Using Shift Left Testing to Improve the Software Development Lifecycle
June 07, 2022

Eran Kinsbruner
Perfecto by Perforce

Testing is critical for long-term success, however, many enterprise teams are grappling with the timing of their testing. Today, the traditional software development lifecycle begins with requirements, goes to design, then coding, and ends with testing. The problem with conducting testing at the end is that much of the work is already complete, causing last minute surprises, costly defects, and delays in deploying the final product or update.

The Rise of Shift Left Testing

Shift left testing is exactly what it sounds like — shifting testing left to happen earlier in development. This practice is praised for its focus to test earlier and often, identify problems from the start and allow enterprises to deliver higher quality software at scale. This is why enterprise organizations are increasingly determining how to best integrate shift left testing strategies to keep pace in this age of rapid digital transformation and remain competitive.

By testing in the earliest stages of the development lifecycle, businesses can ensure the highest level of functionality and the most secure software systems. The 2022 State of Automotive Report by Perfecto found that in 2021, teams not only grew their mobile and web app test suites, but also adopted other technologies to serve different personas within the same team. Further, the survey uncovered the strong interest in investing in commercial test creation solutions, with 46% of respondents looking to these tools to improve non-functional tests like performance and accessibility. By adopting shift left practices, these enterprise organizations ensure teams have the time to fix defects, avoiding delays and missed deadlines.

Challenges of Implementation

The benefits of shift left testing have never been clearer and easier to understand. Yet, enterprise organizations largely continue to lag in adopting the testing process, or unsuccessfully attempt at introducing it to their workflows. For the latter, the implementation challenges of shift left testing may be a deterrent to certain teams stuck in the traditional way of working. Some of the most common challenges plaguing these teams:

A Lack of Resources. Testing at scale requires the proper resources, tools and workload capacity. Being able to complete shift left testing and existing testing simultaneously is needed and although not every test can be completely automated, businesses consider implementing codeless tools to make testing more feasible.

Misalignment of Leadership. There will be challenges if the company’s leadership isn’t onboard with the shift left approach or there is a lack of alignment across existing processes. Many developers are hesitant to disrupt existing processes and stray away from traditional ways of working, creating unforeseen friction across teams. To combat this, level-setting and educating employees on the benefits of shift left testing ensures the business value is clear across all levels and departments.

Misfit in the Build Cycle. Defining the scope of testing is needed to justify integrating shift left testing to the build cycle. For each build to be tested, consider integrating key functional testing scenarios; security and performance testing; and

As enterprises look towards shift left testing adoption and overcoming application development challenges, there are ways to ensure a smoother rollout process. Enterprise organizations should first educate teams on what this process means and how it serves as a touchpoint for operational efforts as well as clearly demonstrate what this kind of testing can and cannot do to get buy-in cross-departmentally. Taking these smaller steps to adoption will create a more cohesive testing environment, cultivate a better end-user experience, and radically transform the digital enterprise.

From Developers to Customers — The Benefits of Shift Left

Smaller bugs. Less rework. Easier fixes. Shift left testing is a rising movement because of its value for agile teams and versatility across projects — the tangible benefits are a game-changer for all involved.

With shift left testing, errors and defects are identified earlier in the process, resulting in less rework and significant time-savings, ultimately keeping projects on track (and successful) with tight deadlines. This streamlines the time-to-release process and reinforces customers’ confidence in the product, software, or tool.

By combining coding and testing together, the shift left approach reduces code instabilities. It creates a better-quality product and codebase — both needing less patches and/or fixes. This increases customer satisfaction and improves business results.

From a people management perspective, this change in the testing approach bridges the gap between developers and testers, encouraging greater collaboration from the start. It also provides an opportunity to automate testing which can reduce human error, eliminate repetitive tasks so teams have more time for value-added work and lower the number of production issues.

Shift left places an emphasis on quality from the start and by testing earlier in the process, teams can eliminate defects and save a lot of time later in the development cycle. When defects are found late in the lifecycle, teams have less time to fix them — leading to production delays, missed deadlines, and potentially unhappy customers. That can affect your bottom line. When you move the testing phase up, bugs can be caught earlier in the development lifecycle and expensive mistakes can be avoided.

Eran Kinsbruner is Chief Evangelist of Test Automation at Perfecto by Perforce
Share this

Industry News

March 18, 2024

Kubiya.ai announces the launch of its DevOps Digital Agents.

March 18, 2024

Aviatrix® introduced Aviatrix Distributed Cloud Firewall for Kubernetes, a distributed cloud networking and network security solution for containerized enterprise applications and workloads.

March 18, 2024

Stride announces the general availability of Stride Conductor, its new autonomous coding product that transforms the software development landscape.

March 14, 2024

CircleCI unveiled CircleCI releases, which enables developers to automate the release orchestration process directly from the CircleCI UI.

March 13, 2024

Fermyon™ Technologies announces Fermyon Platform for Kubernetes, a WebAssembly platform for Kubernetes.

March 13, 2024

Akuity announced a new offer targeted at Enterprises and businesses where security and compliance are key.

March 13, 2024

New Relic launched new capabilities for New Relic IAST (Interactive Application Security Testing), including proof-of-exploit reporting for application security testing.

March 12, 2024

OutSystems announced AI Agent Builder, a new solution in the OutSystems Developer Cloud platform that makes it easy for IT leaders to incorporate generative AI (GenAI) powered applications into their digital transformation strategy, as well as govern the use of AI to ensure standardization and security.

March 12, 2024

Mirantis announced significant updates to Lens Desktop that makes working with Kubernetes easier by simplifying operations, improving efficiency, and increasing productivity. Lens 2024 Early Access is now available to Lens users.

March 12, 2024

Codezero announced a $3.5 million seed-funding round led by Ballistic Ventures, the venture capital firm dedicated exclusively to funding entrepreneurs and innovations in cybersecurity.

March 11, 2024

Prismatic launched a code-native integration building experience.

March 07, 2024

Check Point® Software Technologies Ltd. announced its Check Point Infinity Platform has been ranked as the #1 Zero Trust Platform in the latest Miercom Zero Trust Platform Assessment.

March 07, 2024

Tricentis announced the launch and availability of SAP Test Automation by Tricentis as an SAP Solution Extension.

March 07, 2024

Netlify announced the general availability of the AI-enabled deploy assist.

March 07, 2024

DataStax announced a new integration with Airbyte that simplifies the process of building production-ready GenAI applications with structured and unstructured data.