Pass the ISTQB Advance Level CTAL-TTA Questions and answers with ValidTests

To achieve full Modified Condition/Decision Coverage (MC/DC), each condition within a decision must be shown to independently affect the outcome of the decision. For the decision IF X < 5 OR Y > 10 THEN, the conditions are:

Condition 1: X < 5

Condition 2: Y > 10

We need to test these conditions in such a way that each condition independently influences the decision outcome. Let's analyze the options:

Option A:

X=4 and Y=7 (X < 5 is true, Y > 10 is false; overall decision true)

X=6 and Y=12 (X < 5 is false, Y > 10 is true; overall decision true)

X=5 and Y=10 (X < 5 is false, Y > 10 is false; overall decision false)

This set achieves full MC/DC coverage because each condition is shown to independently affect the outcome.

Option B:

X=4 and Y=11 (X < 5 is true, Y > 10 is true; overall decision true)

X=7 and Y=10 (X < 5 is false, Y > 10 is false; overall decision false)

This set achieves full MC/DC coverage because it demonstrates both conditions independently affecting the outcome.

Option C:

X=5 and Y=8 (X < 5 is false, Y > 10 is false; overall decision false)

X=2 and Y=12 (X < 5 is true, Y > 10 is true; overall decision true)

X=4 and Y=4 (X < 5 is true, Y > 10 is false; overall decision true)

This set does not fully achieve MC/DC coverage as it does not demonstrate the impact of Y > 10 being false while X < 5 is false.

Option D:

X=3 and Y=10 (X < 5 is true, Y > 10 is false; overall decision true)

X=5 and Y=15 (X < 5 is false, Y > 10 is true; overall decision true)

X=0 and Y=15 (X < 5 is true, Y > 10 is true; overall decision true)

This set does not achieve MC/DC coverage because it does not show the decision outcome when both conditions are false.

Therefore, the correct answer is B. X=4 and Y=11, X=7 and Y=10.

Acceptance Test-Driven Development (ATDD) enhances both functional and non-functional aspects of the project, providing a collaborative approach to acceptance criteria that developers, testers, and stakeholders agree upon before development begins. Using ATDD alongside TDD (Test-Driven Development) ensures that both the internal system logic and the user-facing features adhere to the specified requirements, thereby increasing the likelihood of delivering a quality product that meets all stakeholders' expectations .

Dynamic analysis involves evaluating a system or component based on its behavior during execution. This type of analysis is particularly useful for identifying issues related to memory usage and pointer management. The focus is on runtime behaviors that can't be detected through static analysis alone.

Identifiable Issues via Dynamic Analysis:

System Memory Not Released (Memory Leaks):

System memory not released when it is no longer needed (Option C) can be identified through dynamic analysis. Tools and techniques used in dynamic analysis can track memory allocation and deallocation during program execution, revealing instances where memory is allocated but not freed properly.

Pointers in a Program (Dangling Pointers):

Pointers in a program that are no longer accurate and must not be used (Option D) can also be identified through dynamic analysis. This includes issues like dangling pointers (pointers that refer to memory that has been freed) or wild pointers (uninitialized pointers). Dynamic analysis tools can detect when pointers are used incorrectly or point to invalid memory locations during runtime.

Explanation of Incorrect Options:

A. Objects having too much or too little visibility into parent classes: This is more related to design and structure, typically identified via static analysis or code reviews rather than dynamic analysis.

B. Repetition of code within a single component or module: This is a code quality issue often detected through static code analysis or manual code review.

E. Code that cannot be reached and so will not be executed: This is typically identified through static analysis tools that perform code coverage analysis or by manual code inspection.

References:

Although specific references from the provided documents were not found directly related to dynamic analysis, the general understanding and standard practices of software testing support the answer given. For example, the ISTQB syllabus and various testing literature highlight memory management and pointer issues as typical concerns addressed through dynamic analysis.

Sources:

General knowledge on dynamic analysis in software testing.

ISTQB-CTAL-TTA Syllabus and standard practices in software testing.

Analysis:

For a system to meet its reliability requirements, it must maintain a mean time between failure (MTBF) of three months or longer and a mean time to repair (MTTR) of ten minutes or less. When planning and specifying reliability tests, several factors must be considered to ensure these requirements are met.

Key Factor:

B. Determining the target availability for the system:

Availability is a critical factor that encompasses both the MTBF and MTTR. Availability is calculated based on the uptime and downtime of the system, which directly correlates with MTBF and MTTR. Determining the target availability helps ensure that the system can meet the required reliability standards by specifying acceptable levels of uptime and downtime.

Explanation of Incorrect Options:

A. Defining the replaceability requirements:

Replaceability pertains to the ease with which components can be replaced or updated. While important for maintainability, it is not the primary focus for reliability testing in this context.

C. Monitoring reliability in production:

Monitoring in production is important for ongoing reliability assessment but is not a primary consideration when planning and specifying tests before release.

