How to Shift Left Testing Across the SDLC

This involves a range of strategies aimed at incorporating early testing and quality assurance into the software development life cycle. Instead of waiting until the later stages of development to initiate testing efforts, shift-left testing emphasizes the importance of testing earlier in the software development life cycle and in parallel with code development.

When testing is injected early on, development teams can identify and address defects, issues, and potential risks before they propagate further into the development process. By doing so, teams save time, resources, and costs associated with rework and refactoring.

Shifting testing activities to the left or earlier in the software development life cycle offers numerous benefits that can significantly enhance the overall quality, efficiency, and delivery of software projects. Here are some of the benefits organizations can derive from shift-left testing.

To embrace the shift-left testing approach, it is crucial to integrate development-level testing activities into the development process. Integrating testing practices such as static analysis, unit testing, and functional and nonfunctional testing directly into development allows developers and testers to find and fix defects early, at their source. The following sections will break down various testing techniques and how they align with a shift-left testing strategy.

The Role of Static Analysis

Shift-left testing thrives on early detection, and static analysis tools are the secret weapon in this proactive approach. Unlike traditional testing methods that require running code, static analysis solutions examine the source code itself, acting like a code detective scrutinizing every line. This meticulous examination uncovers potential bugs, security vulnerabilities, and areas where the code could be written more efficiently.

Static analysis solutions like Parasoft’s C/C++test, dotTEST, and Jtest can be incorporated into development workflows in several ways. Developers can run static analysis scans locally in their development IDEs on their code changes and new feature code before committing them, or they can integrate automated code scans into their CI/CD pipelines to ensure code is scanned each build, allowing for early detection and resolution of issues.

Shifting Static Analysis Into Active Development

To fully embrace the shift-left development testing approach, organizations should integrate static analysis tools directly into their development workflows.

While shift-left development testing emphasizes integrating testing practices into the development phase, the role of quality assurance (QA) teams remains crucial. Shifting testing activities left and embedding QA teams with development enables closer collaboration, provides earlier testing feedback, and allows the entire team to contribute to the overall quality assurance process from the outset. This collaboration bridges the gap between development and testing, ushering in a more cohesive and efficient workflow.

Early involvement of QA teams ensures testing aligns with project requirements and design specifications. QA professionals can provide valuable insights during the requirement-gathering and design phases, ensuring testability is built into the product from the beginning. This alignment helps in creating comprehensive test plans that cover all aspects of the application, including edge cases and potential failure points.

Scalability Challenges

As organizations adopt shift-left testing approaches, QA teams may face scalability challenges. With testing efforts being initiated earlier in the software development life cycle, the volume of tests and the frequency of test execution can increase significantly. This can strain resources, infrastructure, and tooling, potentially leading to bottlenecks and delays in the testing process.

To address these scalability challenges, QA teams need to embrace strategies that enable efficient and scalable testing practices. This may involve leveraging cloud-based testing platforms, implementing parallelization techniques, optimizing test suite execution with test impact analysis, and adopting risk-based testing approaches to prioritize critical areas.

What Is a Lean Web UI Test Strategy?

A lean web UI test strategy is an approach that urges QA teams to think critically about what type of test they should create to validate functionality or to meet their testing requirements. Many QA teams overrely on UI and end-to-end testing to validate business logic. However, in many cases testing can shift left from the UI layers to the API layers enabling teams to start their functional testing much earlier in the development life cycle. This is not to say that teams should abandon UI or end-to-end testing as it’s required to validate user interface interactions, end user workflows, and cross-browser compatibility, and more.

Here are some tips for teams adopting a lean web UI test strategy.

• Think critically about what type of test to create based on the business logic they’re required to validate.
• Take an API testing first approach. Start creating API tests as soon as a service definition file has been created. Many commercial API testing tools enable the use of service definition files to generate API component tests, and some solutions, such as Parasoft SOAtest, for example, leverage AI to make API scenario test creation easier for less technical testers.
• Outline the appropriate use cases in which a web UI test should be created and share these guidelines across the team.
• Analyze old UI test cases as they break to determine if the business logic under test can be validated on the API layers or if maintaining that web UI test case is necessary. If the logic can be validated through the APIs, retire the test case and create an API test scenario to replace it.

