Welcome to Day 3 of my 30 day series on AI in Testing!
Yesterday, we talked about how AI is improving test automation, making it more intelligent and adaptable. Today, we’re going to look at something equally exciting how AI can help predict defects and assess risk in software. This is a huge time-saver and can help teams focus on areas where problems are most likely to occur.
Let’s get into how AI helps with predicting bugs and assessing risk so that we can improve the quality of our software before issues even arise.
Please checkout my other articles for AI in Testing Series
What is Defect Prediction?
In simple terms, defect prediction is the process of figuring out where bugs are most likely to happen in your software. Normally, teams rely on experience or intuition to decide which parts of the code need more testing, but this can be hit or miss.
AI changes the game by analysing data like
- Previous test results
- Bug reports
- Code complexity
- Code changes
