As enterprises massively leap to an Agile adoption, software development, and testing teams need to move at a faster pace while rolling out high-quality IT products preferred by end users. This can be possible with a shift-left testing (SLT) approach.

Companies who choose SLT can obtain huge advantages, such as earlier identification of defects, faster time to market, increased software quality, or improved QA efficiency, to name a few, allowing them to avoid possible losses. And they can be extensive, believe me — according to research, in 2022, the US economy may have lost up to $2.41 trillion because of software issues.

Despite growing popularity, this concept and its implementation still raise questions. In this article, I’ll focus on the essence of this approach, its benefits for business, implementation tips, and challenges.

Meaning and significance of the groundbreaking approach

Traditional ways of crafting software solutions presuppose that QA and software testing activities are done at the end project stages, which can complicate the overall process as the cost and time of fixing issues of diverse severity increase exponentially. This is because it may be necessary to fully alter the solution from the ground up.

It could be said that SLT is the exact opposite of this model. Its effectiveness lies in the search for bugs as early in the SDLC as possible. As QA engineers quickly delve into product specifics and detect issues or ambiguity at the requirements stage, software quality improves, while testing time reduces.

Currently, there are several types of SLT, such as traditional, incremental, Agile/DevOps-driven, or model-based. The choice of the type depends on individual project characteristics, such as size, complexity, duration, team composition, and more.

Big perks brought to the table

From my experience, I can highlight the most remarkable pluses of changing settled workflows:

How to effectively establish the practice

Although comprehensive verifications enhance the technical health of software, the implementation of this approach may still be challenging for the companies. So, I suggest considering the following steps for the smooth introduction of SLT on a project:

1. Embed QA from the get-go

To get the maximum effect from the SLT approach, QA teams need to incorporate testing into the project as early as possible, for instance, ideally at the stage dedicated to requirements or brainstorming sessions. This way software testing engineers can define any ambiguities, logical contradictions, or other problems, and provide a clear explanation of possible bugs and ways of preventing them, thus decreasing the risk of their appearance later in the SDLC and minimizing the cost of their fixing.

2. Rely on automated QA workflows

As SLT is all about frequent software verifications, prioritizing manual testing becomes a challenging task, especially if the project is large and requires working with an extensive regression testing scope. Therefore, test automation can become a game-changer.

By utilizing it, project teams can considerably broaden coverage, improve testing accuracy due to minimizing the probability of human errors, and obtain feedback on software quality quicker. So, it’s not surprising that the respondents of the World Quality Report (WQR) 2023-24 expect a lot from it. They stated that automated testing implemented on the projects should contribute to decreasing the number of live issues (51%), lowering testing efforts (50%), and enhancing customer experience (50%).

Currently, teams can choose from a wide variety of commercial or open-source test automation tools (from Selenium to Playwright) able to fit any QA budget, specialists’ knowledge, ease of maintenance, reporting, integration, unique testing requirements within a project, or several other priorities.

In addition, I can recommend paying attention to the usage of artificial intelligence (AI) in testing, which is gaining momentum nowadays. 74% of WQR’s interviewees actively use it to optimize their QA workflows. For instance, when an AI-based component is applied for determining failed tests and generating corresponding reports, test failure analysis becomes quicker.

3. Prioritize continuous interaction

To establish this, teams should stick to the practice of regular sync-ups, QA engineers’ participation in analyzing requirements, and bear in mind the importance of effective written communication that can contribute to better resolution of defects. Such constant interaction helps ensure quick problem-solving, identify and rectify software issues faster and easier, delve deeper into IT products’ specifics, boost project productivity, minimize the risks of software failures in the future, and ensure in-time delivery of the planned functionality.

4. Maintain consistent standards

The developers need to agree with the usage of unified standards of writing code within a project they are working on. This contributes to the delivery of robust, straightforward, and maintainable code from the get-go. In addition, automated static code analysis helps scrutinize the entire code, identify diverse problems, and detect parts that aren’t compliant with existing standards.

As for QA specialists, they need to establish quality gates for diverse SDLC phases. This helps to make sure no deviations from the requirements occur during software development.

Possible process challenges

I think it’s worth paying attention to the most probable bumps in the road that need to be overcome:

Final note

I do believe that prevention is better than cure. And SLT is exactly this. By moving testing to the earlier SDLC phases, project participants can find problems at the project stage when fixing is easy and inexpensive, thus optimizing overall efforts and making sure business goals are met.

To set up this beneficial approach, teams can engage QA engineers earlier, introduce test automation, establish effective cooperation between project members, and adhere to essential standards.