Introduction to Software Testing

Software testing is the process of verifying and validating that code works as expected. The most granular level is unit testing, where each standalone unit in a code (e.g., function) is exercised to help ensure that it works correctly, even in edge and corner cases. Whether you write unit tests after your code is written or as you go, software tools exist to help make the testing process less manual and more systematic. This session will discuss some best practices for testing code and give participants a hands-on introduction to testing frameworks for interpreted (Python) and compiled languages (C/C++). Though the emphasis will be on unit testing, other forms of testing such as system tests, integration tests, and regression tests will be discussed.

Learning objectives:

Attendees will learn different high-level approaches to testing code and will get firsthand experience setting up and using automated testing frameworks.

Knowledge prerequisites:

Basic Linux and the Bash command-line. Some programming experience in Python and/or C++.

Hardware/software prerequisites:

Participants in any PICSciE virtual workshop need a Princeton Zoom account. For this session, users should also have an account on our Adroit cluster (another cluster like Tiger or Della is ok), and they should confirm that they can SSH into Adroit at least 48 hours beforehand. Details on connecting to Adroit can be found in the advance setup guide for PICSciE virtual workshops (https://researchcomputing.princeton.edu/learn/workshops-live-training/hardware-and-software-requirements-picscie-workshops).

Session format:

Lecture and hands-on

What to expect:
Single workshop (one-off workshop –" 2 hours total)

Meet the facilitator:
Jonathan Halverson is a research software and programming analyst with the Princeton Institute for Computational Science & Engineering (PICSciE) and Research Computing. He has an expertise in data science and he is a founding organizer of the TensorFlow & PyTorch User Group at Princeton. Prior to his current position, Jonathan performed polymer physics research at the Max Planck Institute for Polymer Research and nanoscience research at Brookhaven National Laboratory. He has a Ph.D. in Chemical Engineering from CUNY.

To request accommodations for this event, please contact the workshop or event facilitator at least 3 working days prior to the event.

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Co-hosted with: Research Computing

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