Better Scientific Software

a tutorial presented at

Improving Scientific Software

on 9:00 am - 11:20 am and 1:20 pm - 3:40 pm MDT (UTC-6) Thursday 7 April 2022

Presenters: David E. Bernholdt (Oak Ridge National Laboratory), Rinku K. Gupta (Argonne National Laboratory), Patricia A. Grubel (Los Alamos National Laboratory), and David M. Rogers (Oak Ridge National Laboratory)

Helpers: Anshu Dubey (Argonne National Laboratory) and Gregory R. Watson (Oak Ridge National Laboratory)

This page provides detailed information specific to the tutorial event above. Expect updates to this page up to, and perhaps shortly after, the date of the tutorial. Pages for other tutorial events can be accessed from the main page of this site.

Quick Links

Description

Producing scientific software is a challenge. The high-performance modeling and simulation community, in particular, is dealing with the confluence of disruptive changes in computing architectures and new opportunities (and demands) for greatly improved simulation capabilities, especially through coupling physics and scales. At the same time, computational science and engineering (CSE), as well as other areas of science, are experiencing increasing focus on scientific reproducibility and software quality.

Computer architecture changes require new software design and implementation strategies, including significant refactoring of existing code. Reproducibility demands require more rigor across the entire software endeavor. Code coupling requires aggregate team interactions including integration of software processes and practices. These challenges demand large investments in scientific software development and improved practices. Focusing on improved developer productivity and software sustainability is both urgent and essential.

This tutorial distills experience from members of the IDEAS Productivity project and the creators of the BSSw.io community website drawn from many scientific software projects over many years. The tutorial will provide information about software practices, processes, and tools explicitly tailored for CSE. Topics to be covered include: Agile methodologies and tools, software design and refactoring, testing and continuous integration, Git workflows for teams, and reproducibility. Material will be mostly at the beginner and intermediate levels. There will also be opportunities to discuss topics raised by the audience.

Learning Objectives

Participants should be able to…

Describe a range of methods and strategies to improve software development processes, working towards better developer productivity, software sustainability, and scientific reproducibility.
Be able to customize an approach for tailoring software development processes to the particulars of your project team and explain software value-related trade-offs.
Increase motivation, inspiration, and awareness of resources to help you in working towards producing better scientific software, and thus better scientific outcomes, in your own projects.

Agenda

This tutorial comprises two conference sessions. The first session, 9:00am-11:20am MDT, will be a series of presentations. The second session, 1:20pm-3:40pm MDT, will be more open-ended, depending on the interests of the participants. There will be opportunities to:

Gain some experience with hands-on activities the presentations (guided or independent);
Deeper Q&A based on the presentations; or
Discussion of experiences and challenges with software development faced by participants in their own projects.

We will use Zoom breakout rooms to be able to accommodate multiple interests in so far as we can staff them.

Time (MDT)	Module	Title	Presenter
9:00 AM	0	Introduction and Setup	David E. Bernholdt (ORNL)
9:05 AM	1	Motivation and Overview of Best Practices in HPC Software Development	Rinku K. Gupta (ANL)
9:15 AM	2	Agile Methodologies	Patricia A. Grubel (LANL)
9:45 AM	3	Git Workflows	Patricia A. Grubel (LANL)
10:00 AM		Break
10:20 AM	4	Software Testing Introduction	Rinku K. Gupta (ANL)
10:40 AM	5	Scientific Software Design	David E. Bernholdt (ORNL)
11:00 AM	6	Testing Complex Software	Rinku K. Gupta (ANL)
11:15 AM		Q&A
11:20 AM		Adjourn morning session
11:20 AM		Other conference activities
1:20 PM	7	Refactoring Scientific Software	David M. Rogers (ORNL)
1:45 PM	8	Improving Reproducibility Through Better Software Practices	David M. Rogers (ORNL)
2:00 PM	9	Summary	David M. Rogers (ORNL)
2:05 PM		Hands-on & Discussion (optional)
2:20 PM		Break
2:40 PM		Hands-on & Discussion (optional)
3:40 PM		Adjourn

Presentation Slides

The latest version of the slides will always be available at https://doi.org/10.6084/m9.figshare.19416767.

Note that these files may include additional slides that will not be discussed during the tutorial, but questions are welcome.

How to Participate

Please use Zoom chat or unmute to ask questions at any time. We will respond in chat or verbally as opportunities permit.
We will be available during the break for Q&A or further discussion.
We have an afternoon session for the tutorial which will allow you to try the hands-on activities, ask questions from the presentations or have discussion of experiences and challenges with software development faced by participants in their own projects.

Hands-On Exercises

Introduction

The hands-on exercises for this tutorial are based around a simple numerical model using the one-dimensional heat equation. The example is described briefly in the repository’s README file, and in greater detail in the ATPESC Hands-On lesson. The ATPESC version focuses on the numerical aspects of the model.

But for this tutorial, we’re focused on how to make the software better from a quality perspective, so you don’t need to understand the math to do these exercises.

