In the world of software testing, accurate test estimation is the cornerstone of successful project planning. Welcome to our comprehensive guide, where we delve into the essential components of effective test estimation. In this article, we will explore the ‘Test Estimate Blueprint’—a structured approach that highlights eight indispensable elements, each of which plays a pivotal role in ensuring your testing efforts are on track and aligned with your project goals. Whether you’re a seasoned software testing professional or new to the field, understanding these crucial elements is key to achieving precision and efficiency in your testing endeavors.


1. Scope of Testing & Strategy:

The accuracy of software test estimate heavily relies on understanding the scope of testing and developing a comprehensive testing strategy. The scope of testing refers to the specific areas of the software application that require testing. However, the scope of testing can vary from project to project, and accurately defining the scope is crucial for preparing accurate test estimates. In addition to scope, a well-defined testing strategy considers the testing objectives, types of testing, and testing techniques that need to be employed. Failing to define the scope and strategy can lead to inaccurate test estimate missed deadlines, and additional costs.

The extent of testing required for different risk levels can vary significantly, depending on the testing approach adopted. For instance, if a risk-based testing technique is applied, the extent of testing for each requirement with different risk levels will be different. This variation in the degree of testing can have a significant impact on the overall effort required to complete the testing process.

For instance, in a cloud migration project that involves modernization, the scope of testing is going to be significantly higher. There will be different types of testing that need to be performed, such as performance, security, functional, data migration, and chaos engineering. On the other hand, if a Lift and Shift approach is chosen instead of modernization, the scope and amount of testing required would be much lesser.

2. Browser & Device Coverage:


In today’s fast-paced digital world, software applications must work seamlessly on various browsers and devices. Estimating the effort required to test an application on multiple platforms can be challenging. Each browser and device combination may have unique characteristics and issues, which can make testing unpredictable.

Clearing out the number of devices, browser versions, and test cases to be executed on each of them is essential. Adopting a risk-based approach where only a subset of test cases is executed on the devices or browsers considered in scope is an effective way to handle these challenges. This approach becomes even more important when dealing with projects involving IoT or Point of Sale Devices. Therefore, it is vital to consider browser and device coverage while software test estimate is prepared.


3. Prior Experience & Skill Levels:

If the estimator has familiarity with the team that will execute the project, they can better assess the team’s strengths and weaknesses and prepare a more accurate estimate. The productivity and skills of the team directly impact the level of knowledge and expertise required for testing, application, and domain knowledge. Identifying gaps in the team’s skills and training can be one way to reduce knowledge gaps, which needs to be considered in the estimates if training is required.

Furthermore, the skill and knowledge levels of the development team also have a minor impact on test estimate. For instance, if the development team is new to the technology, many defects can be expected during test execution, leading to additional test cycles and increasing defect management efforts. This emphasizes the importance of considering the skills and knowledge level of both the testing and development teams while one does the test estimate.


4. Number of Test Cycles:


The number of testing cycles required to complete a software testing project is a crucial factor that can significantly influence test estimates. The complexity of the software application and the quality of the code are the primary factors that can impact the number of testing cycles required. Additionally, the number of builds planned by the development team can also affect the testing cycles.

The more the software builds planned, the more test cycles may be required, as regression testing is needed on each build. If the development team does not fix defects as per the plan, it may require additional test cycles, leading to an increase in effort and time. Moreover, it is important to consider the test case failure rate to arrive at the appropriate number of test cycles. A higher test case failure rate would require more test execution effort, resulting in an increase in the number of test cycles required to complete the project.


5. Reusable Assets:


One of the crucial factors that should be considered while preparing software testing estimation is the test assets and documentation that can be reused from previous projects. The reuse of these assets can significantly reduce the time spent on designing new deliverables, thus saving costs, and improving efficiency.

Some of the test assets that can be reused include test strategy documents, test cases, automation frameworks, automation scripts, performance test scripts, and more. It is essential to determine which assets can be reused and to what extent. The effort required to modify or update the reused assets should also be considered during the estimation process.

For instance, if the automation scripts used in a previous project are not compatible with the current project’s technology, they will require modifications, and this can impact the estimation. Similarly, if the test cases from the previous project require substantial modifications to fit the current project’s requirements, the effort involved should be factored into the estimate. However, reusing test assets can lead to faster and more accurate testing, enabling testers to focus on new requirements and functionalities. Thus, test assets’ reuse can be an effective way to optimize testing efforts and achieve better results in a shorter time frame.

6. Tool Usage and Process Maturity:


Software testing tools and process maturity have a significant impact on software test estimates. The usage of testing tools can help automate testing processes, reducing manual effort and speeding up testing cycles. The maturity of the testing process also plays a crucial role in reducing testing time across all phases of the test life cycle.

However, the availability and usage of testing tools should also be considered while estimating software testing efforts. If there are no defined processes or tools in place, the project team will have to spend time defining the processes, guidelines, and templates. They will also have to spend a significant amount of time setting up and configuring tools. All these factors must be considered while preparing estimates.

Furthermore, the overhead associated with regulatory process compliance requirements can also impact software test estimates. Compliance with regulations can often add additional steps and documentation to the testing process, increasing the overall testing effort. Therefore, it is essential to consider compliance requirements and the additional overheads associated with them while estimating software testing efforts.


7. Test Data & Environment Availability:


The availability and stability of the test environment play a significant role in the test estimate preparation process. The test execution activity relies heavily on the test environment’s availability and stability. If the test environment is not stable or does not have all the necessary interfaces, it can impact the productivity of the test execution team. Additionally, the approach taken for creating data required for executing the test cases has a direct impact on the test execution effort.


There are various approaches for creating data required for test cases, such as loading data from production after masking, creating data using SQL statements, manually creating data using applications, and creating data using automation tools or scripts. Non-testing team members primarily handle loading data from production and creating data using SQL statements.


On the other hand, the testing team handles the remaining approaches. If the required data is not available or not created as per the test cases’ needs, it will lead to delays in testing and impact the overall test effort. The testing team must have the required data available to perform the tests efficiently. Therefore, the availability of test data and environment needs to be considered while you carry out the software test estimate.

8. Test Automation Levels:


Test estimate is significantly impacted by the level of test automation required for a project. While test automation can help reduce testing time and effort, it requires a significant upfront investment in developing and maintaining automation scripts. Therefore, the level of test automation required for a project should be considered while preparing the software test estimate.


If there are test automation scripts available from previous projects, the investment required will be limited to maintenance, tool procurement, and automated test execution. However, the Return on Investment (ROI) needs to be considered before recommending test automation. One should only recommend test automation if it can achieve a break-even point after several tests. Additionally, the effort required to maintain and update the test automation scripts should be factored into the test estimate.


Key Inferences on Factors influencing Software Test Estimate:

In this article, we have discussed the major factors that influence software test estimate, such as the scope of testing, browser and device coverage, prior experience and skill levels, test cycles, reusable assets, tool usage and process maturity, test data and environment availability, and test automation levels. Considering these factors while estimating software testing efforts can help achieve better results in a shorter time frame, optimize testing efforts, and save costs.

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