed]
    Git is not specifically required and projects can use centralized version control software (such as subversion) with justification.

    The project uses git, hosted on GitLab at https://gitlab.com/hepcedar/yoda


  • Unique version numbering


    The project results MUST have a unique version identifier for each release intended to be used by users. [version_unique]
    This MAY be met in a variety of ways including a commit IDs (such as git commit id or mercurial changeset id) or a version number (including version numbers that use semantic versioning or date-based schemes like YYYYMMDD).

    Each release has a unique three-component version number (e.g. 2.1.0),
    applied consistently across the git tag, the release tarball filename
    (yoda-X.Y.Z.tar.gz) and the version reported by the library at runtime
    and by yoda-config --version. Version numbers are never reused.



    It is SUGGESTED that the Semantic Versioning (SemVer) or Calendar Versioning (CalVer) version numbering format be used for releases. It is SUGGESTED that those who use CalVer include a micro level value. [version_semver]
    Projects should generally prefer whatever format is expected by their users, e.g., because it is the normal format used by their ecosystem. Many ecosystems prefer SemVer, and SemVer is generally preferred for application programmer interfaces (APIs) and software development kits (SDKs). CalVer tends to be used by projects that are large, have an unusually large number of independently-developed dependencies, have a constantly-changing scope, or are time-sensitive. It is SUGGESTED that those who use CalVer include a micro level value, because including a micro level supports simultaneously-maintained branches whenever that becomes necessary. Other version numbering formats may be used as version numbers, including git commit IDs or mercurial changeset IDs, as long as they uniquely identify versions. However, some alternatives (such as git commit IDs) can cause problems as release identifiers, because users may not be able to easily determine if they are up-to-date. The version ID format may be unimportant for identifying software releases if all recipients only run the latest version (e.g., it is the code for a single website or internet service that is constantly updated via continuous delivery).

    YODA uses a three-component MAJOR.MINOR.PATCH scheme closely modelled on Semantic Versioning, with major increments reserved for backwards-incompatible interface changes. The correspondence is not strictly enforced for minor releases, which may occasionally include small interface changes, so the project does not claim full SemVer compliance.



    It is SUGGESTED that projects identify each release within their version control system. For example, it is SUGGESTED that those using git identify each release using git tags. [version_tags]

    Every release is tagged in git, with tags visible at
    https://gitlab.com/hepcedar/yoda/-/tags. The tag name corresponds to the
    release version number, so the source state of any release can be
    recovered directly from the repository.


  • Release notes


    The project MUST provide, in each release, release notes that are a human-readable summary of major changes in that release to help users determine if they should upgrade and what the upgrade impact will be. The release notes MUST NOT be the raw output of a version control log (e.g., the "git log" command results are not release notes). Projects whose results are not intended for reuse in multiple locations (such as the software for a single website or service) AND employ continuous delivery MAY select "N/A". (URL required) [release_notes]
    The release notes MAY be implemented in a variety of ways. Many projects provide them in a file named "NEWS", "CHANGELOG", or "ChangeLog", optionally with extensions such as ".txt", ".md", or ".html". Historically the term "change log" meant a log of every change, but to meet these criteria what is needed is a human-readable summary. The release notes MAY instead be provided by version control system mechanisms such as the GitHub Releases workflow.

    Each release is accompanied by human-written release notes published on
    the project's GitLab releases page:
    https://gitlab.com/hepcedar/yoda/-/releases

    The notes summarise new features, interface changes and significant bug
    fixes for each version, written to help users assess the impact of
    upgrading. They are composed by the maintainers, not generated from the
    version control log. A separate hand-maintained ChangeLog in the
    repository records development detail at finer granularity, and releases
    are also announced with a summary on the project website and the MCnet
    announcement mailing list.



    The release notes MUST identify every publicly known run-time vulnerability fixed in this release that already had a CVE assignment or similar when the release was created. This criterion may be marked as not applicable (N/A) if users typically cannot practically update the software themselves (e.g., as is often true for kernel updates). This criterion applies only to the project results, not to its dependencies. If there are no release notes or there have been no publicly known vulnerabilities, choose N/A. [release_notes_vulns]
    This criterion helps users determine if a given update will fix a vulnerability that is publicly known, to help users make an informed decision about updating. If users typically cannot practically update the software themselves on their computers, but must instead depend on one or more intermediaries to perform the update (as is often the case for a kernel and low-level software that is intertwined with a kernel), the project may choose "not applicable" (N/A) instead, since this additional information will not be helpful to those users. Similarly, a project may choose N/A if all recipients only run the latest version (e.g., it is the code for a single website or internet service that is constantly updated via continuous delivery). This criterion only applies to the project results, not its dependencies. Listing the vulnerabilities of all transitive dependencies of a project becomes unwieldy as dependencies increase and vary, and is unnecessary since tools that examine and track dependencies can do this in a more scalable way.

