Open b4yuan opened 1 year ago
CLA Assistant Lite bot:
Thank you for your submission, we really appreciate it. Like many open-source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution. You can sign the CLA by just posting a Pull Request Comment same as the below format.
I have read the CLA Document and I hereby sign the CLA
You can retrigger this bot by commenting recheck in this Pull Request
@kiram9 Pinging to check in on a possible followup to this PR?
Summary
This pull request introduces a CodeQL workflow to enhance the security analysis of this repository.
What is CodeQL
CodeQL is a static analysis tool that helps identify and mitigate security vulnerabilities. It is primarily intra-function but does provide some support for inter-function analysis. By integrating CodeQL into a GitHub Actions workflow, it can proactively identify and address potential issues before they become security threats.
For more information on CodeQL and how to interpret its results, refer to the GitHub documentation and the CodeQL documentation (https://codeql.github.com/ and https://codeql.github.com/docs/).
What this PR does
We added a new CodeQL workflow file (.github/workflows/codeql.yml) that
Validation
To validate the functionality of this workflow, we have run several test scans on the codebase and reviewed the results. The workflow successfully compiles the project, identifies issues, and provides actionable insights while reducing noise by excluding certain queries and third-party code.
Using the workflow results
If this pull request is merged, the CodeQL workflow will be automatically run on every push to the main branch and on every pull request to the main branch. To view the results of these code scans, follow these steps:
Is this a good idea?
We are researchers at Purdue University in the USA. We are studying the potential benefits and costs of using CodeQL on open-source repositories of embedded software.
We wrote up a report of our findings so far. The TL;DR is “CodeQL outperforms the other freely-available static analysis tools, with fairly low false positive rates and lots of real defects”. You can read about the report here: https://arxiv.org/abs/2310.00205
Review of engineering hazards
License: see the license at https://github.com/github/codeql-cli-binaries/blob/main/LICENSE.md:
False positives: We find that around 20% of errors are false positives, but that these FPs are polarized and only a few rules contribute to most FPs. We find that the top rules contributing to FPs are: cpp/uninitialized-local, cpp/missing-check-scanf, cpp/suspicious-pointer-scaling, cpp/unbounded-write, cpp/constant-comparison, and cpp/inconsistent-null-check. Adding a filter to filter out certain rules that contribute to a high FP rate can be done simply in the workflow file.