Experimenting with LLMs for Developer Productivity
An experiment tested LLMs' ability to improve code coverage through unit tests, no-cost tools like ChatGPT were used but required human intervention for success.
Mutation Testing in C#.NET with Stryker
Code coverage is important for measuring test thoroughness but may not guarantee test quality.
Mutation score is a valuable KPI to assess test effectiveness by measuring how well tests detect and eliminate mutations.
Experimenting with LLMs for Developer Productivity
An experiment tested LLMs' ability to improve code coverage through unit tests, no-cost tools like ChatGPT were used but required human intervention for success.
Mutation Testing in C#.NET with Stryker
Code coverage is important for measuring test thoroughness but may not guarantee test quality.
Mutation score is a valuable KPI to assess test effectiveness by measuring how well tests detect and eliminate mutations.
Python Test | 218: Balancing test coverage with test costs - Nicole Tietz-Sokolskaya
Balancing schedule and testing is crucial in decision-making.
Deciding what and how much to test impacts coverage and effectiveness.
Refactoring can affect code coverage; focusing on key features is essential for effective testing.
New version of Publish Code Coverage Results task - Azure DevOps Blog
The V2 version of the publish code coverage results task in Azure Pipelines offers support for more formats of code coverage results and programming languages.
Users are encouraged to migrate from the V1 task to the V2 task to take advantage of new features and support for additional code coverage result formats.
Looking beyond code coverage with Amazon CodeWhisperer | Amazon Web Services
Code coverage is a code quality metric that often focuses on meeting a coverage threshold rather than improving code quality.
Using tools like Amazon CodeWhisperer can help generate test cases, including boundary conditions, to improve code quality and productivity.
Coverage at a crossroads
Coverage.py is undergoing changes to reduce execution-time overhead, causing complexity in maintaining coverage accuracy.