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6 Common Continuous Testing Bottlenecks

Agile and DevOps practices are rapidly growing in popularity. Many companies are adopting these software development methodologies to deliver new software and updates quickly and frequently. Since Agile commonly uses user stories and requirements to define product features, the software released incrementally delivers value to the clients.

Subsequently, continuous testing has also seen an unprecedented rise in demand as it the key catalyst to deliver quality with speed.

Continuous software testing is the execution of test suits as part of software delivery pipeline, as opposed to testing at the end of the software development life cycle (SDLC). It provides risk-based feedback as rapidly as possible, at every phase of the software delivery pipeline. Continuous testing allows the software development process to advance at a quick pace without compromising the user experience.

Freeform Dynamics discussed the advantages of continuous testing and accumulated feedback from 923 IT and testing professionals in their research, Continuous Testing as Digital Business Enabler. The study revealed some interesting statistics.

Around 75% professional agreed to the importance of continuous testing in software development. However, only 20% of the respondents said that they had an appropriate level (more than 80%) of test automation coverage. Moreover, roughly 1 in 5 respondents said that they still relied heavily on manual testing.

Despite its many benefits, implementing continuous testing is still challenging for a plethora of companies:

Analyzing continuous, automated testing

One of the biggest challenges of continuous testing is to investigate the massive volume of output generated very quickly. The output is produced from various sources including multiple testing tools, static and dynamic analysis, code coverage, functional and regression testing, etc.

The analysis of the testing takes a lot of time and effort which could have been served, e.g., to optimize the test suite or enhance the test coverage. It can take hours to determine if the automation software test was successful or not, which detracts from the core purpose of implemented continuous testing, i.e., to expedite software delivery.

Automating the analysis of testing can solve this problem to an extent. More and more developers are directing their attention to accelerating output analysis to speed up the entire delivery cycle.

Visibility in the continuous testing analytics

Image result for continuous testing shift right shift left

It is crucial for both the developers and the operations team to have vivid clarity in the testing analytics. While shifting it left or testing early on in the application lifecycle is very essential, it is not enough. You need to obtain continuous feedback from the users for quality-assurance, which is only possible by shift-right testing.

The primary focus of software testing is not only the performance of the product in the development phase and test environment, but it should also focus on enhancing its usability. You need insights on the behavior of the application or feature as an end product to optimize your initial stages.

Therefore, you should not only shift left to integrate testing and finding problems earlier but also procure data from the production to understand the potential flaws of the product.

Long test run-time

Since continuous testing constitutes of implementing different test suites at every level of the software architecture, the amount of testing is monumental. While you need to focus on test coverage, functional coverage and scripting new lines of codes, you also need to pay attention to run-time.

Continuous testing was introduced to speed up the delivery process without affecting the software quality. Hence, it is not practical to run the test for four to five hours because it will delay the feedback marginally. Consequently, the entire delivery pipeline will slow down.

To overcome this problem, you need a more comprehensive view of what is essential and what is relevant. The Test Impact Analysis (TIA) feature can augment the validation by automatic test selection. For a given source code entering the pipeline, TIA will select and run only the required test necessary to validate the code. Thus, the test run becomes faster and more focused.

Keeping up with numerous deployments

Continuous testing generates test debt. Various tests are deployed in a day to evaluate the software quality and detect bugs, as well as to keep up with the Agile methodologies.

However, it becomes difficult to keep track of all the tests implemented every day. If you cannot identify the effectiveness of the tests, or analyze how the changes in test iterations influence business risk and the end-user experience, the increased frequency and speed becomes irrelevant.

Time-consuming and expensive

Test automation is the key component of efficient continuous testing. It allows the team to analyze the performance of new tests and iterations quickly.

However, building automated test scripts can be time-consuming and expensive. Therefore, it is essential for organizations to optimize their use.

Amir Ghahrai, QA industry veteran, explained that organizations should be aware of automating which testing areas are most beneficial. You can adhere to the test automation pyramid principle to extract the most value from test scripts.

Image result for test automation pyramid principle


Teams should focus the majority of their automation efforts on unit tests, which lie at the bottom of the pyramid. As you move up the pyramid, you can scale back on automation to optimize your investments in automated scripts.

Resistance to change

Finally, despite all the advances in software development and testing, a small but significant percentage of experienced testers refuse to update their testing methods. The primary reason for the unwillingness to change is the seemingly effective traditional methods. As a result, ultimately the entire team suffers the consequences slowing the development procedure.

Marco Achtziger, a test architect at Siemens Healthcare, spoke about this matter at an OOP 2015 conference in Germany. He suggested that you should remain supportive and positive to the unrelenting team members. Focus, not only on the benefits of switching to the advanced procedure but also on the advantages the change will bring to the entire team.

Continuous testing is a significant asset to organizations as it can accelerate the software developing process while mitigating the business risks. Software testing tools can also facilitate the testing practice and help overcome some of the challenges associated with the feedback-driven test method.

What challenges did you face when integrating continuous test in your SDLC and how did you overcome them? Share your story to benefit our readers struggling with integrating continuous testing.

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