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| Section | Weight | Objectives |
|---|---|---|
| Test Analyst Tasks in Risk-Based Testing | 15% | - Product risk analysis and assessment - Risk-based test prioritization and scope definition - Regression testing scope based on change impact |
| Test Analysis and Test Design | 51% | - Black-box test techniques
|
| The Test Analyst Role in the Software Development Lifecycle | 15% | - Contribution to test strategy and planning - Test analyst tasks across SDLC models - Work products and stakeholder communication |
| Test Implementation and Execution | 10% | - Designing test procedures and test cases - Test data preparation and management - Executing tests and documenting results - Defect logging and root cause analysis support |
| Evaluating Test Results and Reporting | 9% | - Assessing requirement and risk coverage - Improving test processes and defect detection - Analyzing test results and coverage - Reporting test progress and quality status |
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10. Frage
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?
Antwort: A
Begründung:
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 .
11. Frage
You are testing a program which should calculate the area of a trapezium and have decided to use metamorphic testing. The formula Area = (((a + b) / 2) * h) where a and b are the lengths of the two parallel sides, and h is the height when the parallel sides are horizontal.
Which ONE of the following would be an appropriate metamorphic relation?
Antwort: A
Begründung:
The correct answer is B , but the question is slightly under-specified as written. CTAL-TA v4.0 defines a metamorphic relation as a property that describes how a change in test input is reflected in the expected result.
It is used to create follow-up test cases from a source test case and then evaluate the source and follow-up results jointly.
For the trapezium formula, if b changes while a and h remain unchanged, the area must change, not the height. Therefore, options C and D are structurally wrong because changing an input side length does not imply a change in h . Option A is also weak because it mixes an absolute increase in b with a fixed percentage increase in area, without considering the original values of a , b , and h . Option B is the only option that correctly expresses the expected-result relationship: a percentage increase in b causes a predictable percentage increase in area . Strictly, the exact percentage depends on the contribution of b to a + b ; the shown 2/3 relation is valid when b / (a + b) = 2/3 . Reference: CTAL-TA v4.0, Section 3.3.2 Metamorphic Testing .
12. Frage
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?
Antwort: A
Begründung:
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 .
13. Frage
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?
Antwort: D
Begründung:
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
.
14. Frage
A written specification describes the rules for granting membership of your company's sports facility, whether it must be paid for if granted and whether free transport to and from the facility will be provided.
These actions depend upon employment status (permanent, temporary or probationary), the result of a medical exam (passed, failed or not taken) and whether the person is classed as a local resident. The best decision table that could be created from this specification is shown below.
Which of the following conclusions is correct?
Antwort: D
Begründung:
The correct answer is A because the decision table has the correct structural completeness, but it exposes missing rules in the written specification. There are three condition dimensions: employment status has three values, medical exam has three values, and local residency has two values. Therefore, the complete decision table requires 3 × 3 × 2 = 18 rule columns , and the table contains exactly 18 rules. The unresolved entries appear in rules 17 and 18 , where the person is probationary , the medical exam is not taken , and local residency is either yes or no . Since all action cells for these two combinations are marked with question marks, the model has revealed that the specification does not define the required behavior for those cases.
CTAL-TA v4.0 places decision table testing under rule-based test techniques and states that it is used when behavior is determined by combinations of conditions, such as business rules. It is especially useful for finding omissions, inconsistencies, ambiguities, and gaps in rule specifications. Option B is wrong because the table has the correct number of columns. Option C is wrong because models are deliberately used to clarify text-based specifications. Option D is wrong because a decision table is the correct model type for condition-action business rules. Reference: CTAL-TA v4.0, Section 3.3.1 Decision Table Testing .
15. Frage
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