D. Configuring a production-like test environment:

This is essential for accurate testing but is a logistical consideration rather than a direct factor in the reliability requirements.

References:

The ISTQB CTAL-TTA syllabus and standard practices in reliability testing emphasize the importance of availability metrics in planning reliability tests.

Sources:

ISTQB-CTAL-TTA Syllabus

General knowledge on reliability testing and availability.

The epic described has broad and overarching objectives that span multiple user groups and stakeholders, making it inherently dependent on other functionalities within the same system. This fails the 'Independent' criterion of INVEST, which suggests features should be self-contained. Moreover, the epic's scope suggests it's quite large, likely requiring splitting into smaller, more manageable stories, thus not meeting the 'Small' criterion. INVEST aims for manageable, independent increments that can be developed and validated quickly .

Only one of the checklist items has been fulfilled in the Java function provided. Option C is correct.

Checklist Review:

Capitalization of Variables: The variable 'Number' does start with a capital letter, fulfilling this checklist item.

Capitalization of Output Messages: The output messages do not start with a capital letter following the prompt text (e.g., 'your input number...'), failing this checklist item.

Comment Line: There is no comment line explaining the purpose of the class or method, failing this checklist item.

Thus, only the requirement regarding the capitalization of the variable is met, indicating a partial adherence to the specified coding standards .

Multiple condition testing requires each possible combination of conditions to be tested, whereas modified condition/decision testing (MC/DC) requires each condition to be shown to independently affect the outcome. In the case of the ATM withdrawal, TC 3 (Customer does not have sufficient funds and credit has not been granted) would not result in the machine paying out, which is a result of applying multiple condition testing. However, for MC/DC, this test case would not be included because it doesn't provide an independent assessment of either condition's effect on the decision since both conditions are negative and the outcome is as expected (no payout).

100% statement coverage means that every line of code is executed at least once during testing. Based on the provided pseudo-code and the test cases given:

Test 1 executes the MIN = B statement when A and B are equal.

Test 2 executes the MIN = A statement and skips the inner IF since B is not equal to 2*A.

All statements within the code have been executed by these two tests, hence no additional test cases are needed to achieve 100% statement coverage.

To determine the percentage of decision testing coverage achieved by the given suite of test cases, we need to analyze the decisions and outcomes in the provided logic.

Detailed Analysis

Identify all decisions in the logic:

IF account number is valid

IF customer account is active

IF oldBalance < zero

IF balance now >= zero

IF account holder is VIP customer

Calculate the number of unique decisions:

There are 5 unique decision points in the logic.

Determine the possible outcomes for each decision:

IF account number is valid → 2 outcomes (True, False)

IF customer account is active → 2 outcomes (True, False)

IF oldBalance < zero → 2 outcomes (True, False)

IF balance now >= zero → 2 outcomes (True, False)

IF account holder is VIP customer → 2 outcomes (True, False)

Test Cases Analysis

Test Case A

Account number valid → True

Account is active → True

OldBalance = -100 → True (less than zero)

Balance now = +200 → True (greater than zero)

Not a VIP customer → False

Test Case B

Account number valid → True

Account is active → True

OldBalance = -100 → True (less than zero)

Balance now = -50 → False (less than zero)

Is a VIP customer → True

Coverage Calculation

To calculate the decision coverage, we need to see how many of the possible outcomes are covered by the test cases:

IF account number is valid (True in both A and B, False not tested)

IF customer account is active (True in both A and B, False not tested)

IF oldBalance < zero (True in both A and B, False not tested)

IF balance now >= zero (True in A, False in B, both outcomes tested)

IF account holder is VIP customer (False in A, True in B, both outcomes tested)

Out of the 10 possible outcomes (2 for each decision), the given test cases cover 6 outcomes:

Account number valid → True

Account number valid → False (not covered)

Customer account active → True

Customer account active → False (not covered)

OldBalance < zero → True

OldBalance < zero → False (not covered)

Balance now >= zero → True

Balance now >= zero → False

Account holder is VIP → True

Account holder is VIP → False

Thus, 6 out of the 10 outcomes are covered by the test cases, giving us a decision coverage percentage of:

Decision Coverage=(610)×100%=60%\text{Decision Coverage} = \left(\frac{6}{10}\right) \times 100\% = 60\%Decision Coverage=(106​)×100%=60%

References:

The sample questions and answers provided in the ISTQB CTAL-TTA documentation confirm this calculation method and the expected coverage percentage for similar logical scenarios​​​​​​.

The code provided contains a potential endless loop. The loop is conditioned on the variable 'E' being less than 1 (IF E < 1), but within the loop, there is no operation that modifies the value of 'E'. Therefore, once the loop is entered, if the condition A > B holds true, the value of 'E' remains unchanged, leading to an endless loop situation. The decrement of 'A' in line 15 does not guarantee an exit condition for the loop, as it does not affect the value of 'E'. This is a control flow defect that could cause the program to hang or crash.