Which ONE of the following would be the MOST effective input to an AI-based defect prediction tool?

The correct answer is B. Cyclomatic complexity. Cyclomatic complexity would be the most effective input to an AI-based defect prediction tool. Cyclomatic complexity is a software metric that measures the complexity of a program's control flow, which is closely related to the likelihood of defects. Higher complexity generally…

Specific Approaches to Testing AI-based Systems

Question

Options

ADevelopers associated with previous code changes
BCyclomatic complexity
CLines of code changed
DCommit size

How the community answered

(28 responses)

A
11% (3)
B
82% (23)
C
4% (1)
D
4% (1)

Explanation

Cyclomatic complexity would be the most effective input to an AI-based defect prediction tool. Cyclomatic complexity is a software metric that measures the complexity of a program's control flow, which is closely related to the likelihood of defects. Higher complexity generally indicates a higher probability of defects. This makes it a strong predictor of potential issues in the code, and thus a valuable input for defect prediction.

Topics

#defect prediction#cyclomatic complexity#code metrics#AI-based testing

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