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| Section | Objectives |
|---|---|
| Topic 1: Software Defect Prevention | - Supporting Phase Containment - Mitigating Recurrence of Defects - Defect Prevention Practices |
| Topic 2: Testing Quality Characteristics | - Flexibility Testing - Functional Testing - Usability Testing - Compatibility Testing |
| Topic 3: 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 4: Test Analysis and Test Design | - Rule-Based Test Techniques - Experience-based Testing - Data-Based Test Techniques - Behavior-Based Test Techniques |
| Topic 5: The Tasks of the Test Analyst in Risk-Based Testing | - Risk Control - Risk Analysis |
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NEW QUESTION # 28
You are testing the functional correctness of an application which generates quotes for motor insurance. The amount of the quote is governed by a combination of the following factors:
* Type of Cover, can be: comprehensive, third party damage only, or third party damage + fire and theft
* Vehicle Engine Size, can be: < 1500cc, < 2000cc, < 2500cc, > =2500cc
* Driving Licence Type, can be: fully qualified, or student driver
* Vehicle Storage Type, can be: locked garage, or unlocked private place, or public place
* Time Since Last Claim, can be: < 1year, < 2yrs, < 3yrs, > =3yrs
In order to achieve full PAIRWISE coverage, how many combinations must be tested?
Answer: A
Explanation:
The correct answer is C . Pairwise coverage means that every possible pair of parameter-value pairs across any two parameters must appear in at least one test case. CTAL-TA v4.0 defines pairwise coverage as coverage where the coverage items are pairs of parameter-value pairs for any two parameters, and notes that tools are commonly used because finding a minimal set can be difficult.
Here the parameter value counts are: Type of Cover = 3 , Vehicle Engine Size = 4 , Driving Licence Type = 2
, Vehicle Storage Type = 3 , and Time Since Last Claim = 4 . The largest two-parameter interaction is between the two 4-value parameters: Vehicle Engine Size × Time Since Last Claim = 4 × 4 = 16 required pairs. Therefore, no pairwise suite can have fewer than 16 tests, because each test can cover only one specific pair between those two parameters.
A 16-test pairwise suite is achievable because the remaining 3-value, 2-value, and 3-value parameters can be distributed across those 16 rows while preserving all required two-way interactions. Option D , 288, is the full exhaustive combination count: 3 × 4 × 2 × 3 × 4 = 288 , not pairwise coverage. Option A and B are insufficient or unsupported by the pairwise lower bound. Reference: CTAL-TA v4.0, Section 3.1.2 Combinatorial Testing .
NEW QUESTION # 29
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 # 30
You have been appointed to be a TA in the development of a road traffic control application, which will be installed at busy road junctions to control the operation of traffic signal lights according to sensors that detect traffic volume on the various approaches to the junction. The project is still in the early stages of test planning, but it is already clear that despite a tight schedule its safety-critical nature demands careful and thorough testing.
You have been asked to decide whether automated test design would deliver benefits. Which characteristic of automated test design is MOST important for the development of this system?
Answer: D
NEW QUESTION # 31
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 would like to purchase 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 system is being developed following an Agile SDLC. Risk-based testing is practiced informally, discussion about what testing each user story will need being done in a risk-driven way during story refinement, but there is no central product risk register. Testing is exploratory, except for the acceptance tests for each story's acceptance tests. Operational profiles have been created to guide performance testing.
Regression test automation started late. The team want to automate all acceptance tests for every user story, but the test automation engineers are still playing catch up. They started with the tests that were easiest to automate, so the functional and non-functional coverage of the regression test pack is incomplete and random.
The current iteration is delivering a major change to the approval workflow and you, as a Test Analyst, have been tasked with defining the regression testing.
Which techniques would be MOST effective for selecting regression tests?
a) History-based, driven by the results of the regression tests run so far b) Risk-based, driven by the product risks and their traceability to the tests c) Operational profile-based, driven by the likely patterns of use of the relevant transactions d) Coverage-based, driven by the coverage obtained from use of relevant test techniques e) Impact analysis, driven by consultation with technical stakeholders to identify what might be affected.
Answer: C
Explanation:
The correct answer is B because the most effective regression-selection combination in this situation is operational profile-based selection plus impact analysis . CTAL-TA v4.0 states that regression testing often cannot execute every regression test because of time, budget, environment, or data constraints, so appropriate regression tests must be selected and the scope must be reviewed every cycle. The syllabus identifies impact analysis as a regression selection technique that focuses tests on areas most likely to be affected by changed configuration items, and also recognizes operational-profile-based testing as useful for selecting tests according to likely usage patterns and critical business processes.
Here, the current change is a major approval workflow change , so impact analysis with technical stakeholders is essential to identify direct and indirect effects. Operational-profile-based selection is also appropriate because approval, rejection, clarification, forwarding, and purchase-order creation are transaction flows with realistic usage patterns. Option A is weak because history-based selection is unreliable when the existing regression pack is incomplete and randomly biased toward easy-to-automate tests. Option C is invalid because formal risk-based selection depends on product risks and traceability to tests, but the scenario explicitly says there is no central product risk register. Option D also includes the invalid risk-based pair.
Reference: CTAL-TA v4.0, Section 2.2 Risk Control / Regression Testing .
NEW QUESTION # 32
You are working on a project to replace an old sales and merchandising system with a new system that will be based on modern platforms. The old system is still in production but is poorly documented and expensive to maintain. The new version will be developed using modern technology. The main requirements for the system are that it shall:
* Load sales data, sent electronically from the stores each evening, into a central database.
* Produce actual sales reports for the merchandisers, whose job is to manage stock levels in stores.
* Produce sales forecast reports, based on a combination of sales history and forecasting parameters. The parameters will be entered by the merchandisers into a browser-based front end and the reports will be produced overnight. The users will be able to see the reports next day, on screen or in print, by requesting this through the browser.
Requirements 1 and 2 are satisfied by the existing system and will be rewritten with no significant functional changes. Requirement 3 is new and has been clearly specified. Because of the poor test basis you have decided to perform experience-based functional correctness testing for requirements 1 and 2 with the support of checklists. Which would be the BEST items to include in the checklist for testing Requirement 2?
a) Does the sales quantity in the database for any one product in a particular store, equal the sales data input for that product / store?
b) Does the total sales value in the report for all products in a particular store, equal the sales data input for that store?
c) Does the sales quantity in the report for any one product in a particular store, equal the sales data input for that product / store?
d) Does successful login allow access to the report parameter entry features?
e) Does the total sales value in the database for all products in a particular store, equal the sales data input for that store?
Answer: D
Explanation:
The correct answer is C because Requirement 2 is specifically about producing actual sales reports for merchandisers. CTAL-TA v4.0 states that checklist-based testing helps the Test Analyst cover known essential aspects of a test item, prevents overlooking critical areas, and supports experience-based testing when documentation is weak or changing. It also states that checklist items should be clear, specific, relevant, actionable, measurable, and answerable with yes, no, or not applicable.
Checklist item b is relevant because it verifies that the report total sales value for a store matches the sales input for that store. Checklist item c is also relevant because it verifies that the report shows the correct sales quantity for a specific product/store combination. These two checks directly test the functional correctness of the actual sales reports .
Item a is not the best fit because it checks data in the database , which belongs more directly to Requirement
1, loading sales data into the central database. Item d belongs to Requirement 3, because report parameter entry is part of the new sales forecast reporting feature. Item e again checks database content rather than report output. Reference: CTAL-TA v4.0, Section 3.4.2 Checklists Supporting Experience-Based Test Techniques and Section 4.1 Functional Testing .
NEW QUESTION # 33
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