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Shift Left Testing in 2024: The New Norm of Effective Testing

Cem Dilmegani
Updated on Jan 3
4 min read

Delivering high quality, low defect, and on-time products within the budget allowance is the goal of every project manager. However, delays and going over budgets are common problems in the software development industry. 

In traditional software development models, testers tend to have idle time before the development process is completed so they can start testing but by that time the project deadline is close and there is too much work to be done. Shift left testing can change this and provide benefits such as cost savings and early bug detection. 

In this article we will explore shift left testing, its benefits compared to traditional testing models, challenges, types, and best practices for QA specialists and project managers. 

What is the shift left in testing?

A practice known as “shift left testing” moves testing to the beginning of the development cycle. Testers are participating in crucial program stages while implementing this methodology. Shifting left method seeks to identify problems and minimize risks as early as possible by testing early and repeatedly. Thus, shift left testing might be a more realistic way of detecting bugs for firms compared to typical testing approaches like waterfall testing which starts testing at the end of development.( see Figure 1).

Figure1. Traditional model vs shift left model

This picture shows the difference between shift left and traditional model of testing on a graph.
Source: Geeks for Geeks


Testifi is an automated testing tools provider that supports shift left testing with their AI-based API testing tool PULSE. PULSE decreases the cost of testing by more than 50% and provides insight into the test results in a dashboard format. Many industry giants such as Amazon, BMW, and Vodafone use their products. 

4 Types of shift left testing

There are 4 types of shift left testing.

1- Traditional shift left testing

This approach aligns itself with the traditional V model ( figure 2). Each stage of development has a testing phase according to the V-model, commonly known as the verification and validation model. Shift left testing in this model uses API testing and modern testing tools to focus on :

  • Unit testing
  • Integration testing

Figure 2. Traditional shift left testing

Traditional shift left testing
Source: Wikipedia

2- Incremental shift left testing

This model is most appropriate for large & complex projects. While implementing incremental shift left testing projects are frequently divided into smaller parts that add to one another gradually. Development and testing are moved to the left with each incremental delivery (see Figure 3). incremental shift-left testing shift left developmental testing and operational testing. 

Figure 3. Incremental Shift Left Testing

Figure 3. Incremental Shift Left Testing
Source: Wikipedia

3- Agile/DevOps shift left testing

This approach is useful for projects that are using agile or DevOps testing (see Figure 4). This method is useful for developmental testing and does not include operational testing. 

Figure 4. Agile/DevOps shift-left testing

Agile/DevOps shift-left testing
Source: Wikipedia

4- Model-based shift-left testing

This approach moves testing to the requirement gathering phase which means testing starts before the development starts (see Figure 5). In this approach the followings are tested:

  • Requirements
  • Architecture
  • Design

Figure 5. Model-base shift-left testing

Source: Wikipedia

Benefits of shift left testing compared to traditional testing methods

  • Faster delivery: As testing is conducted earlier, defects are found early and can be fixed faster which results in quick delivery of the project. 
  • Decrease in the cost: The cost of bugs increases as the development moves to later stages. Early bug detection can decrease the cost of fixing bugs considerably (see Figure 6).

Figure 6: Cost of fixing defects

Source: IBM System Science Institute
  • Higher customer satisfaction: High-quality code, on-time delivery, and delivery within budget will ensure customer satisfaction. 

Challenges of shift- left testing

  • Acceptance: shift left testing requires a major shift in the culture of the organization. Developers and testers might be used to their traditional work process but shifting left will be a disruptor. It will disrupt the flow of work, tools, and required skills.

Recommendation: Ensuring alignment in the team is crucial. That is why clear communication is important to internalize the importance of shift left testing. Additionally, planning should be conducted to ensure the smooth functioning of the new approach. 

  • Waste: Not everything can be tested early. Shift left testing has the potential to waste time and effort if the foundation has not been developed yet. For example, if you start writing tests before the development of GUI, there is a high chance the GUI characteristics change by the time it is developed so most of your effort has been wasted. 

Recommendation: If a certain test is important for you to be tested early, development must be done earlier. For example, if API testing is important for your project and you are trying to do shift left testing, develop the API early. 

4 Best practices for shift left testing

1- Test at the correct moment

Testing early should not mean that testing should not happen in relatively later stages. Testing early has the benefit of early risk mitigation and defects detection but defects can emerge in later stages too. Therefore, QA specialists and project managers should not forget the concept of continuous testing. 

2- Automate testing 

Automating testing can save a considerable amount of time for testers as they should test continuously. For more on automated testing, read Automation Testing: Types, Frameworks, Tools & Best Practices.

3- Static code analysis

Static code analysis is the process of analyzing the code without actually running it. This analysis should be done early in the software development cycle. This analysis checks the code with the guidelines and standards. Static code analysis can be automated and can detect problems in the following areas:

  • Programming errors
  • Violations of commonly followed coding standards
  • Syntax anomalies
  • Security issues

4- Offer continuous feedback

Continuous feedback allows misalignments and gaps to be fixed quickly. Additionally, it provides a better insight to everyone involved and improves them for future projects. In order to have an effective continuous feedback loop, organizations should:

  • Explain the reasons for the meetings clearly
  • Set goals for the meeting
  • Take detailed notes of the feedback
  • Have an effective communication pipeline 

Further reading

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Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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