For the purposes of these hands-on exercises, you should imagine you’ve inherited an early version of the hello-numerical-world software from a colleague who’s left the project, and you’ve been assigned to get it into better shape so that it can be used in the next ATPESC summer school.

The repository you’ll be working with is: bssw-tutorial/hello-numerical-world-2022-04-07-iss.

Note: most of the screenshots will refer to the generic “hello-numerical-world” repository rather than the one specifically for this event.

List of Hands-On Exercises

Note that not every presentation module has exercises (yet).

Setting up the Prerequisites. Setup the accounts needed for these exercises.
Agile Methodologies. You’ll use GitHub issues and project boards to setup a simple “personal kanban” board.
Basic Git for Collaboration. You’ll fork our hello-numerical-world repository, create a feature branch, and make a pull request
Software Testing. You’ll use an example project to try out using test driven development to add new functionality to a project
Refactoring Scientific Software. You’ll perform a small, well-defined refactoring exercise

There are also activities associated with a couple of modules that we didn’t have time to cover in this tutorial. You are welcome to try them out too.

Agile Redux. You’ll create epic, story, and task issues for the refactoring task and track them on a kanban board
Continuous Integration. You’ll establish a simple continuous integration workflow and then refine it, adding code coverage assessment

Stay in Touch

After the tutorial please feel free to email questions or feedback to the BSSw tutorial team at bssw-tutorial@lists.mcs.anl.gov.
If you want to do the hands-on exercises, we’re happy to provide feedback on your pull requests and issues, even after the end of the tutorial.
To find out about future events organized by the IDEAS Productivity Project, you can subscribe to our mailing list (usually ~2 messages/month).
For monthly updates on the Better Scientific Software site, subscribe to our monthly digest.

Resources from Presentations

Links from the tutorial presentations are listed here for convenience

Module 0: Introduction and Setup
- IDEAS Productivity Project
  - IDEAS Productivity mailing list
- Better Scientific Software site
  - BSSw Digest
  - RSS Feed
- The IDEAS report
- Write to the tutorial authors
- Inclusive Naming Initiative
- Bssw.io resource on Inclusive Naming
Module 1: Motivation and Overview of Best Practices in HPC Software Development
Module 2: Agile Methodologies
Module 3: Git Workflows
- Atlassian/BitBucket (Comparing Workflows)
- How to code review in a Pull Request
- Testing and Code Review Practices in Research Software Development (webinar) (previously linked to ~~ideas-productivity.org/events/hpc-best-practices-webinars/#webinar044~~)
- Git Flow (Driessen’s Original Blog)
  - Git extensions
- GitHub Flow (previously linked to ~~scottchacon.com/2011/08/31/github-flow.html~~)
- GitLab Flow (previously linked to ~~docs.gitlab.com/ee/topics/gitlab_flow.html~~)
- Trilinos
- Open MPI
- FleCSI
Module 4: Software Testing Introduction
- In the face of uncertainties, NNSA seeks verification and validation
- Python Build and Test Framework: pyscaffold.org
- Build-Link-Test CMake Framework: llnl-blt.readthedocs.io
- Static Source Analysis (C++): clang-tidy
- Static Source Analysis (python): flake8 and pylint
- Code Coverage Webservices: codecov and coveralls
- Tutorials for code coverage: Online Tutorial, Another example
- Development Practices Survey Article
- CMake Tutorial
- CMake add-test command documentation
- Verification and Validation in Scientific Computing
- Working Effectively with Legacy Code
Module 5: Scientific Software Design
Module 6: Testing Complex Software
- Useful resources on testing (formerly linked to ~~ideas-productivity.org/resources/howtos/~~)
- Related articles:
  - Methodology for Building Granular Testing in Multicomponent Scientific Software
  - Ongoing verification of a multiphysics community code: FLASH
Module 7: Refactoring Scientific Software
- AMReX
- Related article: Distillation of Best Practices from Refactoring FLASH for Exascale
- Related Presentation
Module 8: Improving Reproducibility Through Better Software Practices
- Motivations and Background:
- Definitions, Guidelines, and Organizations:
- Helpful Tools
  - Floating Point Analysis Tools
  - Code Ocean (Cloud platforms - publish and reproduce research code and data)
  - DOIs and hosting of data, code, documents:
    - Zenodo
    - FigShare
- Other Resources:
Module 9: Summary

Requested Citation

The requested citation the overall tutorial is:

David E. Bernholdt, Rinku K. Gupta, Patricia A. Grubel, and David M. Rogers, Better Scientific Software tutorial, in Improving Scientific Software, online, 2022. DOI: 10.6084/m9.figshare.19416767.

Individual modules may be cited as Speaker, Module Title, in Better Scientific Software tutorial…

Acknowledgements

This tutorial is produced by the IDEAS Productivity project.

This work was supported by the U.S. Department of Energy Office of Science, Office of Advanced Scientific Computing Research (ASCR), and by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.