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| Section | Weight | Objectives |
|---|---|---|
| Test Analysis and Test Design | 51% | - Experience-based and defect prevention techniques
|
| Evaluating Test Results and Reporting | 9% | - Reporting test progress and quality status - Analyzing test results and coverage - Assessing requirement and risk coverage - Improving test processes and defect detection |
| The Test Analyst Role in the Software Development Lifecycle | 15% | - Test analyst tasks across SDLC models - Contribution to test strategy and planning - Work products and stakeholder communication |
| Test Implementation and Execution | 10% | - Defect logging and root cause analysis support - Executing tests and documenting results - Designing test procedures and test cases - Test data preparation and management |
| Test Analyst Tasks in Risk-Based Testing | 15% | - Regression testing scope based on change impact - Risk-based test prioritization and scope definition - Product risk analysis and assessment |
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NEW QUESTION # 11
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: A
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 # 12
A simple DVD player is described in the following state transition diagram:
States shown in the diagram:
All round trips are feasible, even those that do not start at OFF. How many test cases will be needed for complete round-trip coverage?
Answer: C
Explanation:
The correct answer is B , because complete round-trip coverage requires every feasible round trip in the state model to be covered, not only those that start from the initial OFF state. CTAL-TA v4.0 explicitly includes state transition testing with N-switch and round-trip coverage as the focus of its state transition topic. A round trip is a path that starts and ends in the same state, normally without repeating an intermediate state.
The feasible round trips are:
* OFF # PLAY # OFF
* PLAY # OFF # PLAY
* OFF # REC # OFF
* REC # OFF # REC
* REC # REC PAUSE # REC
* REC PAUSE # REC # REC PAUSE
* PLAY # PLAY PAUSE # PLAY
* PLAY PAUSE # PLAY # PLAY PAUSE
* OFF # REC # REC PAUSE # OFF
* REC # REC PAUSE # OFF # REC
* REC PAUSE # OFF # REC # REC PAUSE
That gives 11 round trips. The warning in the question is important: if only OFF-starting round trips were counted, the answer would be too low. Option A overcounts by adding a non-modeled or duplicate round trip.
Options C and D miss feasible non-OFF-starting round trips. Reference: CTAL-TA v4.0, Section 3.2.2 State Transition Testing , round-trip coverage.
NEW QUESTION # 13
You are assigned to an Agile team as a Test Analyst. In most ways, the team seems to be working well.
Iteration planning goes smoothly because the user stories are good quality. Most defects that are found by testing are fixed in the same iteration and those that do go live are not causing significant dissatisfaction amongst stakeholders. However, the team is unhappy because the Defect Removal Efficiency rate, measured for each iteration, is less than 80%.
What would be the MOST effective contribution by you as a TA, to improve the situation?
Answer: D
Explanation:
The correct answer is D . The problem described is not obviously poor requirements quality, poor Agile discipline, or severe stakeholder dissatisfaction. The visible issue is a defect metric : Defect Removal Efficiency is below 80% for each iteration. The most effective Test Analyst contribution is therefore to improve the collection, classification, interpretation, and evaluation of defect data before the team acts on the metric. CTAL-TA v4.0 states that test results provide feedback that helps the TA improve defect detection effectiveness, and that measures such as defect detection percentage require careful boundaries, escaped- defect counting rules, and exclusion criteria. A low value indicates ineffective defect detection, so the TA should analyze the reasons and propose focused improvements.
This scenario strongly suggests that the team may be reacting to a headline metric without understanding what is being counted. For example, escaped defects may be minor, duplicates may be counted inconsistently, defects may belong to earlier work, or the iteration boundary may distort the figure. CTAL-TA also warns that defect metrics are not always easy to read because failed tests and defects can have many-to-many relationships and severities may differ.
Option B , root cause analysis, is useful after credible defect classification exists, but it is premature as the primary action. Options A and C are too generic. Reference: CTAL-TA v4.0, Sections 5.3.1 Analyzing Test Results to Improve Defect Detection and 5.3.2 Supporting Root Cause Analysis with Defect Classification .
NEW QUESTION # 14
A pricing system for determining the postage cost of a company's letters examines two input variables, representing the length L of the envelope in centimeters and the weight W of the letter in grams. Envelopes can only have three lengths: 15 cm Small, 20 cm Standard, and 25 cm Large.
For standard length envelopes, 20 cm, a premium postage rate is applied if the weight is equal to or greater than 50 grams. This is represented as:
IF L = 20 AND W > = 50 THEN RETURN Cost "Premium rate"
Which set of test points, each represented as variables L, W , achieves 100% simplified domain coverage for the Standard letter postage cost domain?
Answer: D
Explanation:
The correct answer is B . Simplified domain coverage requires boundary-focused ON and OFF points. CTAL- TA v4.0 states that for borders defined by < , #, > , or #, simplified domain coverage requires one ON and one OFF point. For an equality border, it requires one ON point and two OFF points on different sides of the border, with OFF points as close as possible according to the given precision.
The premium Standard-letter domain is defined by L = 20 and W > = 50 . For the W > = 50 border, (20,50) is the ON point because 50 is included, and (20,49) is the closest OFF point. For the L = 20 equality border, (20,50) also serves as the ON point, while (15,60) and (25,60) are OFF points on the two available sides of the Standard envelope length, because envelope lengths are restricted to 15, 20, and 25 cm.
Option A includes unnecessary extra points and does not represent the minimal required simplified coverage set. Option C uses 19 and 21, which are invalid envelope lengths. Option D misses the closest OFF point for the inclusive weight boundary because it uses 51 instead of 49. Reference: CTAL-TA v4.0, Section 3.1.1 Domain Testing , simplified domain coverage.
NEW QUESTION # 15
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 changes.
Requirement 3 is new. The development will use your company's Agile SDLC, with 2-week iterations.
Technical skill levels in the team are high and the approach to automate test execution is aggressive. Each requirement will be specified with user stories, will be released only when complete, and will need more than one iteration. The main business benefit will come from requirement 3, which depends on the other two requirements, and the stakeholders are keen to get this into production as soon as possible.
Release planning has begun for requirement 3 and you need to know at a high level what the testing scope will be, to ensure that the correct resources will be available. Which functional test techniques will be MOST effective for this release?
a) Domain testing
b) Combinatorial testing
c) Random testing
d) CRUD testing
e) Scenario-based testing
f) Decision table testing
g) Exploratory testing
Answer: A
Explanation:
The correct answer is C : domain testing, scenario-based testing, and decision table testing . Requirement
3 is new and business-critical. It involves entering complex forecasting parameters, generating reports overnight from sales history and parameters, and then viewing or printing those reports through the browser.
Domain testing is appropriate because forecasting parameters and sales-history values form input domains with partitions and boundaries. CTAL-TA v4.0 states that domain testing extends equivalence partitioning and boundary value analysis to domains with multiple parameters and complex partitions.
Scenario-based testing is also essential because the requirement describes an end-to-end user/business flow:
enter parameters, run overnight report generation, request report output, view or print result. CTAL-TA states that scenario-based testing evaluates behavior in realistic workflows and is often used in system and acceptance testing from the user's perspective.
Decision table testing fits because forecast calculation behavior is likely governed by business rules involving sales history, parameters, thresholds, and report-generation rules. CTAL-TA classifies decision table testing as a rule-based technique for stateless business rules. Random testing is inferior because the requirement is clearly specified, not poorly understood. CRUD testing is not the strongest match because Requirement 3 is not mainly an entity lifecycle problem.
NEW QUESTION # 16
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