CT-AI · Question #107
There is a growing backlog of unresolved defects for your project. You know the developers have an ML model that they have created which has learned which developers work on which type of software…
The correct answer is B. Use it to assign defects to the best developer to resolve the problem and to load balance the. The syllabus explains that ML models can be used to analyze reported defects and suggest which developers are best suited to fix them based on historical data about defect assignment and resolution speed: "Assignment: ML models can suggest which developers are best suited to…
Question
There is a growing backlog of unresolved defects for your project. You know the developers have an ML model that they have created which has learned which developers work on which type of software and the speed with which they resolve issues. How could you use this model to help reduce the backlog and implement more efficient defect resolution?
Options
- AUse it to prioritize defects automatically based on the time expected for the fix to be made, the
- BUse it to assign defects to the best developer to resolve the problem and to load balance the
- CUse it to determine the root cause of each defect and develop a process improvement plan that
- DUse it to review the code and determine where more defects are likely to occur so that testing can
How the community answered
(50 responses)- A4% (2)
- B76% (38)
- C14% (7)
- D6% (3)
Explanation
The syllabus explains that ML models can be used to analyze reported defects and suggest which developers are best suited to fix them based on historical data about defect assignment and resolution speed: "Assignment: ML models can suggest which developers are best suited to fix particular defects, based on the defect content and previous developer assignments."
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