Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

iSQI Exam CT-AI Topic 10 Question 11 Discussion

Actual exam question for iSQI's CT-AI exam
Question #: 11
Topic #: 10
[All CT-AI Questions]

Written requirements are given in text documents, which ONE of the following options is the BEST way to generate test cases from these requirements?

SELECT ONE OPTION

Show Suggested Answer Hide Answer
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:

Cathrine
10 months ago
A, definitely A. I mean, who needs fancy machine learning when you can just read the requirements and use your brain? It's the old-fashioned way, but it works!
upvoted 0 times
...
Lorrie
10 months ago
GUI analysis by computer vision? Sounds like something straight out of a sci-fi movie! I'll pass on that one.
upvoted 0 times
Cecilia
9 months ago
C) Machine learning on logs of execution
upvoted 0 times
...
Sharee
9 months ago
B) Analyzing source code for generating test cases
upvoted 0 times
...
Dierdre
10 months ago
A) Natural language processing on textual requirements
upvoted 0 times
...
...
Deja
10 months ago
Machine learning on logs? That's a bit overkill, don't you think? I'd stick with the good old natural language processing approach.
upvoted 0 times
...
Linwood
10 months ago
Option B sounds interesting, but I'm not sure how that would work if we don't have the actual source code yet. Seems a bit premature.
upvoted 0 times
Alva
10 months ago
C) Machine learning on logs of execution
upvoted 0 times
...
Cary
10 months ago
B) Analyzing source code for generating test cases
upvoted 0 times
...
Valene
10 months ago
A) Natural language processing on textual requirements
upvoted 0 times
...
...
Ellsworth
11 months ago
I think option A is the way to go. Natural language processing can really help us extract meaningful test scenarios from those written requirements.
upvoted 0 times
Emelda
10 months ago
I'm not sure about option D. GUI analysis by computer vision might be too complex for generating test cases.
upvoted 0 times
...
Filiberto
10 months ago
I'm leaning towards option C. Machine learning on logs of execution could help us identify patterns for test cases.
upvoted 0 times
...
Adelina
10 months ago
I think option B could also be useful. Analyzing the source code can give us insights into potential test cases.
upvoted 0 times
...
Effie
10 months ago
I agree, option A seems like the best choice. Natural language processing can help us understand the requirements better.
upvoted 0 times
...
...
Alecia
11 months ago
I think B) Analyzing source code for generating test cases is the most accurate method.
upvoted 0 times
...
Gretchen
11 months ago
I personally prefer D) GUI analysis by computer vision for generating test cases.
upvoted 0 times
...
Alba
11 months ago
I disagree, I believe C) Machine learning on logs of execution is more effective.
upvoted 0 times
...
Candra
11 months ago
I think the best way is A) Natural language processing on textual requirements.
upvoted 0 times
...

Save Cancel