A mobile app start-up company is implementing an AI-based chat assistant for e-commerce customers. In the process of planning the testing, the team realizes that the specifications are insufficient.
Which testing approach should be used to test this system?
When testing an AI-based chat assistant for e-commerce customers, the lack of sufficient specifications makes it difficult to use structured test techniques. The ISTQB CT-AI Syllabus recommends exploratory testing in such cases:
Why Exploratory Testing?
Exploratory testing is useful when specifications are incomplete or unclear.
AI-based systems, particularly those using natural language processing (NLP), may not behave deterministically, making scripted test cases ineffective.
The tester interacts dynamically with the system, identifying unexpected behaviors not documented in the specification.
Analysis of Answer Choices:
A (Exploratory testing) Correct, as it is the best approach when specifications are incomplete.
B (Static analysis) Incorrect, as static analysis checks code without execution, which is not helpful for AI chatbots.
C (Equivalence partitioning) Incorrect, as this technique requires well-defined inputs and outputs, which are missing due to insufficient specifications.
D (State transition testing) Incorrect, as state-based testing requires knowledge of valid and invalid transitions, which is difficult with a chatbot lacking a clear specification.
Thus, Option A is the correct answer, as exploratory testing is the best approach when dealing with insufficient specifications in AI-based systems.
Certified Tester AI Testing Study Guide Reference:
ISTQB CT-AI Syllabus v1.0, Section 7.7 (Selecting a Test Approach for an ML System)
ISTQB CT-AI Syllabus v1.0, Section 9.6 (Experience-Based Testing of AI-Based Systems).
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