System Testing vs End-to-End Testing Explained With Examples
Confusing system testing with end-to-end (E2E) testing can lead to duplicate work, overlooked defects, and delayed releases. While both are part of the software testing life cycle, they differ in scope, objectives, and execution.
We explain each with a side-by-side comparison and examples to help QA teams choose the right approach for their project stage.
System testing vs end-to-end testing
Feature | End-to-end testing | System testing |
|---|---|---|
Objective | Validate the entire user journey and system behavior across multiple components and integrations. | Ensure that each component of the system works correctly within the complete environment. |
Scope | Broad; involves multiple systems, subsystems, and external integrations. | Limited to the internal components of a single system without focusing on external systems. |
Focus | User interactions, workflows, and data flow across multiple systems. | System functionality, internal interfaces, and behavior against requirements. |
Test coverage | Comprehensive, covering the full process from start to end. | Covers specific functionalities and features as defined by requirements. |
Execution level | High-level, mimicking real-world usage. | Intermediate-level, focused on internal system behavior. |
Complexity | High, due to involvement of multiple systems and dependencies. | Moderate, limited to internal systems and interfaces. |
Figure 1: The place of system & end-to-end testing in SDLC.
What is system testing?
System testing verifies that a fully integrated and finished piece of software works as intended. During system testing, a QA team assesses how application components interact in a complete, integrated system.
System testing falls under black-box testing because it examines how the software functions from the user’s perspective.
In system testing, testers:
- Verify the desired outputs by thoroughly testing each input in the application.
- Evaluate the user’s experience of the application and the user interface (UI).
- Examine all application components to ensure they function consistently and seamlessly as a whole.
When is system testing performed?
Testers often carry out system testing after integration testing and before acceptance testing. See Figure 1 for the complete SDLC timeline.
What are the benefits of system testing?
- Identifying potential problems: System testing can be used to determine program weaknesses and pinpoint areas in need of repair.
- Ensuring compliance: Testers can determine whether the software meets the program’s criteria and objectives.
- Complete testing: System testing evaluates the entire system, allowing testers to quickly identify flaws or issues that may have slipped through integration and unit testing.
- Reducing reliance on hard-to-hire technical skills: Testers don’t need additional programming expertise to perform system testing.
- Accurate testing: The testing environment mirrors the production or business environment.
How is system testing done?
Prepare a testing plan
System testing begins with creating a detailed testing plan that outlines objectives, scope, success criteria, and responsibilities. This document ensures all QA team members follow the same approach.
For example, in a healthcare management application, the plan might define goals such as verifying patient data accuracy across modules, testing user-role restrictions, and ensuring HIPAA compliance.
Set up the testing environment
The testing environment should replicate the production environment as closely as possible, including servers, databases, network settings, and configurations. This allows for accurate validation of system behavior.
For instance, in an ERP system, setting up the environment might involve configuring modules for inventory, sales, and finance, and using the same database structure as in production.
Write test cases
Develop specific test cases for each feature or functionality in the application. These should cover normal, edge, and error scenarios to ensure robust validation.
For example, on an online banking platform, test cases might include verifying balance updates after a transfer, validating failed login attempts, and confirming interest calculations on savings accounts.
Execute testing protocols
Run the prepared test cases systematically, using both manual and automated testing where applicable. Ensure each case is executed in the defined sequence for consistent results.
For instance, in a university enrollment system, execution could involve creating a student profile, enrolling in courses, and verifying that the tuition fee calculation is correct.
Report defects
Document any issues or unexpected behavior found during execution, including steps to reproduce, screenshots, and severity level. This helps developers address problems efficiently.
For example, in a travel booking application, a defect might involve incorrect currency conversion when displaying total booking costs.
Perform regression testing
After fixes are applied, run regression tests to confirm that changes have not introduced new defects or broken existing functionality.
For instance, in a retail POS system, after fixing a discount calculation bug, regression testing might confirm that the payment process, receipt generation, and inventory update still work correctly.
What is end-to-end (E2E) testing?
End-to-end (E2E), also known as chain testing, is a methodology for ensuring that software functions as intended and that data flow is preserved across all user tasks and processes.
End-to-end testing aims to simulate a complete production environment by thoroughly testing the entire software for dependencies, data integrity, and communication with other systems, interfaces, and databases.
It is also a key testing practice when a product must function with other systems across various environments. In such scenarios, validating data processing across upstream and downstream systems is required to maintain accurate interactions across different platforms & environments.
When is end-to-end (E2E) performed?
End-to-end (E2E) testing is usually performed after system testing. It is especially useful for identifying system dependencies, as it tests both the software system and the connected systems. See Figure 1 for the complete SDLC timeline.
What are the benefits of end-to-end (E2E) testing?
End-to-end testing can provide the following benefits:
- Increased test coverage: It adds more thorough test cases than other testing techniques, such as unit and functional testing, helping teams increase their test coverage.
- Reducing overall cost: Shortens testing time, lowering the cost of building and maintaining software.
- Determining priorities: End-to-end testing helps managers set priorities for backlog items by assessing the workflow’s real-world significance to users.
How is E2E testing done?
Define test scenarios
E2E testing begins by defining critical user journeys or workflows to validate, such as user registration, login, checkout, and data input and retrieval. These workflows represent the primary ways users interact with the application.
For example, in an e-commerce application, a critical scenario might be verifying the checkout flow from adding a product to the cart to completing a payment.
Set up the test environment
To accurately test an application’s entire flow, the testing environment should mirror the production setup as closely as possible. This may include configuring servers, databases, third-party services, and other systems and network components required to support the full application.
For instance, in a banking application, setting up the environment might involve configuring test databases, network connections, and external services like payment gateways to simulate the production environment.