    No publicly known run-time vulnerabilities have been reported against YODA, and no CVEs have been assigned to the project, so there are none to identify in release notes.


 Reporting 8/8

  • Bug-reporting process


    The project MUST provide a process for users to submit bug reports (e.g., using an issue tracker or a mailing list). (URL required) [report_process]

    Users can submit bug reports through the project's GitLab issue tracker:
    https://gitlab.com/hepcedar/yoda/-/work_items

    Anyone with a free GitLab account can open an issue. A support mailing
    list (yoda-support@cern.ch) is also available for users who prefer email
    or who are unsure whether a problem is a bug.



    The project SHOULD use an issue tracker for tracking individual issues. [report_tracker]

    The project uses the GitLab issue tracker for individual issues:
    https://gitlab.com/hepcedar/yoda/-/work_items

    Each report is tracked as a separate issue with its own identifier and
    URL, with status, labels, assignee and discussion history maintained per
    issue. Bugs reported via the support mailing list are transferred to the
    tracker where they warrant follow-up.



    The project MUST acknowledge a majority of bug reports submitted in the last 2-12 months (inclusive); the response need not include a fix. [report_responses]

    The maintainers monitor the GitLab issue tracker and respond to bug reports. Reviewing issues opened in the qualifying window, the large majority received a maintainer response -- typically triage, a request for a reproducer, or an explanation of the behaviour -- independently of whether a fix followed. Reports arriving via the support mailing list are answered directly by the maintainers.



    The project SHOULD respond to a majority (>50%) of enhancement requests in the last 2-12 months (inclusive). [enhancement_responses]
    The response MAY be 'no' or a discussion about its merits. The goal is simply that there be some response to some requests, which indicates that the project is still alive. For purposes of this criterion, projects need not count fake requests (e.g., from spammers or automated systems). If a project is no longer making enhancements, please select "unmet" and include the URL that makes this situation clear to users. If a project tends to be overwhelmed by the number of enhancement requests, please select "unmet" and explain.

    Enhancement requests are submitted through the GitLab issue tracker and the support mailing list, and the maintainers respond to the majority of them -- whether by implementing the request, discussing design alternatives, or explaining why it falls outside the project's scope. Requests are frequently raised directly by the physics user community through the MCnet collaboration and at community meetings, and are discussed there as well as in the tracker.



    The project MUST have a publicly available archive for reports and responses for later searching. (URL required) [report_archive]

    All issues and their discussion, including closed issues, remain publicly
    readable and searchable in the GitLab tracker:
    https://gitlab.com/hepcedar/yoda/-/work_items

    The archive is browsable without an account, supports full-text search
    across open and closed issues, and every issue and individual comment has
    a stable, addressable URL.


  • Vulnerability report process


    The project MUST publish the process for reporting vulnerabilities on the project site. (URL required) [vulnerability_report_process]
    Projects hosted on GitHub SHOULD consider enabling privately reporting a security vulnerability. Projects on GitLab SHOULD consider using its ability for privately reporting a vulnerability. Projects MAY identify a mailing address on https://PROJECTSITE/security, often in the form security@example.org. This vulnerability reporting process MAY be the same as its bug reporting process. Vulnerability reports MAY always be public, but many projects have a private vulnerability reporting mechanism.

    The vulnerability reporting process is published in the project's
    SECURITY.md, at the root of the source repository and linked from the
    project website:
    https://gitlab.com/hepcedar/yoda/-/blob/release-2-1-x/SECURITY.md

    It documents the private reporting address, the alternative of a
    confidential GitLab issue, the information to include in a report, and
    the expected response and disclosure process.



    If private vulnerability reports are supported, the project MUST include how to send the information in a way that is kept private. (URL required) [vulnerability_report_private]
    Examples include a private defect report submitted on the web using HTTPS (TLS) or an email encrypted using OpenPGP. If vulnerability reports are always public (so there are never private vulnerability reports), choose "not applicable" (N/A).

