In the Agile Testing Quadrants model, Quadrant 1 (Q1) contains technology-facing tests that support the development team, such as unit tests and component tests. They are typically automated, written alongside or before the code (as in TDD), and their primary purpose is to support developers by verifying code correctness and driving good design.

Use Case Testing is ideal for this scenario as it focuses on testing sequences of actions (scenarios) that achieve a user’s goal. It is particularly effective for uncovering integration defects because it traces the user’s action (‘Submit Trade’) through its entire journey across various subsystems, ensuring all components interact correctly to fulfill the end-to-end transaction.

Decision Table Testing is the most appropriate technique here. It systematically captures complex business logic (like password rules, ‘Remember Me’ choices, and lockout counters) in a table of conditions and resulting actions. This ensures that all interesting combinations of inputs and states are considered, leading to a complete and efficient set of test cases for the login mechanism’s rules.

A time-based exit criterion alone is weak because it measures input (time spent) rather than output (what was tested and found). Stopping testing simply because time ran out does not indicate whether testing objectives (like coverage of risks, requirements, or code) were met. Effective exit criteria should be based on measurable goals, such as requirement coverage, risk level reduction, or defect detection rate stabilization.

The primary factor for defect priority is its business impact. A bug that causes incorrect financial calculations—especially resulting in a negative total—directly impacts a core, mission-critical function of an e-commerce system. This could lead to direct financial loss, fraud, or severe damage to customer trust and the company’s reputation, outweighing the argument about the combination’s rarity.

Bidirectional traceability provides two crucial assurances. Forward traceability (requirements to tests) ensures that every requirement is covered by at least one test case, which is essential for regulatory compliance. Backward traceability (tests to requirements) ensures that every test case validates a specific requirement, preventing ‘gold-plating’ (unnecessary testing) and confirming that the test suite has a clear, justified purpose.

Given the combinatorial explosion of devices, OS versions, and screen sizes, exhaustive testing is impossible. A risk-based approach is the most pragmatic. It focuses testing effort on the configurations that represent the highest risk (e.g., most popular devices, recent OS versions). Emulators and simulators are then efficiently used to extend coverage to a wider matrix of configurations for basic layout and functionality checks, optimizing the use of limited physical resources.

The core issue here is the insufficiency of the test data. Effective Test Data Preparation is a critical test analysis and design activity. It involves designing and creating data that is representative of production, including valid, invalid, boundary, and edge-case data. Relying solely on ‘clean’ data is a common pitfall that leaves defects related to data processing and exception handling undiscovered.

Integration Testing focuses on testing the interfaces and interactions between integrated components or systems. In this case, the new payment gateway is a component that needs to be tested for its correct interaction with the existing shopping cart and order modules. This is a classic example of component integration testing.

In the Agile Testing Quadrants model, Quadrant 1 (Q1) contains technology-facing tests that support the development team, such as unit tests and component tests. They are typically automated, written alongside or before the code (as in TDD), and their primary purpose is to support developers by verifying code correctness and driving good design.0