SCQA in software engineering is a set of practices, tools, processes, and metrics that must be followed by development teams to ensure the delivered software code is high quality. Crafting an SCQA plan is usually a collaborative effort across multiple stakeholders throughout the software development lifecycle.

Software quality assurance program focuses on meeting quality objectives like:

• Consistency: Ensuring consistency in the code.
• Readability: Improved code clarity to isolate and debug defects or issues.
• Maintainability: simplify the code to modify, extend, and refactor easily.
• Security: Reducing vulnerabilities and adhering to security standards and best practices.
• Performance: Writing efficient and optimized code.
• Bug reduction: Proactively discover and resolve defects/issues earlier in the development process.

These are a set of methodologies every software development team should use when building a quality assurance plan:

Test-driven development (TDD) is a software development practice in which tests are written prior to writing the actual code. A developer writes a test case for a requirement and tests to verify if the code can pass it. This practice helps promote good coding practices as the code is written to be passed by the code.

Behavior-driven development focuses on ensuring that the code delivers value to the end user by adhering to defined behaviors. The business value is defined in user stories written in plain language, which are then converted into automated tests.

Pair programming software development has two developers on one station. One writes the code, and the other reviews each line of code. This approach improves on-time code reviews and collaborative efforts and reduces issues in the code.

CI/CD is a software development practice that automates the process of building, testing, and deploying code changes.

• Continuous Integration (CI) focuses on frequently merging code changes into a shared repository. This ensures that new code integrates smoothly by running automated tests to catch issues early.
• Continuous Deployment (CD) automates the process of delivering tested code to production quickly and reliably.

CI/CD pipelines manage these tasks step-by-step, from building code and running tests to deploying updates, ensuring that software changes are safe and consistent.

Static code analysis involves examining source code without executing it to identify potential vulnerabilities, bugs, or compliance issues. SCA tools analyze code to detect security flaws, coding errors, and style violations early in the development process-before the application is even run.

• Readability: How easy the code is to understand. This helps team members to collaborate and maintain the code easily.
• Maintainability: How easy it is to modify, extend, or refactor the code.
• Performance efficiency: Appropriate use of efficient algorithms, memory management, and caching will help reduce the quantity of resources consumed and optimize the response times.
• Scalability: Guarantees that the application can be scaled up for increased traffic volumes while still performing efficiently.
• Security: Resilience of the code against threats and vulnerabilities.
• Reusability: How much of the code can be reused or shared when writing a new feature.
• Consistency: The degree to which the same conventions of usage and patterns were used throughout the codebase document.
• Fault tolerance: How gracefully the code handles the system errors and recovers without crashing the entire system.

Creating a software quality assurance planning is a collaborative effort from various stakeholders:

1. Lead developer or engineering manager

• Defines coding standards and guidelines and sets quality gates and metrics.
• Selects tools for SCA (static code analysis), testing, and CI/CD.
• Trains and coaches developers.

2. Quality assurance (QA) engineers or test engineers

• Develop testing strategies and methodologies.
• Implement test case automation.
• Validate test cases.

3. Developers

• Follow best practices and coding conventions and set guidelines.
• Actively participate in code review sessions.
• Write unit tests and automated tests.
• Implement CI/CD.

4. Product manager or project manager

• Defines the business-driven quality goals and their acceptance criteria.
• Provides the communication foundation between technical and non-technical teams.

5. DevOps engineers

• Set up and manage CI/CD pipelines.
• Ensure smooth running of automated tests in test environments.
• Provide close observation of the infrastructure’s health.

6. Security engineers

• Integrate security best practices and security test tools like SAST, DAST, etc.
• Discover vulnerabilities, threats, and security flaws.
• Perform security audits.

7. Business owners and clients

• Define business requirements and goals.
• Determine final acceptance criteria and benchmarks.
• Facilitate feedback for the final approval.

Building high-quality code requires clear metrics, coding standards, automation, and continuous improvement. This section highlights key strategies and practices to create reliable, scalable, and maintainable software.

1. Clear definition of the code quality metrics

• Code coverage: This shows the percentage of a codebase that has been tested with automated tests. Tools like JaCoCo (for Java), Istanbul (for JavaScript), and Coverage.py (for Python) are the most popular tools today.
  

  Source: https://istanbul.js.org/

• Code complexity: Measures the complexity of a program’s control flow. High complexity indicates that the code is difficult to understand and maintain and is error-prone. Tools like SonarQube or CodeClimate can calculate this metric.
  

