Quality Assurance Vs Quality Control In Software Engineering
In software product development, many teams tend to ignore quality metrics and focus more on quantity. Such teams face challenges when building for production. They end up pushing to production very low-quality software that is filled with bugs. These bugs alone irritate and drive away product users.
In 2022, research done by the Consortium for Information and Software Quality (CISQ) revealed that the cost of poor software quality in the US has grown to at least $2.41 trillion.
The question here is, how can one control and ensure that when building for consumers, they only build quality software that will attract users?
This blog has detailed answers to the above question. It provides solutions to low-quality issues. It covers details on Quality Assurance (QA) and Quality Control (QC) in software engineering, both of which are activities under Quality Management.
In this blog, we discuss the key aspects of QA and QC, examples, similarities, differences, importance, processes,approaches, and best practices for QA & QC.
So, let’s dive right into it.
What is Quality Assurance?
Quality Assurance (QA) is a quality management activity and process that ensures quality in the whole Software Development Lifecycle (SDLC). It is carried out during and after development to ensure products are bug-free. This process helps to prevent bugs from occurring.
The key aspects of Quality Assurance include the following.
QA focuses on prevention. Its goal is to find issues during the planning, designing, and development stages.
QA complies with software engineering standards, including coding standards, frameworks, reviews, audits, and methodologies such as agile and waterfall.
It is a continuously improving process, as it involves constant monitoring and process refinement to achieve better performance.
An example of QA is ensuring that unit tests are written in the early stages of development. For example, let’s examine the sample Python code below, which tests a login function to ensure password validation.
The above snippet defines a validate_password function for checking whether a password is at least 8 characters long and consists of at least a digit. The snippet also includes a test_validate_password function for verifying how correct the earlier function is while using examples of inputs.
Now, QA will define the process where tests like the one shown above are a must in a codebase before merging the pull requests (PR).
What is Quality Control?
Quality Control (QC) is a quality management activity and process that involves identifying and detecting defects, glitches, imperfections, or bugs in the final software product, then correcting them before delivering to the end-users. It is an important process as it ensures only quality products are released to the market.
The key aspects of Quality control include the following.
Its main goal is to identify defects in software products and then fix them.
It focuses more on the product to ensure it meets the essential quality and client requirements.
It involves manual and automated software testing.
QC validates the functionality, performance, and usability of a software product before delivering it to the market.
An example of QC in software engineering is writing automated tests to check actual functionality before releasing the product to the market. Let’s look at the Python example below.
The above snippet defines a function named login for checking if a given username is ‘admin’ and the password is ‘admin123’. If they match, then access is granted; else, access is denied. The test_login function is the QC where we verify that the login function’s behavior is correct. With QC, we ensure that these tests pass before the product is released to the market.
QA vs QC: Similarities between Quality Assurance and Quality Control
Quality Assurance and Quality Control have similarities, given that they are both techniques of quality management. This makes some individuals even use them interchangeably. Let’s have a look at some of the similarities below.
They both focus on delivering better quality software products.
Both ensure that the software functions as required.
Both QA and QC require skilled professionals to carry them out efficiently.
Both have the goal of delivering a bug-free experience to end product users.
Both processes continuously improve software development
They both involve planning and documenting tests
Now that we have examined the similarities, we will explore the key differences between QA and QC in the next section.
QA vs QC: Key differences between Quality Assurance and Quality Control
There are many differences between QA and QC, even though some individuals are unaware of their distinct differences and use them interchangeably. This section explores all of them. They are as listed in the table below.
Importance of Quality Assurance in Software Engineering
As seen from previous sections, Quality assurance is a very important process when managing quality in software development. Let’s have a look at some of the advantages that this process brings to you.
With Quality Assurance, defects are found early during development.
QA increases efficiency and code quality due to set structures and standards for developing a given software product.
It ensures the end product satisfies and retains customers.
It reduces final-stage software costs as defects are detected early.
If well implemented, it promotes collaboration among teams.
Importance of Quality Control in Software Engineering
Just like Quality assurance, Quality control also brings unique advantages to developers building software products while keeping quality in mind. Below, let’s have a look at the importance of quality control in software development.
It helps detect issues before the software product is released to the end users.
It ensures that the software has all the planned features and also works as planned. This ensures that all the software requirements are executed.
It is a final stage that determines whether the software is ready for the market or not.
It also reduces costs that would arise if defective software is released to the market.
This process helps review common errors, which are then documented and avoided in future developments.
The Quality Assurance Process
Quality Assurance is a process with defined steps followed. This section describes these steps so that you can follow them when implementing QA in your building process. This will guarantee that your product satisfies the set quality standards and specified customer requirements. The steps below are followed.
Planning
Defining Processes
Training
Auditing
Continuous Improvement
The Quality Control Process
Like QA, Quality Control is a process with defined steps to ensure it is effective and easy to implement. This process, when well implemented, following the steps in this section, helps systematically detect and remove issues in products that are ready to be pushed to the market so that only quality products reach the end users and thus promote retention and avoid customer complaints. Let’s have a look at the detailed steps to follow below.
