Week 6: Pull Request and Peer Review

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Hello again!

Week 6 of my GSoC 2025 journey has been all about refinement, feedback, and forward momentum. I finally opened my long-standing pull request with the work done over the past three weeks. Here are more details around it.

The Pull Request

On July 7th, 2025, I submitted a pull request that encapsulated all the major changes and improvements I’ve worked on since Week 3. This included:

  • The updated LSODA package

  • A clean interface supporting both SBML input and direct ODEs

  • Multiple system-level tests for validation

  • Detailed exception handling for edge cases

  • Detailed method-level docstrings 

Once opened, the PR served as a starting point for deeper discussions with my mentors — not just about what’s working, but how things can be made even better.

SBMLTestSuite: Building the Test Bridge

As part of verifying LSODA’s reliability in a broader context, I started my work on testing the solver against the SBML Test Suite. I read the documentation and looked into few of the test cases. For testing ODE solvers, there are around 1800 semantic test cases in it containing various files within each case such as sbml files having the reaction details, settings file, results file, plots etc. An application named SBMLTestRunner is provided by SBML developers, which when passed a wrapper program can run the solver against all the test cases, save the results in a csv file and compare it with the expected results. Based on the comparison it marks the test case as green if it has been passed, red if the wrapper results do not matches with the expected result and black if any error is encountered while running the wrapper. It also provides plots for both the wrapper result and expected result side be side along with the difference between them.  

  • I’ve written the test runner wrapper that connects our solver to the suite.

  • Now, I’m in the process of executing these tests, collecting results, and identifying any inconsistencies or issues.

This will form the foundation of our benchmarking phase and is essential for validating the solver’s performance under varied biological models.

Mentor Meeting & Feedback

We had our weekly meeting on 10 July 2025. 

  • Dr. Dräger had already reviewed the PR and provided several suggestions for code clarity, design decisions, and best practices. We walked through his feedback and discussed ways to address them effectively.

  • Taichi shared his views, especially around how exceptions are structured and propagated throughout the solver pipeline. He suggested using Enums in place for numerical values for different cases within an exception.

  • Dr. Funahashi asked about the validity of system tests. I told him that I am using the answers from libLSODA as reference.

  • I shared a few improvements I had identified while working on the SBML Test Suite:

    • Most notably, I suggested overriding setAbsTol() and setRelTol() methods from the AdaptiveStepSizeIntegrator. This connects both the implementation and allows users to configure solver tolerances more easily. 

    • We also talked about how can we follow OOP principles more clearly throughout the codebase.

The discussions were highly productive and reflected how our team is not only focused on functionality but also maintainability and user experience.

Suggested Tasks Moving Forward

Based on this week’s discussion, my next steps are clear:

  • Incorporate all feedback shared by Dr. Dräger and Taichi into the PR.

  • Continue testing against the SBML Test Suite — with focus on analyzing result accuracy, model support, and logging potential discrepancies

As the project nears its mid-point, it’s becoming increasingly important to:

  • Ensure stability and clarity in the codebase.

  • Build confidence through formal testing and real-world benchmarks.

  • Refine usability, both for direct users and for SBML-based workflows.

We are trying our best and having thorough discussions to look over these points.

That’s all from me for Week 6 — a week of collaborative refinement and stepping into the testing arena with confidence.

Until next time,
Bye! 👋

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