    The SECURITY.md documents two private reporting routes: a dedicated
    email address (yoda-security@cern.ch) that reaches the core
    maintainers and is not publicly archived, and the option of opening a
    confidential issue on the GitLab tracker, which is visible only to
    project members.

    https://gitlab.com/hepcedar/yoda/-/blob/release-2-1-x/SECURITY.md



    The project's initial response time for any vulnerability report received in the last 6 months MUST be less than or equal to 14 days. [vulnerability_report_response]
    If there have been no vulnerabilities reported in the last 6 months, choose "not applicable" (N/A).

    No vulnerability reports have been received in the last six months, so there are no response times to report. The project's published policy in SECURITY.md commits to acknowledging reports within 14 days, and the private reporting address reaches multiple maintainers so that reports are not dependent on any single person's availability.


 Quality 12/13

  • Working build system


    If the software produced by the project requires building for use, the project MUST provide a working build system that can automatically rebuild the software from source code. [build]
    A build system determines what actions need to occur to rebuild the software (and in what order), and then performs those steps. For example, it can invoke a compiler to compile the source code. If an executable is created from source code, it must be possible to modify the project's source code and then generate an updated executable with those modifications. If the software produced by the project depends on external libraries, the build system does not need to build those external libraries. If there is no need to build anything to use the software after its source code is modified, select "not applicable" (N/A).

    YODA provides a standard GNU autotools build system (autoconf, automake,
    libtool). The software is built from source with the conventional
    sequence:

        ./configure [options]
        make
        make install
    

    The build is fully automated: dependency and compiler detection, C++
    compilation, generation of the Python bindings (via Cython), and
    installation are all handled by the build system without manual
    intervention. Release tarballs ship with a pre-generated configure
    script, so end users need only a C++ compiler, make and Python. Building from a git
    checkout additionally requires the autotools, with the configure script
    generated by running autoreconf -i.



    It is SUGGESTED that common tools be used for building the software. [build_common_tools]
    For example, Maven, Ant, cmake, the autotools, make, rake (Ruby), or devtools (R).

    The build uses the GNU autotools (autoconf, automake, libtool) together with make and a standard C++ compiler, all of which are widely available and packaged for every mainstream Linux distribution and macOS. No project-specific or unusual build tooling is required. The Python bindings are generated with Cython, also widely packaged.



    The project SHOULD be buildable using only FLOSS tools. [build_floss_tools]

    YODA builds using only FLOSS tools: the GNU autotools (autoconf,
    automake, libtool), make, and a standard C++ compiler. Both GCC and
    Clang are supported, and [Cython] is used to generate the Python
    bindings. No proprietary compiler, library or build tool is required at
    any stage.


  • Automated test suite


    The project MUST use at least one automated test suite that is publicly released as FLOSS (this test suite may be maintained as a separate FLOSS project). The project MUST clearly show or document how to run the test suite(s) (e.g., via a continuous integration (CI) script or via documentation in files such as BUILD.md, README.md, or CONTRIBUTING.md). [test]
    The project MAY use multiple automated test suites (e.g., one that runs quickly, vs. another that is more thorough but requires special equipment). There are many test frameworks and test support systems available, including Selenium (web browser automation), Junit (JVM, Java), RUnit (R), testthat (R).

    YODA includes an automated test suite in the tests/ directory of the
    source repository, released under the same GPL-3.0 licence as the rest of
    the project. It covers the core analysis-object types, fill and
    aggregation behaviour, rebinning and merging operations, and I/O
    round-tripping through the .yoda format, and includes both the C++ tests
    and tests of the Python interface.

    The suite is run with:

        make check
    

    after configuring and building, as documented in https://gitlab.com/hepcedar/yoda/-/blob/release-2-1-x/doc/installation.md

    It is also run automatically in CI on every push: https://gitlab.com/hepcedar/yoda/-/blob/release-2-1-x/.gitlab-ci.yml



    A test suite SHOULD be invocable in a standard way for that language. [test_invocation]
    For example, "make check", "mvn test", or "rake test" (Ruby).

    The test suite is invoked with make check, the standard target for
    autotools-based projects, after the usual ./configure && make build
    steps. No project-specific test runner or wrapper script is required.



    It is SUGGESTED that the test suite cover most (or ideally all) the code branches, input fields, and functionality. [test_most]

    The test suite covers over 90% of lines (4391 of 4642), measured with gcov/lcov automatically in CI on every merge request. Function-level coverage figures are not meaningful for this codebase: YODA is largely header-only and heavily templated, so gcov counts every instantiated specialisation — including implicit special member functions — as a distinct function, inflating the denominator.



