01
Build product and tool knowledge
The team worked with Squish, Python and Eclipse across Windows and Mac environments. Domain learning covered the product’s market-analysis behaviour.
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Case study
Building regression automation for market simulation software
A six-month engagement established an automated regression framework and test coverage for a US market-analysis product using Python and Squish.
- Client context
- A US market investment consulting software company
- Engagement
- 6 months
- Test automation
- Python and Squish
- Platforms
- Windows and Mac
The situation
The business need
The product simulated market behaviour using historical sales, advertising investment, product attributes and market positioning. Testers needed to understand both the application and the marketing concepts behind its results.
The GUI automation tooling was also new to the team. The engagement therefore required learning the product domain while establishing a practical automation framework.
The approach
How the team delivered
02
Maintain short feedback loops
Daily calls and online meetings exposed issues quickly and clarified changing requirements. Work was planned and delivered within agreed iterations.
03
Create repeatable regression checks
The team established the automated framework and regression scripts so builds and versions could be checked consistently.
Project context
Technology and delivery
Technologies and working practices used in this engagement.
PythonSquishRegression testingWindowsMac
The result
What the engagement delivered
A regression automation foundation
The team delivered a framework and broad regression coverage over the six-month engagement.
Repeatable product checks
Scripts supported consistent checks of stability across software versions.
A more efficient test process
The project included improved regression efficiency; it does not provide a numerical time-saving measurement.
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