Navigating the QA Roadmap: Understanding Test Plan vs Test Strategy testRigor AI-Based Automated Testing Tool

The choice of test approaches or test strategy is one of the most powerful factor in the success of the test effort and the accuracy of the test plans and estimates. For example, by designing re-usable testware and by extensive automation of testing at one or more test levels. Once the test strategy has been written, we cannot modify it, and it is approved by the Project Manager, development team. In this section, we are going to understand the test strategy documentation, which is an integral part of testing documentation. For example, You might use the IEEE 829 standard for testing using books or fill in the methodological gaps. They may also provide a list of connection types, operating systems, anti malware software, etc. against which they want the application to be tested.

We can combine the two or more strategies as per the needs of the product and organization’s requirements. And it is not necessary to use any one of the above listed test strategies for any testing project. The selection of test approaches is a powerful factor in the success of the test effort and the accuracy of the test plans and recipe estimation.

Other types of Testing

A high-level document is used to validate the test types or levels to be executed for the product and specify the Software Development Life Cycle’s testing approach is known as Test strategy document. For example, you might create a set of testing guidelines focusing on the software’s rapid adaptation of known weaknesses. A model-based test approach is common in creating or selecting a formal or informal model for critical system behavior.

regression averse

When quality is measured correctly, you can predict test outcomes and influence the testing process. High-level documentation, such as a test strategy and test plan, allows you to measure the quality of the QA effectively, and thereby also the quality of your product in general. A test strategy gives you greater control over the testing process and the testing budget. Regression UI testing may be required when the product functionality has grown, and multiple new UI elements may cause confusion among users.

Software Testing Strategies and Approaches

Another example is the requirement-based approach, which involves conducting analysis based on the specified requirements. Testing strategy is arguably the most crucial piece of the test documentation hierarchy. It connects business objectives with the practicalities of quality assurance to drive company-based and project-based testing efforts. A good testing strategy requires an experienced QA lead and good communication with other stakeholders to tailor the best practices to your project. A consultative test approach is an inclusive and collaborative testing approach that focuses on active stakeholder engagement throughout the STLC. The testing team, business analysts, stakeholders, and developers are in close coordination.

regression averse

Also, within the test strategy, you should define the highlights also for other test documents. Here we explore different types of Selenium locators and learn how they are used with different automation testing. Cap off these test approach best practices with impeccable imitation between the developer environment and the end-user environment. Maintain traceability in test cases, requirements, and test results and establish a traceability matrix linking all requirements to their corresponding test case and result. Increased stakeholder involvement results in the development and implementation of a successful test approach. Testers should collaborate with architects, developers, and business analysts and take user feedback into account.

Introduction to Test Approaches

Test documentation houses various records and artifacts as part of the testing process to support and document various relevant activities. It includes test scripts, test cases, test plans, defect logs, and test reports. It also opens a gateway to effective stakeholder communication and serves as a crucial resource for future audits, reference, and for compliance. More up-to-date and well-maintained test documentation directly results in better accountability and transparency in testing. Test data comprises pre-existing information, conditions, and input values testers use during the Software Testing Life Cycle to execute various scenarios and test cases. Professionals involved can easily validate the reliability, performance, and functionality of software under a wide array of circumstances.

  • Determining the scope of testing and the desired outcome can become difficult, and testers can face confusion in having a clear grasp of the intended behavior of functionality.
  • They can arise anytime during the testing process and profoundly impact the efficiency and effectiveness of different testing activities.
  • While testing is in progress, the Senior Manager, Product Manager, Project Manager, and other stakeholders can monitor and deal with the Software Development Life Cycle due to the risk-based testing.
  • This is a really interesting strategy because it allows for the best tool support.

Once the testing team adopts efficient setup as well as maintenance practices, it will become much easier to mitigate test environment challenges and facilitate reliable and smooth testing activities. A tester’s comprehensive scope of understanding of the entire software testing process can easily determine what kind of technique is suitable for a specific program. The entire testing team uses their critical thinking, creativity, and domain expertise to identify the scope of improvement, explore possible scenarios, and simulate user behavior. The best part is that heuristic testing exercises great adaptability and flexibility.


You can also identify high-priority bottlenecks and risks that need quick addresses. This component also offers feedback to the software development team so that they can fix any problems if they arise quickly. Stakeholders can use these reports and analyze data to gain valuable insights into how ready the software is to brim up to its full potential. A test environment regression averse is a setup and infrastructure housing different testing activities, including all the software, hardware, and configurations required for effective test execution. Test objectives report specific purposes and goals that constitute the primary driver of all testing efforts. They outline different software aspects for evaluation and the end goal of any testing process.

This allows Techstack team members to be aware of different areas of responsibility and where to send inquiries. For this process to be of predictable quality, each phase is formalized and described as input criteria, the testing process during the phase, and output criteria. Testing can be carried out at different phases depending on the development process.

Automation Testing

Following that, the teams involved engage with stakeholders to understand user needs and stakeholder expectations. Considering the neverending list of testing activities, it’s always a good idea to create a comprehensive and detailed plan, also known as carrying out a test plan. It includes defining the objective and scope of testing, recognizing deliverables, estimating timelines and resources, and analyzing the test environment as well as requirements for test data. Test approach also offers test execution guidelines, test automation, and test data management, which makes managing tests more efficient. They can easily identify the required test data and suitable automation testing frameworks to automate repetitive tasks.

regression averse

Organizations that have experienced resources in this arena identify the risks quickly and move ahead to detect the sources and consequences of risks. Frequently, the team implements root cause analysis to have a detailed understanding of the source of the risks. Then, the team can plan the improvements that are essential to prevent the occurrences of defects in the future. The team executes the mitigation of risks throughout the complete life cycle. For product quality, if performance is a risk factor, the team tests the performance at several levels, such as integration testing, unit testing, and design testing.

Tips to develop successful QA test strategy

The prime intention of risk-based testing is to minimize the quality risks to an acceptable level. The team can detect and review quality and product risks while performing a risk analysis of the product quality. Automation plays a crucial role in the test plan and strategy, elevating the overall efficiency, accuracy, and effectiveness of the testing process. In the Test Plan, automation tools help define the approach for automated testing by identifying the specific areas or functionalities that can be automated.

Types of Testing

I have only done this in limited scenarios, for example an infrastructure replacement where nothing is expected to change. A methodical test strategy is when you use a standard test basis for different applications. There are several types of Test Strategies, but let’s go through some of the most commonly used ones. Get Mark Richards’s Software Architecture Patterns ebook to better understand how to design components—and how they should interact. Software test conditions are part of testing basics and represent an item or event of a component or system that could be verified. If you liked this article and want to learn more about software test management, then I would recommend that you check out our eBook – A Test Manager’s Guide.


While Product A is undergoing development, a few of these customers help the organization to identify the defects. The testing team is involved in this risk identification phase because it can leverage its experience in defect identification and quality risk analysis. In this scenario, the small group of customers is considered representative of the total count of customers. In risk-based testing, the QA team observes some risks related to product quality. The team uses these product quality risks to select the test conditions, calculate the effort essential for the end-to-end testing, and prioritize the created test cases.