    It is SUGGESTED that the project implement continuous integration (where new or changed code is frequently integrated into a central code repository and automated tests are run on the result). [test_continuous_integration]

    The project uses GitLab CI. Every merge request triggers an automated
    pipeline that builds the library and runs the full test suite, including
    coverage measurement with gcov/lcov. Changes are merged into the main
    branch only after the pipeline passes, so the integration branch is
    continuously tested.

    CI configuration: https://gitlab.com/hepcedar/yoda/-/blob/main/.gitlab-ci.yml
    Pipeline history: https://gitlab.com/hepcedar/yoda/-/pipelines


  • New functionality testing


    The project MUST have a general policy (formal or not) that as major new functionality is added to the software produced by the project, tests of that functionality should be added to an automated test suite. [test_policy]
    As long as a policy is in place, even by word of mouth, that says developers should add tests to the automated test suite for major new functionality, select "Met."

    The project's CONTRIBUTING.md states that contributions adding new
    functionality are expected to include corresponding tests in the
    automated test suite. This is applied in practice during merge request
    review, and the CI pipeline reports test results and coverage on every
    merge request, so gaps in test coverage are visible to reviewers before
    merge.

    https://gitlab.com/hepcedar/yoda/-/blob/release-2-1-x/CONTRIBUTING.md



    The project MUST have evidence that the test_policy for adding tests has been adhered to in the most recent major changes to the software produced by the project. [tests_are_added]
    Major functionality would typically be mentioned in the release notes. Perfection is not required, merely evidence that tests are typically being added in practice to the automated test suite when new major functionality is added to the software produced by the project.


    It is SUGGESTED that this policy on adding tests (see test_policy) be documented in the instructions for change proposals. [tests_documented_added]
    However, even an informal rule is acceptable as long as the tests are being added in practice.

    The policy is stated in CONTRIBUTING.md, the project's documented
    instructions for proposing changes, so contributors encounter it before
    submitting a merge request rather than discovering it in review.

    https://gitlab.com/hepcedar/yoda/-/blob/release-2-1-x/CONTRIBUTING.md


  • Warning flags


    The project MUST enable one or more compiler warning flags, a "safe" language mode, or use a separate "linter" tool to look for code quality errors or common simple mistakes, if there is at least one FLOSS tool that can implement this criterion in the selected language. [warnings]
    Examples of compiler warning flags include gcc/clang "-Wall". Examples of a "safe" language mode include JavaScript "use strict" and perl5's "use warnings". A separate "linter" tool is simply a tool that examines the source code to look for code quality errors or common simple mistakes. These are typically enabled within the source code or build instructions.

    The build enables compiler warnings by default: -Wall and -Wextra
    are passed to the C++ compiler via the build system, for both GCC and
    Clang. Warnings are visible in the CI build logs for every merge request,
    so newly introduced warnings are apparent during review.



    The project MUST address warnings. [warnings_fixed]
    These are the warnings identified by the implementation of the warnings criterion. The project should fix warnings or mark them in the source code as false positives. Ideally there would be no warnings, but a project MAY accept some warnings (typically less than 1 warning per 100 lines or less than 10 warnings).

    Warnings are enabled with -Wall and -Wextra under both GCC and
    Clang, and warnings arising in YODA's own sources are fixed as they
    appear, with the CI build log for each merge request making new ones
    visible during review.

    The build is not currently warning-free, because the bundled copy of the
    third-party Eigen3 library has aged and emits warnings under recent
    compilers. This has been addressed on the main branch: the bundled Eigen3
    has been updated, and the build now additionally supports linking against
    an external Eigen3 installation. These changes will appear in the
    2.2.x release series.



    It is SUGGESTED that projects be maximally strict with warnings in the software produced by the project, where practical. [warnings_strict]
    Some warnings cannot be effectively enabled on some projects. What is needed is evidence that the project is striving to enable warning flags where it can, so that errors are detected early.

    Warnings are enabled with -Wall and -Wextra and are fixed in the
    project's own sources, but the build does not use -Werror. YODA is a
    header-only library compiled directly by users on a wide range of
    compilers and compiler versions; treating warnings as errors in the
    user-facing build would cause builds to fail whenever a new compiler
    release introduces a new diagnostic, for reasons unrelated to any defect
    in the code.


