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| Section | Objectives |
|---|---|
| Topic 1: Testing Quality Characteristics | - Functional Testing - Flexibility Testing - Usability Testing - Compatibility Testing |
| Topic 2: The Tasks of the Test Analyst in the Test Process | - Testing in the Software Development Lifecycle - Tasks Related to Work Products - Involvement in Test Activities |
| Topic 3: Software Defect Prevention | - Defect Prevention Practices - Supporting Phase Containment - Mitigating Recurrence of Defects |
| Topic 4: The Tasks of the Test Analyst in Risk-Based Testing | - Risk Control - Risk Analysis |
| Topic 5: Test Analysis and Test Design | - Rule-Based Test Techniques - Data-Based Test Techniques - Behavior-Based Test Techniques - Experience-based Testing |
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NEW QUESTION # 12
You are developing test cases for an application which performs complex calculations and have decided to model these calculations on a spreadsheet, to determine expected results from inputs.
Which solution to the test oracle problem BEST describes the approach you are using?
Answer: D
Explanation:
The correct answer is D . A spreadsheet model used to calculate expected results is best classified as a pseudo- oracle when it has been developed independently from the test object and is used to produce expected outcomes for comparison with the system under test. CTAL-TA v4.0 explains that a test oracle is needed to determine expected results in dynamic testing, and that the test oracle problem occurs when a cost-effective oracle is not readily available because of factors such as data-related complexity, non-determinism, probabilistic behavior, or ambiguous requirements. The syllabus identifies pseudo-oracles as independently developed systems that fulfill the same specification as the test object, including simplified versions of the test object.
Here, the application performs complex calculations, and the spreadsheet is being used as an independent calculation model to determine expected results from the same inputs. That is the classic pseudo-oracle pattern. Option A is wrong because property-based testing verifies general input/output properties rather than exact expected calculation results. Option B is wrong because metamorphic testing checks relations between source and follow-up test cases, not a full expected result from a spreadsheet. Option C is not the named CTAL-TA oracle solution being used here. Reference: CTAL-TA v4.0, Section 1.3.4 Determining Test Oracles .
NEW QUESTION # 13
You are working on a project to build a purchasing system. The main requirements for the system are that it shall:
* Allow users to enter details of items that they wish to have purchased and, from these details, create a purchase request.
* Take each purchase request through a workflow that will allow the requestor's line manager to approve the request, reject it or return it for clarification / modification.
* Forward approved requests to the Purchasing Department.
* Allow purchasers to find the best available supplier for each approved request and place the request on that supplier as a purchase order.
The solution is being developed according to the company's traditional V-model methodology. The requirements are clearly documented and include a business process model. Operational profiles have been created to guide performance testing.
Initial item entry will involve a check that each item entered exists on the master stock file and that the user is entitled to request it; this depends on user role and grade. Line manager authorization will be assisted by a recommendation made by the system according to relevant business rules, although the manager can override this recommendation. For approved requests, the workflow will continue to support the process through to placing of the purchase order.
Planning has begun for system testing and the Test Manager has asked you, the senior TA, to help with it.
What would be the MOST effective techniques for functional testing of this project?
a) Combinatorial testing
b) Random testing
c) CRUD testing
d) State transition testing
e) Scenario-based testing
f) Decision table testing
g) Exploratory testing
Answer: C
Explanation:
The correct answer is D because the scenario gives three strong test-basis signals: a workflow, a business process model, and business rules. CTAL-TA v4.0 classifies relevant black-box techniques into data-based, behavior-based, and rule-based techniques, and explicitly includes state transition testing, scenario-based testing, and decision table testing within Chapter 3 test analysis and design. It also requires the Test Analyst to select appropriate techniques for a given situation.
State transition testing fits the purchase request workflow because requests move between states such as created, approved, rejected, returned for clarification, forwarded, and converted to purchase order. CTAL-TA states that behavior-based techniques derive tests from state-dependent or dynamic behavior. Scenario-based testing fits because the requirements include a business process model and end-to-end purchasing flows.
CTAL-TA states that scenario-based testing evaluates behavior in realistic workflows and may use activity diagrams, use cases, flowcharts, or BPMN models. Decision table testing fits because entitlement checks and manager recommendations are driven by business rules involving role, grade, and authorization logic. Rule- based techniques verify stateless business-rule behavior.
Combinatorial testing may help with input combinations, but it is not the best overall functional set here.
Random and exploratory testing are weak choices because the requirements are clear and formal.
NEW QUESTION # 14
You have been assigned as Test Analyst on a project that will deliver quotes for motor insurance. The amount quoted depends upon the combined values of twelve variables, that are resolved by a set of business rules.
What should be your MAIN task during the test analysis activity?
Answer: D
Explanation:
The correct answer is C because the question asks for the main task during test analysis , not test implementation, execution, or regression maintenance. CTAL-TA v4.0 states that during test analysis the Test Analyst checks the completeness of the test basis, gathers additional information relevant for testing, evaluates the test basis for defects and testability, and may model system behavior according to the test techniques to be applied. It also states that the TA defines and prioritizes test conditions traceable to the test basis.