Benefits of a Lean Web UI Test Strategy

Implementing a lean web UI test strategy can yield numerous benefits for QA teams and the overall software development process. Below are some of the specific benefits:

• Shift-left testing. By concentrating testing efforts on the API layers, teams can initiate functional testing much earlier since API testing can commence before all application components are fully developed. Leveraging service definitions, teams can generate these tests even before the UI or dependent components are completed.
• Faster test execution. API tests execute much faster than UI or end-to-end test cases, so by focusing on API testing, teams can get faster testing feedback.
• Early defect detection. By focusing on API testing and involving QA teams earlier in the development process, teams can identify and address defects and issues promptly, reducing the cost and effort associated with late-stage fixes.
• More stable and maintainable test suites. In general web UI test cases tend to be less stable and more sensitive to application change resulting in high test maintenance burdens to the QA team. API testing in comparison is less brittle and more stable, resulting in a lower test maintenance cost.
• Scalability and flexibility. Since API testing facilitates high levels of test automation and scales easily across teams and physical machines, by adopting a lean web UI test strategy, QA teams can have a more robust test automation strategy that easily scales across the enterprise.

API testing solution like Parasoft SOAtest leverage AI to help teams easily adopt a lean web UI test strategy. With the Smart API Test Generator, teams can convert automated web UI test suites in any test framework to API scenario tests for RESTful services. This allows teams to leverage their existing web UI test suite to generate API scenario tests to validate the business logic.

Shifting left nonfunctional testing involves integrating nonfunctional testing activities, such as performance, security, and accessibility testing, early in the development life cycle.

Moving these tests to earlier phases enables teams to identify and address potential problems before they boomerang out of control. Early nonfunctional testing ensures that the software meets performance benchmarks, security standards, and accessibility requirements from the outset, leading to a more robust and reliable product. This approach also aligns well with Agile and DevOps practices as it promotes continuous iterative improvement.

The Challenge of Late-Stage Nonfunctional Testing

Deferring nonfunctional testing until the later stages of development can pose significant challenges and risks.

Service virtualization is a technique that simulates the behavior of components in a software application, such as APIs, databases, and third-party services, that are not readily available or are difficult to access during development and testing. It creates a virtual environment that mimics the functionality and performance of these components, allowing developers and testers to work independently of external constraints.

Service virtualization plays a crucial role in enabling shift-left testing by allowing teams to start testing much earlier in the development process. It provides virtual representations of unavailable or incomplete components, enabling developers and testers to validate interactions and performance without waiting for the actual services to be developed or become accessible.

This early testing capability helps identify defects and performance issues sooner, reducing the risk of late-stage surprises and the associated costs. In addition, service virtualization supports CI/CD practices by providing stable and predictable testing environments, ensuring that testing is thorough and uninterrupted.

The Benefits of Shifting Left With Service Virtualization

Service virtualization improves test coverage by enabling testing of various scenarios, including edge cases that might be difficult to reproduce with real services. It also reduces costs associated with setting up and maintaining test environments, as virtual services can be easily configured and reused. Additionally, service virtualization fosters a more agile and responsive development process, aligning well with modern Agile and DevOps methodologies.

An effective strategy for optimizing regression testing is to focus the testing efforts on areas of change. Identifying and isolating the code changes or updates can help teams execute regression tests selectively on the affected components and their dependencies, reducing the overall testing time and effort.

This approach can be achieved through techniques such as:

1. Test impact analysis. Analyzing the code changes and identifying the tests that need to be executed to verify those impacted components and functionalities.
2. Test suite prioritization. Prioritizing and executing the most relevant regression tests first, ensuring that critical functionalities are validated early in the testing process.
3. Test parallelization. Leveraging parallel execution of regression tests, particularly for independent and isolated components, to accelerate the overall testing process.