Moving from Quality Assurance to Quality Engineering


Organizational alignment is vital to the growth of the software engineering process. As the digital world transforms, it is crucial for QA to keep pace with this transformation. As organizations continue their digital transformation journey, the focus is on quickly delivering innovative and top-quality software. Quality assurance plays a vital role in achieving a successful digital transformation. In particular, software quality testing becomes critical before, during, and even after the digital transition.

Quality Assurance (QA) is integral to the Software Development Life Cycle (SDLC); however, it needs a transition to Quality Engineering (QE) to keep up with the pace of changing technology.

Quality Assurance (QA) vs. Quality Engineering (QE)

While “Quality Assurance” assures the quality of the product, “Quality Engineering” drives the development of quality products and processes. Simply put, QA is proactive and identifies defects in the developed software, whereas QE extends QA through a technical transformation from (mostly) manual to (mostly) automated processes. Moreover, QE follows the shift-left approach and starts test automation early in the software development life cycle.

Transitioning from QA to QE is not difficult—it just requires a change in approach and processes. The good news is that you don’t need Google’s budget to implement industrial-strength Quality Engineering. The transition can be achieved by implementing changes to your existing processes including:

    • QA engineering team transformation

Organizations can reskill their existing team to make a successful QA to QE transition. It involves transforming the culture and the team’s mindset and upskilling the resources and tools. Since the existing QA engineer(s) already have a good understanding of the product, it will be easier for them to make a transition to QE.

    • Shift-left testing approach

The shift-left approach involves QA from the beginning of the development life cycle and allows it to participate in the software design sessions and creation of test strategies. Similarly, QE gets involved from the beginning of the development life cycle. However, its focus is on creating a robust test strategy for achieving greater levels of test automation.

    • Automation Testing with AI/ML capabilities

Upskilling the testers with automation testing skills can leverage intelligent test automation to increase coverage and quality. Developing a robust automation framework helps smooth the transition from QA to QE.

    • DevOps implementation

Continuous Integration (CI) and Continuous Deployment (CD) pipelines help save a lot of time and effort spent on manual, error-prone deployment work. They work in tandem with shift-left testing to drive quality from the start of the software development lifecycle. Moreover, automated tests can be incorporated and scheduled to run after every deployment.

QA to QE transition helps an organization to effectively enable digital transformation and guarantees the desired customer experience. QE aids in building platforms that bring various tools, utilities, and AI/ML techniques together with lifecycle automation (business process, functional UI, API, test data, and environment). Moreover, the transition offers the best and most efficient coverage across code and functionality that helps in continuously improving product quality.


Bringing Quality Engineering Expertise

Celsior is developing a series of blogs covering various QE areas. These will include:

      • Automation – Getting the most out of open-source

We will cover how QE can leverage open-source tools for implementing intelligent test automation not only for functional but API, database, etc. testing across the project to offer the best and most efficient coverage across code and functionality.

      • AI – Adding AI capabilities

AI/ML are not just buzzwords, but can do wonders for QE. In this blog, we will provide tips for leveraging AI/ML techniques together with functional automation. The blog will provide additional insights into improving customer experience and reducing script maintenance costs.

      • Mobile Automation – Getting the most bang for your buck

Most applications include mobile functionality. Thus, we will shed light on how to use test automation and device clouds to test on mobile devices in order to provide better coverage and time efficiency. The blog will also provide more insights on mobile and app performance parameters.

      • DevOps – CI/CD, Monitoring, and SRE

In this blog, we will cover how QE can utilize DevOps (CI/CD) to get faster testing results. We will also discuss the role of QE in monitoring and keeping critical systems up and running.

      • ETL Data Validation

ETL data validation is typically a manual process with its own challenges and drawbacks. For instance, the tools available in the market are notably expensive. In this blog, we will cover how ETL data validation can be done using the Celsior data framework.

Keep following this space for additional insightful blogs on Quality Engineering and other IT support services that can enhance your digital transformation initiatives.

23 September 2022

      • Quality
      • Automated Testing
      • Automation
      • Software Quality Assurance
      • Software Testing
      • Software Testing Services



Vikas Shukla
Director – Quality Engineering

Himanshu Gosain
Senior QE Architect


Read other blogs of the series to get more insights on Quality Engineering, QE services, and QE Automation:

Test Automation – Getting the most out of open-source
Adding AI capabilities to a Test Automation Framework
Mobile Test Automation – How to get the most bang for your buck
ETL Data Validation – Better decision making through improved data quality
Role of Quality Engineering within DevOps and CI/CD

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