Prepare test data
E2E tests often require specific data to simulate real-world scenarios. This data can be created manually, imported, or generated by scripts. It should represent realistic use cases that the application will encounter in production.
For example, for a social media platform, sample user profiles, posts, and interactions might be created to represent real user data and actions.
Write test scripts
Test scripts are written to automate the actions users would take within the application. Commonly, these scripts are created using E2E testing frameworks such as Selenium, Cypress, or Playwright, which provide tools for interacting with the user interface, making API requests, and verifying data consistency.
For instance, in a ride-hailing app, automated scripts might include actions like entering a pickup location, selecting a destination, and verifying that a driver is assigned correctly.
Execute tests
Once the scripts are ready, they are executed in the testing environment. The automated scripts perform each action as a user would, clicking buttons, filling forms, verifying outputs, and checking that data flows correctly between systems.
For example, in a travel booking app, this could involve running scripts that simulate searching for flights, booking tickets, and checking confirmation emails in the test environment.
Validate results
The final step involves validating each test case’s outcomes against the expected results. This includes checking for correct visual elements, functional responses, data accuracy, and proper integration with third-party services. Any discrepancies are reported as issues.
For example, in a messaging app, validation might involve checking that messages sent by one user appear correctly for the recipient and that notifications are triggered as expected.
Debugging and re-running tests
If errors or failures are identified, the code or configuration is adjusted, and the tests are re-run to ensure the issues are resolved. This iteration improves the application’s reliability before it’s released to users.
For instance, if a checkout test fails in an online store due to a payment error, the script and payment service would be reviewed, updated, and re-run to confirm the fix.
Real-life case studies
Case Study 1: E-commerce Platform Migration – RetailCo’s Testing Strategy
RetailCo, a mid-sized online retailer, needed to migrate from a legacy monolithic platform to a modern microservices architecture while maintaining 24/7 operations.
Challenge: The migration involved integrating new payment gateways, inventory management systems, and customer relationship management (CRM) tools. The team needed to ensure zero data loss and minimal downtime.
Testing Approach:
System Testing Phase:
- Tested individual microservices (product catalog, cart management, user authentication) in isolation
- Verified that each service met its functional requirements
- Conducted performance testing on individual services to ensure they could handle the expected load
- Validated API responses and error handling for each microservice
End-to-End Testing Phase:
- Simulated complete customer journeys from browsing to checkout
- Tested payment processing across multiple payment providers (Stripe, PayPal, Apple Pay)
- Validated order confirmation emails and inventory updates across systems
- Tested cart abandonment and recovery workflows
System testing ensured individual components worked correctly, but E2E testing was essential to catch issues that only surfaced when multiple systems interacted under real-world conditions.
Case Study 2: Banking System Integration – MergeBank
Following a merger, two regional banks needed to integrate their core banking systems while maintaining compliance with federal regulations and ensuring that customer data was not corrupted.
Challenge: The integration involved combining customer databases, transaction histories, and loan portfolios, and connecting to federal reporting systems. Both banks used different core banking platforms with incompatible data formats.
Testing Approach:
System Testing Phase:
- Tested data migration scripts to ensure accurate transfer of customer information
- Verified business logic for interest calculations, fee assessments, and account balancing
- Validated role-based access controls for bank employees
- Tested compliance reporting modules against regulatory requirements (SOX, GLBA, BSA)
End-to-End Testing Phase:
- Simulated complete customer workflows, including opening accounts, applying for loans, and making transfers
- Tested inter-bank transfers between legacy and new system accounts
- Validated regulatory reporting workflows from transaction capture to federal submission
- Tested failure recovery scenarios (network outages, database failures)
- Conducted security penetration testing across integrated systems
Case Study 3: Healthcare Application – MediTrack
MediTrack developed a patient management system connecting hospitals, clinics, laboratories, and insurance providers. The application needed to meet strict HIPAA requirements while ensuring seamless data exchange.
Challenge: The system handled sensitive patient health information (PHI) across multiple touchpoints, required audit trails for all data access, and needed to integrate with legacy hospital information systems (HIS) and laboratory information management systems (LIMS).
Testing Approach:
System Testing Phase:
- Validated encryption mechanisms for data at rest and in transit
- Tested access control lists and authentication protocols
- Verified audit logging for all PHI access events
- Tested data retention and deletion policies
- Validated business rules for appointment scheduling, prescription management, and lab result processing
End-to-End Testing Phase:
- Simulated complete patient care workflows from registration to discharge
- Tested data flow from patient check-in through lab orders, results processing, and insurance claims
- Validated that PHI was properly encrypted and logged at every integration point
- Tested emergency access protocols (break-glass scenarios)
- Conducted cross-facility data sharing scenarios with proper consent management
For healthcare applications, system testing ensures individual components meet security and compliance standards, but E2E testing is critical for validating that compliance is maintained across the entire patient data lifecycle and through all system integrations.
Methods of software testing
To understand the role of system testing and end-to-end testing, we can examine the three types of software testing.
Black-box
Black-box testing is a software testing method that evaluates an application’s functionality without access to its internal structure. Knowledge of the internal working structures is not required for this type of testing. It is based on software requirements and primarily focuses on software inputs and outputs.
White-box
White-box testing examines an application’s internal components or mechanisms, rather than its functionality. Designing test cases for white-box testing involves viewing the system from within.1 Thus, knowledge of the internal working structure is required for this type of testing. The tester selects inputs to test various code paths and identifies expected results.
Gray-box
Gray box testing combines white box and black box testing. With this method, testers approach the software from an end-user perspective while having partial knowledge of the code internals.
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Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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