We all know that testing is an important part of software and systems development. The problem is that as our systems and applications grow, the amount of testing necessary increases at an exponential rate. Cris Medina joins us this week to talk about some of the problems and approaches associated with testing these complex systems and some of the ways that Python can help.
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- Your hosts as usual are Tobias Macey and Chris Patti
- Today we’re interviewing Cris Medina about test engineering for large and complex systems.
Interview with Cris Medina
- How did you get introduced to Python? – Chris
- To get us started can you share your definition of test engineering and how it differs from the types of testing that your average developer is used to? – Tobias
- What are some common industries or situations where this kind of test engineering becomes necessary? – Tobias
- How and where does Python fit into the kind of testing that becomes necessary when dealing with these complex systems? – Tobias
- How do you determine which areas of a system to test and how can Python help in that discovery process? – Tobias
- What are some of your favorite tools and libraries for this kind of work? – Tobias
- What are some of the areas where the existing Python tooling falls short? – Tobias
- Given the breadth of concerns that are encompassed with testing the various components of these large systems, what are some ways that a test engineer can get a high-level view of the overall state? – Tobias
- How can that information be distilled for presentation to other areas of the business? – Tobias
- Could that information be used to provide a compelling business case for the resources required to test properly? – Chris
- Given the low-level nature of this kind of work I imagine that proper visibility of the work being done can be difficult. How do you make sure that management can properly see and appreciate your efforts? – Tobias
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