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iSQI Exam CT-AI Topic 8 Question 19 Discussion

Actual exam question for iSQI's CT-AI exam
Question #: 19
Topic #: 8
[All CT-AI Questions]

Which of the following is a dataset issue that can be resolved using pre-processing?

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Suggested Answer: A

When written requirements are given in text documents, the best way to generate test cases is by using Natural Language Processing (NLP). Here's why:

Natural Language Processing (NLP): NLP can analyze and understand human language. It can be used to process textual requirements to extract relevant information and generate test cases. This method is efficient in handling large volumes of textual data and identifying key elements necessary for testing.

Why Not Other Options:

Analyzing source code for generating test cases: This is more suitable for white-box testing where the code is available, but it doesn't apply to text-based requirements.

Machine learning on logs of execution: This approach is used for dynamic analysis based on system behavior during execution rather than static textual requirements.

GUI analysis by computer vision: This is used for testing graphical user interfaces and is not applicable to text-based requirements.


Contribute your Thoughts:

Adaline
5 hours ago
D) Numbers stored as strings seems like the obvious choice here. Pre-processing can definitely help with that issue.
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Glenna
5 days ago
I believe numbers stored as strings is also a dataset issue that can be resolved using pre-processing. Converting them to numerical values can help in analysis.
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Sanjuana
9 days ago
I agree with Crista. Invalid data can be cleaned up during pre-processing to improve the quality of the dataset.
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Crista
10 days ago
I think the dataset issue that can be resolved using pre-processing is invalid data.
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