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“Static Analysis: J.S. Moeller LF Live Mentor Series” refers to the Linux Foundation’s recorded session Static Analysis & Tools, presented by Jan-Simon Möller on January 27, 2021. The roughly 45-minute presentation, followed by about 45 minutes of Q&A, introduces static analysis and surveys Linux and open-source tools, with examples of integrating checks into builds and Git workflows. The official event page has the recording and slides.
Session details
- Official title: Static Analysis & Tools: Using Linux and Open Source Tools for Static Analysis
- Presenter: Jan-Simon Möller, identified in the slides as Release Manager of Automotive Grade Linux
- Series: LF Live: Mentorship Series
- Recorded: January 27, 2021
- Format: Approximately 45 minutes of presentation and 45 minutes of Q&A
- Materials: Official recording and event page; 41-page slide deck
“J.S. Moeller” is an abbreviated, filename-style reference to the presenter. The official materials spell his name Jan-Simon Möller. This is a recorded webinar, not an article, and its commands are examples from 2021 rather than guaranteed instructions for every current toolchain.
What the session means by static analysis
The slide deck describes static analysis as examining code before it runs, often against rules or through a parsed or intermediate representation. Dynamic analysis observes a program while it executes. The distinction is useful, but neither approach covers everything:
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|---|---|
| Examines source code or a representation of it without running the program. | Observes behavior during execution, such as a test or production run. |
| Can report some defects before a test reaches the relevant code path. | Can expose failures and behavior that depend on actual runtime conditions. |
| May report paths that are difficult to reproduce, but can also produce findings that need human review. | Can miss problems on paths the tests or workload never execute. |
A clean analyzer run is not proof that code is correct or secure. Static checks complement tests, review, fuzzing, sanitizers, and other runtime methods; they do not replace them.
#1 Best Overall
Why use static analysis?
Möller’s presentation frames analysis as a way to find defects earlier, catch subtle problems such as invalid or undefined accesses, support peer review, and check coding rules. It also notes its relevance in safety- and compliance-sensitive fields including automotive, aviation, medical, and nuclear work. These uses should not be conflated: finding a null dereference is a technical result, while satisfying a particular standard or demonstrating regulatory compliance requires a broader, documented assurance process.
Tools covered in the presentation
The deck surveys several kinds of tools rather than establishing a current ranking. It names GCC, Clang, Cppcheck, Coccinelle, Splint, RATS, Flawfinder, and CodeChecker. For Linux kernel work, it also points to scripts/checkpatch.pl for basic style and submission checks, along with Sparse, Coccinelle, Smatch, and compiler analyzers.
- Compiler-based examples: GCC’s analyzer and Clang’s Static Analyzer tooling.
- General C/C++ analysis: Cppcheck and CodeChecker, among others listed in the slides.
- Kernel-oriented checks: Sparse, Coccinelle, Smatch, and
checkpatch.pl; kernel workflows differ from ordinary userspace builds. - Rule- and security-focused examples: Flawfinder and other tools in the deck’s broader survey.
Choose tools for the language, build system, analysis needs, project scale, and reporting workflow. A kernel-specific checker may understand kernel conventions better than a general-purpose tool, while a kernel workflow may be unnecessary complexity for a small userspace program. The 2021 slides do not provide a present-day comparison of maintenance, output formats, IDE support, or relative effectiveness, so they should not be used to rank tools in 2026.
Rank #2
The null-pointer example
To make analyzer output concrete, the deck uses a simple defect:
int *pointer = NULL;
int value = *pointer;The example assigns a null pointer and then dereferences it. The presentation shows Cppcheck, GCC analyzer, and Clang-based tooling identifying that relationship, though the wording and details of a report can differ by tool and version. Such a small example teaches the basic mechanism; production findings may involve longer paths, more files, and conditions that require investigation.
Commands from the 2021 slides
These examples are reproduced as historical references. Check the installed compiler and tool documentation, project configuration, and kernel tree before using them: paths, options, defaults, and build integration vary.
GCC analyzer
gcc -fanalyzerThe deck describes GCC’s analyzer as available starting with GCC 10 and lists diagnostics such as double close or free, resource leaks, possible null arguments or dereferences, tainted array indexes, use-after-free, and unsafe calls from signal handlers. Which diagnostics are available and emitted depends on compiler version, flags, and the code being analyzed.
Clang Static Analyzer
scan-build makeThe slide deck presents scan-build as a way to run analysis while observing compiler invocations in a build. It must be able to capture the relevant build commands. Generated sources, custom compiler wrappers, cross-compilation, and unusual build systems can require extra configuration or leave parts of the build unanalyzed.
Cppcheck
cppcheck nullpointer.cThe slides also show cppcheck --error-exitcode=1 $changed_files in a Git pre-commit pattern. The idea is to check staged, added or modified C/C++ files and return a failing status when findings are reported. A changed-file check is quick feedback, but it may miss defects whose causes or effects cross file boundaries.
Linux kernel build examples
make C=1 CHECK="/usr/bin/sparse"
make C=1 CHECK="scripts/coccicheck"
make C=1 CHECK="smatch -p=kernel"These are examples in the January 2021 deck, not universal commands for every kernel release or distribution. Kernel build configuration, installed tools, tool paths, and supported options matter; consult the documentation for the tree and tools you are using.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Putting analysis into a development workflow
The session’s practical emphasis is on running checks as part of builds and Git workflows. A durable setup adds feedback in layers rather than relying on one command or one gate:
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- Make the check reproducible. Provide a documented build target or script with the project’s compiler flags and configuration. Confirm that analysis sees generated files and the intended compiler, especially for cross-compilation.
- Give developers fast local feedback. A manual target or optional Git hook can catch obvious problems before a commit. Keep local checks short enough that contributors will use them.
- Run an authoritative CI check. Local hooks can be skipped, omitted, or bypassed; they are convenience, not enforcement. Run the agreed checks in CI and use repository protections if passing checks are required for merging.
- Control legacy findings deliberately. For an existing codebase, establish a reviewed baseline and make new or changed findings visible. Avoid treating a large backlog as a reason to disable the analyzer entirely.
- Triage reports. Assign ownership, prioritize by severity and context, and use narrow, documented suppressions when a finding is not actionable. Broad suppressions can hide real defects.
- Keep results useful. Preserve reports as CI artifacts when they help investigation, and review whether runtime and report volume are manageable for the project.
The slides include a pre-commit example that runs scan-build make -j2, then allows or rejects a commit based on the exit status. That illustrates the mechanism, not a universal policy: whether analyzer findings make a build fail depends on the tool’s exit behavior and project configuration. Validate it before relying on it as a gate.
Best Value
What remains useful—and what is dated
The session remains a useful introduction to the purpose of static analysis, the range of Linux and open-source tools, and the value of integrating checks into routine development. Its small defect example and workflow ideas are still easy to follow.
It was recorded in January 2021. Treat its tool versions, command lines, paths, and behavior as historical examples, not a current 2026 setup guide. The deck does not provide a modern comparison of CI or IDE integration, report formats such as SARIF, incremental-analysis workflows, or baseline management. Nor does it establish that a tool is currently maintained, best for a particular project, or sufficient for a safety or security claim.
Quick Recap
Where to watch and read
- Linux Foundation event page: Static Analysis & Tools
- Linux Foundation webinar page
- Official slide deck (PDF)
- LF Live: Mentorship Series archive
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