Requirements definition
Test Planning
Test Execution
Defect Logging
Reporting
Quality Assurance vs Quality Control: Approaches
Now that we have examined the importance, differences, and processes of QA and QC, let’s have a look at some of the strategic approaches companies use for each process to achieve quality software products.
Quality Assurance Approaches
These are strategies implemented by organizations to set quality into the process of software development so that their end software products meet required standards and satisfy their consumers.
Below are some of the commonly used QA approaches.
Total Quality Management (TQM)
Six Sigma
Plan-Do-Check-Act (PDCA)
Lean Manufacturing
The Theory of Constraints
Agile Methodology
Quality Control Approaches
These are the various techniques used for finding, correcting, and preventing defects in final software products. They are utilized to ensure that the product is of set standards and offers user satisfaction.
Below are some of the common QC approaches.
Statistical Process Control
Taguchi Method
Inspection
Quality Circles
Checklist
Best Practices for Implementing QA & QC
If you want your company to maintain a high-quality product lifecycle, knowing the best practices is important for both QA and QC. In this section, we dive into some of the most effective practices used even by teams at top technology companies. Have a look at them below.
Quality Assurance (QA) Best Practices
Establish clear quality standards, guidelines, and procedures to ensure consistency across teams.
Integrate QA activities early across all development cycles to help find and correct bugs early.
Promote the use of Test-Driven Development (TDD) to ensure that software requirements are transparent and clear and reduce rework by detecting bugs early.
Create linkages between requirements and test cases to ensure better coverage and impact analysis in case of any changes.
Provide team-wide or company-wide training on quality assurance and its importance.
Use QA tools and automation tools like Keploy to reduce manual errors and promote efficiency.
Quality Control (QC) Best Practices
Set up comprehensive and detailed test plans that follow the defined software requirements, risks, and set goals. These plans should consist of functional and non-functional requirements, edge cases, and user scenarios.
Utilize modern software testing tools like Keploy, Postman, JUnit, or PyTest for better test coverage, efficiency, and reliability.
Track and analyze bugs based on their rate of occurrence and their severity levels to ensure close monitoring and severity-based fixing.
Perform exploratory testing where the software testers interact with the software product in order to find interaction and usage errors that might have been missed by the script tests.
Automate the entire software testing process in CI/CD pipelines to provide feedback during deployment stages, as well as save time and increase confidence for every code pushed to production.
Accelerating QA and QC using Keploy
Keploy is an open-source AI-powered software testing tool. It makes software testing easy and productive for QA & QC teams. Its AI-powered capabilities help software testers and developers generate unit and API tests quickly, thus increasing development as developers focus on writing code rather than writing tests.
Keploy creates test cases and data mocks/stubs from user traffic by recording API calls and DB queries, significantly speeding up releases and enhancing reliability.
It supports multiple programming languages, including Python, JavaScript, Java, Go, Rust, and C#. This makes it available for a wider community of software developers, thus no one is left out to work on long and time-consuming tasks manually, rather focus on core development tasks.
Keploy comes with AI-powered agentic tools integrated into it for streamlining the software testing process. These agentic tools work as intelligent assistants for developers during development. These tools include:
Conclusion
In this blog, we explored in detail Quality Assurance (QA) and Quality Control (QC), their similarities and differences, their importance in software engineering, the process and approaches of each technique, and the best practices to follow when implementing QA and QC in your organization.
With the rise of demand for better quality software products, the need for implementing QA & QC is unavoidable. Keploy with its AI-powered capabilities can help streamline this process so that your team focuses more on code writing and development rather than spending a lot of time writing tests.
Related Blogs
Top 10 AI Tools Transforming Software Quality Assurance In this blog, you will discover how different AI tools like Keploy are revolutionising QA by enabling faster, smarter, and more reliable testing processes.
Mastering Test Coverage in Software Testing – Quality Over Quantity This blog explores the concept of test coverage, its nuances, challenges, and the human element that goes beyond mere statistics.
QA Automation: Revolutionizing Software Testing This blog dives deeper into QA automation, exploring the key components of QA automation, different types of QA automation testing, and what tools are used for QA automation.
Revolutionising Unit Test Generation with LLMs This blog explores how Large Language Models (LLMs) like ChatGPT, DeepSeek, Grok, etc, can be used for auto-generating unit tests.
FAQs
Q1. Can one implement QA without QC?
No, QA prevents defects, but QC ensures defects aren’t shipped. So they both need to be implemented.
Q2. Is testing part of QA or QC?
Testing is primarily a QC activity, but test planning and test strategy fall under QA.
Q3. What’s the biggest benefit of QA?
Prevention of defects early in the development lifecycle saves time and cost.
Q4. What best tools are commonly used in QA and QC?
Keploy, Postman, Pytest, Selenium, Playwright
This article was originally published on Keploy.io.