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| Section | Objectives |
|---|---|
| Topic 1: Reviews and Defect Management | - Defect lifecycle and reporting
|
| Topic 2: Testing of Software Quality Characteristics | - Non-functional quality aspects
|
| Topic 3: Test Tools and Test Automation Support | - Tool support for test analysis and execution
|
| Topic 4: Testing Process in the Test Analyst Role | - Test analysis and design
|
| Topic 5: Testing Techniques for Test Analysis | - Experience-based techniques
|
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질문 # 32
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?
정답：A
설명：
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 .
질문 # 33
Your company, which specializes in medical software, has designed an application for use on smartphones and tablets that calculates a person's BMI, Body Mass Index.
How can a Test Analyst BEST contribute to interoperability testing for this application?
정답：D
설명：
The correct answer is A because interoperability testing verifies whether the test object can interact correctly with other components or systems, exchange information, and use the exchanged information correctly.
CTAL-TA v4.0 states that interoperability testing verifies compatibility with components or systems with which the test object is intended to interact, and that its goal is to verify that two or more systems can exchange information and mutually use the exchanged information. It also specifically identifies defects in data transformation, interpretation or use of exchanged data, communication flows, protocols, standards compliance, and end-to-end functionality as interoperability concerns.
For a BMI medical application, integration with a national health service system and the correct receiving and processing of a BMI data file directly tests external system interaction and exchanged-data correctness.
Option B is accessibility testing, not interoperability. Option C describes coexistence testing, which CTAL- TA separates from interoperability under compatibility testing. Option D is adaptability or cross-platform environment testing because it checks target devices and operating systems, not interaction with another system. Reference: CTAL-TA v4.0, Section 4.4 Compatibility Testing , especially Interoperability Testing
.
질문 # 34
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
정답：C
설명：
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.
질문 # 35
Your project is developing an application to process claims against insurance policies. Which of the following is a good example of CRUD completeness testing?
정답：D
설명：
The correct answer is C because CRUD completeness testing is a static activity. CTAL-TA v4.0 defines CRUD as create, read, update, and delete, and states that CRUD testing verifies the lifecycle of data entities processed by the test item. The syllabus distinguishes two parts: CRUD completeness testing , which statically verifies whether all possible CRUD operations occur for every entity, and CRUD consistency testing , which dynamically checks whether functions interact correctly when handling the entity.
For an insurance-claims application, the key entity is the claim . A technical review checking whether the architecture/specification includes the ability to create, read, update, and delete claim records directly matches CRUD completeness. It is concerned with whether the full claim lifecycle has been included, not whether the lifecycle behaves correctly during execution. Option A is a strong example of CRUD consistency testing because it executes a lifecycle sequence and checks post-delete behavior. Option B is also dynamic execution, so it is not the best match for completeness. Option D is requirements elicitation completeness, not specifically CRUD completeness for the implemented claim entity. Reference: CTAL-TA v4.0, Section 3.2.1 CRUD Testing .
질문 # 36
You are your employer's most experienced TA. The organisation performs root cause analysis (RCA) thoroughly, but infrequently and only on individual defects that went live at the highest of the five Severity levels.
After six months of live operation for one system, particular concern has been expressed about the volume of usability and security defects and there is a strong desire to reduce their quantities. You have recommended adding product quality characteristics, per ISO 25010, to the defect report template.
How might this recommendation support RCA?
정답：D
설명：
The correct answer is B . The organization already performs RCA, but only infrequently and only for individual live defects at the highest severity level. That approach misses recurring lower-severity or medium- severity defect patterns, especially where many defects share the same quality concern. CTAL-TA v4.0 includes supporting root cause analysis with defect classification and aligns the syllabus with the ISO/IEC
25010:2023 product quality model, including quality characteristics such as functional suitability, usability, security, compatibility, and others.
Adding Quality Characteristic to the defect report template enables defects to be grouped by the quality attribute they affect. Combined with Severity , this allows the team to isolate clusters such as high-volume usability defects or serious security defects and then perform RCA on a meaningful defect group rather than only on isolated live failures. That directly supports the stated goal: reducing the quantities of usability and security defects.
Option A is partly useful because Pareto analysis can identify high-volume categories, but by itself it is defect counting, not the strongest RCA support. Option C concerns defect detection percentage, which is a different analysis objective. Option D is weak because "how the defect was fixed" may help investigation, but it does not provide the systematic classification needed to target recurring root causes. Reference: CTAL-TA v4.0, Sections 5.3.2 Supporting Root Cause Analysis with Defect Classification and Appendix F Software Quality Model .
질문 # 37
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