How can I optimize my Python code coverage using advanced techniques?
You can optimize your Python code coverage by using tools like coverage.py, and applying techniques such as branch coverage, mutation testing, and test case prioritization.
What is branch coverage and how does it help?
Branch coverage measures whether each branch of your code's control structures has been executed. It helps identify untested paths, ensuring more thorough testing.
Can you explain mutation testing?
Mutation testing involves modifying your code in small ways to create 'mutants' and then checking if your tests can catch these changes. It helps assess the effectiveness of your test suite.
What tools can I use for mutation testing in Python?
You can use tools like MutPy and Cosmic Ray for mutation testing in Python. They help automate the process and provide insights into your test coverage.
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