CTFL_Syll_4.0 Exam Dumps : ISTQB Certified Tester Foundation Level (CTFL) v4.0

Statement coverage, also known as line coverage, is a metric used in white-box testing to measure the percentage of executable statements in the source code that have been executed by the test suite. Achieving a certain percentage of statement coverage means that an equivalent percentage of the executable statements in the code have been executed during testing.

For example, achieving 80% statement coverage indicates that 80% of the lines of code have been run through during the testing process. This metric helps in identifying parts of the code that have not been tested and may contain undetected defects.

It's important to note that achieving high statement coverage does not necessarily guarantee that all possible paths or scenarios within the code are tested, nor does it ensure the detection of all types of defects. Other coverage metrics, such as branch coverage or condition coverage, might also be necessary to achieve a more thorough testing process.

Test automationimproves efficiency and accuracy, butit does NOT eliminate manual testing (D).

(A) is correctbecause automationspeeds up execution.

(B) is correctas automated tests produceconsistent and unbiased results.

(C) is correctbecause automationreduces human errors in repetitive tests.

However,manual testing remains essential for exploratory testing, usability testing, and complex test scenarios.

Exploratory testing is an experience-based testing technique where test design and test execution occur simultaneously. It is characterized by the tester actively exploring the application, using their intuition and experience to uncover defects. Exploratory testing sessions are often guided by test charters, which are brief documents outlining the test objectives, scope, and areas to be explored during the session.

These test charters provide a flexible framework that directs the tester's exploration without being overly prescriptive, allowing testers to adapt and investigate new areas as they uncover issues. This approach is particularly useful in dynamic and complex systems where predefined test cases might not cover all scenarios.