 Security 16/16

  • Secure development knowledge


    The project MUST have at least one primary developer who knows how to design secure software. (See ‘details’ for the exact requirements.) [know_secure_design]
    This requires understanding the following design principles, including the 8 principles from Saltzer and Schroeder:
    • economy of mechanism (keep the design as simple and small as practical, e.g., by adopting sweeping simplifications)
    • fail-safe defaults (access decisions should deny by default, and projects' installation should be secure by default)
    • complete mediation (every access that might be limited must be checked for authority and be non-bypassable)
    • open design (security mechanisms should not depend on attacker ignorance of its design, but instead on more easily protected and changed information like keys and passwords)
    • separation of privilege (ideally, access to important objects should depend on more than one condition, so that defeating one protection system won't enable complete access. E.G., multi-factor authentication, such as requiring both a password and a hardware token, is stronger than single-factor authentication)
    • least privilege (processes should operate with the least privilege necessary)
    • least common mechanism (the design should minimize the mechanisms common to more than one user and depended on by all users, e.g., directories for temporary files)
    • psychological acceptability (the human interface must be designed for ease of use - designing for "least astonishment" can help)
    • limited attack surface (the attack surface - the set of the different points where an attacker can try to enter or extract data - should be limited)
    • input validation with allowlists (inputs should typically be checked to determine if they are valid before they are accepted; this validation should use allowlists (which only accept known-good values), not denylists (which attempt to list known-bad values)).
    A "primary developer" in a project is anyone who is familiar with the project's code base, is comfortable making changes to it, and is acknowledged as such by most other participants in the project. A primary developer would typically make a number of contributions over the past year (via code, documentation, or answering questions). Developers would typically be considered primary developers if they initiated the project (and have not left the project more than three years ago), have the option of receiving information on a private vulnerability reporting channel (if there is one), can accept commits on behalf of the project, or perform final releases of the project software. If there is only one developer, that individual is the primary developer. Many books and courses are available to help you understand how to develop more secure software and discuss design. For example, the Secure Software Development Fundamentals course is a free set of three courses that explain how to develop more secure software (it's free if you audit it; for an extra fee you can earn a certificate to prove you learned the material).

    At least one primary developer is familiar with these secure design
    principles, including the Saltzer and Schroeder principles, attack
    surface limitation and input validation.

    They are applied to YODA where relevant to its architecture. The library
    is an offline data-analysis and I/O component: it performs no network
    communication, requires no elevated privileges, and handles no
    credentials or personal data, so the attack surface is deliberately
    limited to file parsing. Input parsing is written defensively, with
    malformed input rejected rather than accepted with undefined behaviour,
    and the parsing code is exercised by the automated test suite (94.6% line
    coverage) run in CI on every merge request. The codebase is fully open,
    developed in public, and reviewed through merge requests.



    At least one of the project's primary developers MUST know of common kinds of errors that lead to vulnerabilities in this kind of software, as well as at least one method to counter or mitigate each of them. [know_common_errors]
    Examples (depending on the type of software) include SQL injection, OS injection, classic buffer overflow, cross-site scripting, missing authentication, and missing authorization. See the CWE/SANS top 25 or OWASP Top 10 for commonly used lists. Many books and courses are available to help you understand how to develop more secure software and discuss common implementation errors that lead to vulnerabilities. For example, the Secure Software Development Fundamentals course is a free set of three courses that explain how to develop more secure software (it's free if you audit it; for an extra fee you can earn a certificate to prove you learned the material).

    At least one primary developer is familiar with the classes of defect
    that lead to vulnerabilities in C++ libraries of this kind, and with
    means of countering them. The relevant classes for YODA, whose principal
    untrusted input is data files that users routinely exchange and download,
    and the mitigations applied, are:

    • Out-of-bounds reads and writes when parsing input (CWE-125,
      CWE-787): the codebase uses standard library containers and std::string
      rather than raw buffers and manual pointer arithmetic, so bounds are
      managed by the container rather than by hand.
    • Integer overflow in size and index calculations (CWE-190): values
      read from input that determine bin counts or dimensions are range-checked
      before use.
    • Uncontrolled resource consumption from malicious input (CWE-400,
      CWE-789): input that would imply implausible allocations is rejected
      rather than acted on.
    • Use-after-free and dangling references (CWE-416): object lifetimes
      are managed by RAII and smart pointers rather than manual
      allocation and deallocation.
    • Use of uninitialised memory (CWE-457): members are initialised at
      construction; the codebase is compiled with warnings enabled, which
      diagnoses many such cases.

