Software testers and developers use regression testing to create efficient software programs. An examination of the challenges of regression testing shows that it counts 80% of total testing costs, while software testing accounts for 50–60% of total project costs. This article will look at the importance of regression testing and its implications on API regression testing and weigh the trade-offs. Regression testing examines existing software to ensure that each feature is intact after an update or addition. It aims to catch bugs that may have unknowingly made their way into the updated version of the software.
The use of application programming interfaces (APIs) is increasing because 83% of all Internet traffic belongs to API-based services. API testing has retained its place as a key testing practice in software testing because of this popularity. In addition to API testing, regression testing is required to verify the functionality of API-based applications after any changes, updates, or enhancements. This is one of the known practices for soften defects and malfunctions.
Research shows that increasing the level of API regression testing automation and reducing manual effort has a significant positive impact on a business-critical system. Such a positive impact can be seen in large-scale business software systems, where manual regression testing is difficult, labor-intensive and time-consuming due to the large number of possible test scenarios. Automating API regression testing allows businesses to reduce such issues to achieve better models.
The benefits of regression testing or automated regression testing in terms of cost, quality and time to market of software can be seen as similar to test automation. It is established through thorough research that test automation is one of the necessary elements in software development because testing uses:
- All around 40%-50% of total resources,
- 30% of the total effort
- 50%-60% of total software development costs.
Regression testing is no exception. Provides:
- Permanent stability: Regression testing improves the overall quality and stability of the API by ensuring that the functions of the applications are intact. This is achieved by maintaining existing coding functionality or evaluating new program code. Keeping app features intact through regression testing helps businesses stay on track.
- Growth and customer trust: It is estimated that software failures lead to losses for companies 2.3 billion in shareholder value on the day the bankruptcy was declared. The test cycle of regression testing allows organizations to demonstrate their competence by indicating the absence of bugs in the API. Enterprises can be more convenient and secure in delivering APIs to their customers.
- Cost Effectiveness: It is expensive and inefficient to create test cases every time. By reusing test cases, automated regression testing provides efficiency and allows businesses to maximize their retained testing. Automated test cases can also reduce cycle time and cost with 50%and free up time for employees to concentrate on software development and contributing to product quality.
PULSE is an automated AI-based API test automation tool created by TESTIMONIES. By examining the API documentation, PULSE generates tests to detect if there are API errors, then the AI analyzes the results and reports back in dashboard style. PULSE can reduce cycle time and costs by 50% and improve documentation. It can integrate with a CI/CD pipeline and is compliant with left-shift testing. Famous companies like BMW and Amazon use TESTIFI services.
- High initial costs. Regression testing can count 80% of the total testing costs. However, while regression testing may seem expensive, the data, research and use cases show the long-term benefits of using such a practice. The current trajectory of API regression testing shows numerous benefits, some of which are covered in this article, that businesses and software development teams can use.
- High frequency of testing. Regression testing is required for any minor code modification, as a small piece of updated or changed code can cause problems in the API. Businesses can avoid this problem by collaborating with the IT team to schedule updates and regression testing of multiple APIs in an organized manner to reduce testing frequency.
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