fbpx
Testing Within the Shift-Left Philosophy Testing Within the Shift-Left Philosophy
Traditionally, application testing was carried out during the last stages of the software development life cycle, that is after the application... Testing Within the Shift-Left Philosophy

Traditionally, application testing was carried out during the last stages of the software development life cycle, that is after the application had been completed and then handed to the security teams.

If an application did not satisfy quality standards, did not function properly, or otherwise failed to fulfill criteria, such as if it contained bugs of enough severity that they could negatively influence application performance, it would be returned to development for more adjustments. 

This resulted in major bottlenecks in the SDLC (software development life cycle) and was incompatible with DevOps approaches, which place an emphasis on development speed. It is also quite expensive and necessitates the utilization of a large number of resources.

It is feasible to find and solve faults considerably earlier in the software development lifecycle with shift-left testing because it is done during the beginning phases of the development. 

Shift-left testing means that security testing is carried out at every stage of the development process. In turn, this shortens the development cycle, improves quality considerably, and allows for speedier progression to later phases, such as security analysis and deployment. Organizations use different types of SAST (static application security testing) tools to facilitate testing in the initial phases. This strategy is also very cost-effective and does not necessitate the use of a large number of resources.

How to Test within the Shift-Left Philosophy

Since requirement gathering is the most critical element in any SDLC, the shift-left testing process should begin with it and work its way down the line.

For the testing team to have a complete understanding of the requirements, they must be involved during the requirement analysis and gathering phase. During this phase, they must review, comprehend, and analyze the information, as well as to conduct the risk assessment. This will help eliminate any misunderstanding or confusion later on in the cycle when the product is put through its paces.

In order to give developers test scenarios that satisfy all customer use cases and business needs, it is critical that QA teams collaborate with them during the designing and development phases following the completion of the requirement analysis phase. The developers will also be provided with a checklist of the test cases, which will assist them in taking countermeasures to address some of the known vulnerabilities in the program, such as incorporating input validation while developing web applications. 

There are some automated tools, such as SAST tools, which are being used to perform the testing. These are used to detect vulnerabilities and provide root cause analysis, which saves a lot of time. It is also necessary to conduct risk analysis in order to determine the impact of each test scenario as well as the possibility of failure. As soon as the test plan is complete, the testers must select which test cases should be prioritized and then discuss with the developers the chance of a test case failing and the consequences of a failed test case.

The shift-left testing process involves continuous testing, in which a large number of repeated test cases are run in order to identify bottlenecks in the software. If developers or QA teams are responsible for running these test cases manually, it is likely that they will soon feel very frustrated and irritated, and some of the critical test cases will not be run properly. Thus, neither the need for automated tools nor their use can be ignored. It is recommended that the teams make use of automated testing solutions in order to carry out their testing tasks.

Conclusion

Shift-left testing is a new way to test applications in each phase of the development process. This lets the teams identify the bottlenecks in the code, that too in the early stages. Hence, teams can patch them easily which will be less time-consuming and more cost-effective for the organizations.

ODSC Community

The Open Data Science community is passionate and diverse, and we always welcome contributions from data science professionals! All of the articles under this profile are from our community, with individual authors mentioned in the text itself.

1