    These are exercised by the automated test suite (94.6% line coverage) run
    in CI on every merge request.


  • Use basic good cryptographic practices

    Note that some software does not need to use cryptographic mechanisms. If your project produces software that (1) includes, activates, or enables encryption functionality, and (2) might be released from the United States (US) to outside the US or to a non-US-citizen, you may be legally required to take a few extra steps. Typically this just involves sending an email. For more information, see the encryption section of Understanding Open Source Technology & US Export Controls.

    The software produced by the project MUST use, by default, only cryptographic protocols and algorithms that are publicly published and reviewed by experts (if cryptographic protocols and algorithms are used). [crypto_published]
    These cryptographic criteria do not always apply because some software has no need to directly use cryptographic capabilities.


    If the software produced by the project is an application or library, and its primary purpose is not to implement cryptography, then it SHOULD only call on software specifically designed to implement cryptographic functions; it SHOULD NOT re-implement its own. [crypto_call]


    All functionality in the software produced by the project that depends on cryptography MUST be implementable using FLOSS. [crypto_floss]


    The security mechanisms within the software produced by the project MUST use default keylengths that at least meet the NIST minimum requirements through the year 2030 (as stated in 2012). It MUST be possible to configure the software so that smaller keylengths are completely disabled. [crypto_keylength]
    These minimum bitlengths are: symmetric key 112, factoring modulus 2048, discrete logarithm key 224, discrete logarithmic group 2048, elliptic curve 224, and hash 224 (password hashing is not covered by this bitlength, more information on password hashing can be found in the crypto_password_storage criterion). See https://www.keylength.com for a comparison of keylength recommendations from various organizations. The software MAY allow smaller keylengths in some configurations (ideally it would not, since this allows downgrade attacks, but shorter keylengths are sometimes necessary for interoperability).


    The default security mechanisms within the software produced by the project MUST NOT depend on broken cryptographic algorithms (e.g., MD4, MD5, single DES, RC4, Dual_EC_DRBG), or use cipher modes that are inappropriate to the context, unless they are necessary to implement an interoperable protocol (where the protocol implemented is the most recent version of that standard broadly supported by the network ecosystem, that ecosystem requires the use of such an algorithm or mode, and that ecosystem does not offer any more secure alternative). The documentation MUST describe any relevant security risks and any known mitigations if these broken algorithms or modes are necessary for an interoperable protocol. [crypto_working]
    ECB mode is almost never appropriate because it reveals identical blocks within the ciphertext as demonstrated by the ECB penguin, and CTR mode is often inappropriate because it does not perform authentication and causes duplicates if the input state is repeated. In many cases it's best to choose a block cipher algorithm mode designed to combine secrecy and authentication, e.g., Galois/Counter Mode (GCM) and EAX. Projects MAY allow users to enable broken mechanisms (e.g., during configuration) where necessary for compatibility, but then users know they're doing it.


    The default security mechanisms within the software produced by the project SHOULD NOT depend on cryptographic algorithms or modes with known serious weaknesses (e.g., the SHA-1 cryptographic hash algorithm or the CBC mode in SSH). [crypto_weaknesses]
    Concerns about CBC mode in SSH are discussed in CERT: SSH CBC vulnerability.


    The security mechanisms within the software produced by the project SHOULD implement perfect forward secrecy for key agreement protocols so a session key derived from a set of long-term keys cannot be compromised if one of the long-term keys is compromised in the future. [crypto_pfs]


    If the software produced by the project causes the storing of passwords for authentication of external users, the passwords MUST be stored as iterated hashes with a per-user salt by using a key stretching (iterated) algorithm (e.g., Argon2id, Bcrypt, Scrypt, or PBKDF2). See also OWASP Password Storage Cheat Sheet. [crypto_password_storage]
    This criterion applies only when the software is enforcing authentication of users using passwords for external users (aka inbound authentication), such as server-side web applications. It does not apply in cases where the software stores passwords for authenticating into other systems (aka outbound authentication, e.g., the software implements a client for some other system), since at least parts of that software must have often access to the unhashed password.