In this motor insurance quoting system, the critical test basis is the combination of twelve variables resolved by business rules. The Test Analyst therefore needs to model how the quote is produced, most likely using a rule-based or combinatorial technique depending on how the rules are structured. That modeling exposes test conditions such as valid rule combinations, boundary cases, conflicting rules, missing rules, and high-risk variable interactions.
Option A relates more to selecting tests for execution, not analysis. Option B is regression test selection or adaptation, which CTAL-TA places under design/maintenance activities for regression tests, not the main initial analysis task. Option D is feedback from prior execution activity and is not the central task when analyzing a new rule-driven quote engine. Reference: CTAL-TA v4.0, Sections 1.2.1 Test Analysis and 3 Test Analysis and Test Design .
NEW QUESTION # 15
A simple drinks machine is described in the following state transition diagram:
How many test cases will be needed for Chow's 1-switch coverage?
Answer: C
Explanation:
The correct answer is C , because Chow's 1-switch coverage requires every valid sequence of two consecutive transitions to be covered. CTAL-TA v4.0 states that N-switch coverage applies to valid sequences of N+1 consecutive transitions , and specifically defines a 1-switch as a pair of incoming and outgoing transitions at a state.
Count the possible incoming-transition/outgoing-transition pairs at each state:
* S1 has 2 incoming transitions: clear, take drink, and 2 outgoing transitions: coffee, tea.
So, 2 × 2 = 4 1-switches.
* S2 has 4 incoming transitions: coffee, tea, dispensed from sugar, dispensed from milk, and 4 outgoing transitions: clear, sugar, milk, vend.
So, 4 × 4 = 16 1-switches.
* S3 has 1 incoming transition and 1 outgoing transition: 1 × 1 = 1 .
* S4 has 1 incoming transition and 1 outgoing transition: 1 × 1 = 1 .
* S5 has 1 incoming transition and 1 outgoing transition: 1 × 1 = 1 .
Total = 4 + 16 + 1 + 1 + 1 = 23 .
Therefore, the minimum quantity needed for full Chow's 1-switch coverage is 23 . Reference: CTAL-TA v4.
0, Section 3.2.2 State Transition Testing , N-switch coverage.
NEW QUESTION # 16
You are working on a project to build a purchasing system. The main requirements for the system are that it shall:
* Allow users to enter details of items that they wish to have purchased and, from these details, create a purchase request.
* Take each purchase request through a workflow that will allow the requestor's line manager to approve the request, reject it or return it for clarification / modification.
* Forward approved requests to the Purchasing Department.
* Allow purchasers to find the best available supplier for each approved request and place the request on that supplier as a purchase order.
The solution is being developed according to the company's traditional V-model methodology. The requirements are clearly documented and include a business process model.
System testing has finished and the test manager has asked you, the senior TA, to identify any parts of the product that should be focused on during acceptance testing. The results of this may be used to adjust the acceptance test plan.
You are using defect cluster analysis, only counting defects with severity levels 1 to 3, ignoring low severity levels 4 and 5. Function point analysis was used for estimating, so you have used function points as the unit of size for the various functional areas of the product. No numeric estimates of expected defect quantities were made for them individually but, as a result of product risk analysis, these functional areas have been ranked according to the amount of product risk that was predicted in them, with risk ranking 1 being the highest and
5 the lowest; the thoroughness of the testing performed so far has been proportional to that. The results are presented in the table below.
Functional area
Total function points
Product risk ranking
Defects found
Purchase Request entry
2000
2
30
Purchase Request workflow
1500
4
15
Purchase Request authorisation
1000
5
25
Supplier identification
2000
1
30
Purchase Order creation
1000
3
30
Which functional areas would you recommend for more test focus in acceptance testing?
a) Purchase Request entry
b) Purchase Request workflow
c) Purchase Request authorization
d) Supplier Identification
e) Purchase Order creation
Answer: B
Explanation:
The correct answer is C because defect cluster analysis must not be based on raw defect counts alone. CTAL- TA v4.0 states that after testing, the Test Analyst can identify actual defect-prone areas and compare predicted versus actual defect clusters; where discrepancies appear, more rigorous testing may be needed in those areas.
Here, size must be normalized using function points. The defect densities are: Purchase Request entry 30
/2000 = 15 defects per 1000 FP , Purchase Request workflow 15/1500 = 10 defects per 1000 FP , Purchase Request authorization 25/1000 = 25 defects per 1000 FP , Supplier identification 30/2000 = 15 defects per
1000 FP , and Purchase Order creation 30/1000 = 30 defects per 1000 FP .
The strongest actual clusters are therefore Purchase Order creation and Purchase Request authorization .
This is even more significant because authorization had the lowest predicted product risk ranking, 5 , so it should not have produced such a high defect density if the original risk assessment and test focus were accurate. Purchase Order creation also shows the highest defect density despite only medium predicted risk, ranking 3. Supplier identification and Purchase Request entry both have 30 defects, but they are larger areas and have only 15 defects per 1000 function points; Supplier identification was also the highest predicted risk area, so more defects there are less surprising. Reference: CTAL-TA v4.0, Software Defect Prevention , test result analysis and predicted-versus-actual defect cluster analysis.
NEW QUESTION # 17
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