In recent years, DevOps has presented a cultural shift that needs more collaboration among dev teams, stakeholders and IT. One key aspect of this collaboration is the need for faster feedback. Since manual regression testing is time and labor-intensive, it creates a bottleneck that hinders the Agile and DevOps way of thinking. ‘Continuity’, Continuous Integration and Delivery are crucial to create a deployment pipeline. The delivery pipeline allows teams to release a constant flow of software updates to accelerate the release cycles, lower costs, reduce risks in a highly competitive environment.
Continuous Testing is essentially the process of testing early, testing often, testing comprehensively , and using automation to achieve cohesive release goals. In the ideal scenario, the release candidate is continuously moving from Development to Testing to Deployment.
That is there is continuous development, delivery, testing and deployment. Thus, whenever a developer checks in the source code, a set of unit tests are executed. If tests fail, the build is rejected and the feedback is provided to the dev team. And when they pass, the code is deployed performance and QA servers for further functional and load tests. These tests are run in parallel and when the process is completed, the software moves to production.
Continuous Testing provides the means to gain quick feedback on the business risks related with a release candidate, using automation. It helps dev teams to meet business goals and managers to make informed decisions to optimize the value of a release. However, Continuous Testing is not just ‘more test automation’.
Here are the key differences between Continuous Testing and Test Automation
|Continuous Testing||Test Automation|
|Software testing paradigm that focuses on executing automated tests as part of the software delivery pipeline to gain immediate feedback on the risks associated with a software release.||A method in software testing that makes uses of special software tools to control test execution and compares the test results with the desired/expected results.|
|Continuous testing process helps find the key risks, address them in a timely manner, and improve the overall product quality.||Automated testing process is a set of repetitive tasks that a machine can execute faster, with fewer mistakes.|
|Continuous testing relies on test automation to meet the continuous delivery goals.||Test Automation is possible without integrating continuous testing.|
|Releases may be very quickly deployed, as short as weekly or hourly.||Releases can take longer from months to years|
|Execution of tests is run through the testing tools automatically following code integration.||Developer code is run through testing tools fed with testing scripts that run each test.|
Continuous Testing has an obvious edge over Automation Testing. That is, once the code is checked into the source code repository, build and validation process begins, and there is immediate feedback. There is no gap where the integration, testing, and feedback mechanism await human intervention.
What a standard Continuous Testing process may look like :
- Generation of test automation suite from user stories or requirements
- Creation of Test Environment
- Copy and anonymize production data to create test data beds
- Service virtualization for API testing
- Parallel Performance Testing
It is a process of evaluating quality at every step of the Continuous Delivery Process. A simplistic view of this is that CT allows us to find problems as soon as possible, making the lead time from check-in to release as short as possible. And hence, parallel activities in the deployment pipeline as opposed to stage-wise execution.
Key Aspects of Continuous Testing:
- Primary Goal for Continuous Testing is assessing business risk coverage
- It establishes a safety net that helps protect the release and the customer experience
- Requires a stable test environment and valid test data for each test run
- Continuous Testing presents the best of both worlds – Shift Left(agile testing, testing early and often) to Shift Right(Testing in production, APM)
- Continuous Testing delivers actionable feedback at each stage of the pipeline
- It focuses on end-to-end tests to assess the end user experience for all associated technologies
- There is continuous review and improvement of the test suite to eliminate redundancy and optimize business risk coverage
Many businesses that have already adopted test automation are now taking to the next level with continuous testing. With the real-time validation of software meeting business outcome at different quality gates, businesses can automate the delivery pipeline and confidently release software faster.
Some of the benefits include:
- Immediate feedback for business stakeholders to take informed decisions
- Objective assessment of organization’s specific goals – useful for the critical go/no go decisions
- Reduces the business risks of a completely automated Continuous Delivery process
- Early and fast removal of defects reducing the overall cost of a defect
- Merges traditional silo-based teams to modern enterprise process. Breaks barriers between development, testing and operations.
- Provides universal test environment access with Service Virtualization
Continuous Testing: What You Will Require?
Automated Code Scans
As mentioned earlier, the earlier continuous testing is implemented, the better value it provides. By implementing your test automation strategy right at the beginning, one can uncover a large number of process defects as they are introduced to the code. Continuous testing provides insight into fixing those defects before they are part of the integrated system. Continuous testing should start in the earliest phases of the SDLC. Arguably this is where an organization can actually take the best advantage of acceleration because the early phases of application development are traditionally where the worst defects are introduced.
Testing early and often needs to be executed as part of the CI pipeline. As soon as developers check in their code, the automated testing kicks off with static analysis and unit testing. Using the results from these scans, businesses can then pass/fail the build based on the threshold you have set.
As an example, if you set a policy gate where if an 85% code coverage is achieved and no more than five level 3 or higher findings are found, then the build is a success. But if the coverage drops below 85% and high-risk defects are found, then the build is failed, integration is rejected, and dev team is notified.
The benefit of this method is that your development teams can function rather independently using whichever dev or test tools they like. Whereas the business by putting in various policy gates, ensures that the teams operate within the risk boundaries set by the stakeholders.
Reporting and analytics are essential to ensure that businesses can track the quality of their requirements and check there are effective tests aligned to each requirement. The dashboards also help the stakeholders in making sure that all the crucial requirements are met, and rework is not required. Traceability also helps in assessing which requirements are at risk, working as expected or require further validation.
Additionally, you can meet compliance mandates and gain real-time visibility into the quality, thereby avoiding late cycle surprises.
Areas such as static code analysis, change impact analysis and scope assessment/prioritization benefit immensely from test automation. This helps in preventing defects and accomplishing more within each iteration. Realistic test data can remarkably improve the effectiveness of a continuous testing strategy. Therefore, good test data and test management practices can broaden the coverage and improve accuracy. Data generation is also an important part of continuous testing
Ultimately, Continuous testing is just a paradigm shift that advances top-level digital enterprise goals. When done right, Continuous Testing is the linchpin of the Agile downstream process. Slowly, Continuous Testing is becoming an indispensable part of modern application delivery due to its inherent ability control business risks.