    The security mechanisms within the software produced by the project MUST generate all cryptographic keys and nonces using a cryptographically secure random number generator, and MUST NOT do so using generators that are cryptographically insecure. [crypto_random]
    A cryptographically secure random number generator may be a hardware random number generator, or it may be a cryptographically secure pseudo-random number generator (CSPRNG) using an algorithm such as Hash_DRBG, HMAC_DRBG, CTR_DRBG, Yarrow, or Fortuna. Examples of calls to secure random number generators include Java's java.security.SecureRandom and JavaScript's window.crypto.getRandomValues. Examples of calls to insecure random number generators include Java's java.util.Random and JavaScript's Math.random.

  • Secured delivery against man-in-the-middle (MITM) attacks


    The project MUST use a delivery mechanism that counters MITM attacks. Using https or ssh+scp is acceptable. [delivery_mitm]
    An even stronger mechanism is releasing the software with digitally signed packages, since that mitigates attacks on the distribution system, but this only works if the users can be confident that the public keys for signatures are correct and if the users will actually check the signature.

    Distribution channels use HTTPS exclusively. [osps_br_03_02]



    A cryptographic hash (e.g., a sha1sum) MUST NOT be retrieved over http and used without checking for a cryptographic signature. [delivery_unsigned]
    These hashes can be modified in transit.

    The project does not retrieve cryptographic hashes over HTTP. YODA's build system does not download dependencies at build time; all sources, including the bundled Eigen3, are contained in the source tree or supplied by the user's own installation. The source repository is served over HTTPS from GitLab, and release tarballs are distributed over HTTPS from the project website.


  • Publicly known vulnerabilities fixed


    There MUST be no unpatched vulnerabilities of medium or higher severity that have been publicly known for more than 60 days. [vulnerabilities_fixed_60_days]
    The vulnerability must be patched and released by the project itself (patches may be developed elsewhere). A vulnerability becomes publicly known (for this purpose) once it has a CVE with publicly released non-paywalled information (reported, for example, in the National Vulnerability Database) or when the project has been informed and the information has been released to the public (possibly by the project). A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known. Note: this means that users might be left vulnerable to all attackers worldwide for up to 60 days. This criterion is often much easier to meet than what Google recommends in Rebooting responsible disclosure, because Google recommends that the 60-day period start when the project is notified even if the report is not public. Also note that this badge criterion, like other criteria, applies to the individual project. Some projects are part of larger umbrella organizations or larger projects, possibly in multiple layers, and many projects feed their results to other organizations and projects as part of a potentially-complex supply chain. An individual project often cannot control the rest, but an individual project can work to release a vulnerability patch in a timely way. Therefore, we focus solely on the individual project's response time. Once a patch is available from the individual project, others can determine how to deal with the patch (e.g., they can update to the newer version or they can apply just the patch as a cherry-picked solution).

    No vulnerabilities have been publicly reported against YODA, and no CVEs have been assigned to the project, so there are none unpatched. The project undertakes to fix any that are reported within the timescales set out in SECURITY.md.



    Projects SHOULD fix all critical vulnerabilities rapidly after they are reported. [vulnerabilities_critical_fixed]

    No critical vulnerabilities have been reported against YODA. The project's published policy in SECURITY.md commits to acknowledging reports within 14 days and issuing fixes in the next release, and the private reporting address reaches multiple maintainers so that reports are not dependent on any single person's availability.


  • Other security issues


    The public repositories MUST NOT leak a valid private credential (e.g., a working password or private key) that is intended to limit public access. [no_leaked_credentials]
    A project MAY leak "sample" credentials for testing and unimportant databases, as long as they are not intended to limit public access.

    The repository contains no credentials intended to limit public access. YODA is an offline library requiring no authentication, network access or external services, so no such credentials exist to leak. CI authentication uses GitLab's masked project variables rather than values committed to the repository.


 Analysis 0/8

  • Static code analysis


    At least one static code analysis tool (beyond compiler warnings and "safe" language modes) MUST be applied to any proposed major production release of the software before its release, if there is at least one FLOSS tool that implements this criterion in the selected language. [static_analysis]
    A static code analysis tool examines the software code (as source code, intermediate code, or executable) without executing it with specific inputs. For purposes of this criterion, compiler warnings and "safe" language modes do not count as static code analysis tools (these typically avoid deep analysis because speed is vital). Some static analysis tools focus on detecting generic defects, others focus on finding specific kinds of defects (such as vulnerabilities), and some do a combination. Examples of such static code analysis tools include cppcheck (C, C++), clang static analyzer (C, C++), SpotBugs (Java), FindBugs (Java) (including FindSecurityBugs), PMD (Java), Brakeman (Ruby on Rails), lintr (R), goodpractice (R), Coverity Quality Analyzer, SonarQube, Codacy, and HP Enterprise Fortify Static Code Analyzer. Larger lists of tools can be found in places such as the Wikipedia list of tools for static code analysis, OWASP information on static code analysis, NIST list of source code security analyzers, and Wheeler's list of static analysis tools. If there are no FLOSS static analysis tools available for the implementation language(s) used, you may select 'N/A'.


    It is SUGGESTED that at least one of the static analysis tools used for the static_analysis criterion include rules or approaches to look for common vulnerabilities in the analyzed language or environment. [static_analysis_common_vulnerabilities]
    Static analysis tools that are specifically designed to look for common vulnerabilities are more likely to find them. That said, using any static tools will typically help find some problems, so we are suggesting but not requiring this for the 'passing' level badge.


    All medium and higher severity exploitable vulnerabilities discovered with static code analysis MUST be fixed in a timely way after they are confirmed. [static_analysis_fixed]
    A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known. Note that criterion vulnerabilities_fixed_60_days requires that all such vulnerabilities be fixed within 60 days of being made public.


    It is SUGGESTED that static source code analysis occur on every commit or at least daily. [static_analysis_often]

  • Dynamic code analysis


    It is SUGGESTED that at least one dynamic analysis tool be applied to any proposed major production release of the software before its release. [dynamic_analysis]
    A dynamic analysis tool examines the software by executing it with specific inputs. For example, the project MAY use a fuzzing tool (e.g., American Fuzzy Lop) or a web application scanner (e.g., OWASP ZAP or w3af). In some cases the OSS-Fuzz project may be willing to apply fuzz testing to your project. For purposes of this criterion the dynamic analysis tool needs to vary the inputs in some way to look for various kinds of problems or be an automated test suite with at least 80% branch coverage. The Wikipedia page on dynamic analysis and the OWASP page on fuzzing identify some dynamic analysis tools. The analysis tool(s) MAY be focused on looking for security vulnerabilities, but this is not required.


    It is SUGGESTED that if the software produced by the project includes software written using a memory-unsafe language (e.g., C or C++), then at least one dynamic tool (e.g., a fuzzer or web application scanner) be routinely used in combination with a mechanism to detect memory safety problems such as buffer overwrites. If the project does not produce software written in a memory-unsafe language, choose "not applicable" (N/A). [dynamic_analysis_unsafe]
    Examples of mechanisms to detect memory safety problems include Address Sanitizer (ASAN) (available in GCC and LLVM), Memory Sanitizer, and valgrind. Other potentially-used tools include thread sanitizer and undefined behavior sanitizer. Widespread assertions would also work.


    It is SUGGESTED that the project use a configuration for at least some dynamic analysis (such as testing or fuzzing) which enables many assertions. In many cases these assertions should not be enabled in production builds. [dynamic_analysis_enable_assertions]
    This criterion does not suggest enabling assertions during production; that is entirely up to the project and its users to decide. This criterion's focus is instead to improve fault detection during dynamic analysis before deployment. Enabling assertions in production use is completely different from enabling assertions during dynamic analysis (such as testing). In some cases enabling assertions in production use is extremely unwise (especially in high-integrity components). There are many arguments against enabling assertions in production, e.g., libraries should not crash callers, their presence may cause rejection by app stores, and/or activating an assertion in production may expose private data such as private keys. Beware that in many Linux distributions NDEBUG is not defined, so C/C++ assert() will by default be enabled for production in those environments. It may be important to use a different assertion mechanism or defining NDEBUG for production in those environments.


    All medium and higher severity exploitable vulnerabilities discovered with dynamic code analysis MUST be fixed in a timely way after they are confirmed. [dynamic_analysis_fixed]
    If you are not running dynamic code analysis and thus have not found any vulnerabilities in this way, choose "not applicable" (N/A). A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known.


This data is available under the Community Data License Agreement – Permissive, Version 2.0 (CDLA-Permissive-2.0). This means that a Data Recipient may share the Data, with or without modifications, so long as the Data Recipient makes available the text of this agreement with the shared Data. Please credit Christian Gutschow and the OpenSSF Best Practices badge contributors.

Project badge entry owned by: Christian Gutschow.
Entry created on 2026-08-06 18:55:37 UTC, last updated on 2026-08-06 21:29:54 UTC.