  Source: https://codeclimate.com/

• Code churn: The percentage of code that has been modified, added, or deleted over a specific period. Churn should not exceed 10-15% within a sprint or development cycle.

2. Implement coding standards and best practices

• Use meaningful variable and function names.
• Use proper indentation and whitespace for readability and keep functions short and focused.
• Add comments for complex or non-obvious sections of the code to reference.

3. Use static code analysis tools

• Use tools like SonarQube, Checkmarx, or ESLint to automate static code analysis, which will effectively detect common coding issues and security vulnerabilities and enforce coding standards.
  

  Source: https://eslint.org/

• Setting up automated linting can help to identify issues prior to committing the code to the repository.

4. Automate testing and continuous integration

• Unit testing: Should cover edge cases, inputs, and outputs.
• Integration testing: Ensure that different modules interact as expected.
• Implement continuous integration (CI): Ensure CI has been implemented along with automated test suites to ensure that code changes don’t break functionality.

5. Integrate QA early in the SDLC

• Integrating QA from the planning and designing phase will reduce the chances of discovering issues or defects later, which will help reduce the cost of fixing them.

6. Initiate feedback loops

• Continuous feedback from tools, code reviews, and tests will ensure developers improve their skill set and help them avoid repeating mistakes.
• Post-mortem analysis, continuous performance monitoring, training, and knowledge sharing can be key actions that may be conducted for continuous improvement.

7. Use tools as support, not as a replacement

• Tools like SCA or linters are often employed to assist developers in maintaining code quality.
• However, these cannot discover architectural or design flaws. So, don’t be solely dependent on these automated tools; use them for additional safety.

8. Maintain a clean and modular codebase

• Write modular code that’s easy to test and maintain. Avoid large, monolithic files and create small, reusable components to simplify updates and debugging.

9. Keep dependencies updated and secure

• Regularly audit dependencies to detect vulnerabilities and ensure compatibility with the latest versions.

10. Foster accountability and documentation

• Encourage developers to take ownership of code quality and provide the necessary training, tools, and time for refactoring.
• Maintain clear documentation of coding guidelines, architectural decisions, and practices to serve as references for teams.

Here are three organizations that have successfully implemented comprehensive SCQA plans through automation, continuous integration, rigorous testing, and a culture of quality.

Let’s see how these companies have implemented their SCQA plans.

Microsoft is one of the biggest market leaders, focusing mainly on maintaining code quality, especially for its widely used software products, Windows and Office.

Automated testing:

• The company uses automated testing extensively coupled with structured code quality unit tests within its Azure DevOps platform in a continuous integration environment.
• As a result, human errors that could easily distort the quality have been significantly reduced.
• Each commit is automatically tested, and quality gates are set up to ensure that only the code that complies with the predefined quality standards is deployed into production.

Static code analysis:

• Development teams at Microsoft use SonarQube and other static analysis tools to perform a semi-automated verification of the entire code base.

Code reviews

• Code reviews at Microsoft are mandatory for any changes to the codebase.
• The company encourages pair programming and continuous feedback to foster better collaboration and higher quality.

Netflix is a market leader known for its continuous delivery of high-quality software. The most important factor behind its success is its capability of scaling with its microservices architecture to support millions of global users.

CI/CD pipelines

• Netflix has a significantly automated testing pipeline that contains unit, integration, and acceptance tests.
• This deployment architecture ensures that every single change made in the system undergoes proper scrutiny before it becomes operational.
• To manage and automate deployments, Netflix uses an open-source continuous delivery platform called Spinnaker.

Chaos engineering

• Chaos engineering is one standout feature in Netflix’s SCQA plan that is used to maintain the quality of its system in the live environment.
• They employ tools like Chaos Monkey to cause failures intentionally in a controlled manner to validate how resilient the system is to various failures.

Monitoring and feedback loops

• Upon deploying the code, Netflix depends on sophisticated monitoring tools such as Atlas and Turbine (for real-time data aggregation) to observe the behavior of the code in production.
• Immediate feedback from monitoring tools helps discover issues that might not have been detected prior to production.

Automated code reviews and continuous performance monitoring are the secrets behind Shopify’s rapid delivery and reliability.

Automated code reviews

• Shopify integrates automated code reviews using tools like GitHub Pull Requests and Code Climate to enforce coding standards and quality checks.
• Each pull request is subject to automated checks for style, complexity, and potential bugs.

Performance monitoring and testing:

• Automated performance testing is a key part of Shopify’s CI/CD pipelines.
• They use tools such as Google Lighthouse and New Relic to test for performance regressions prior to production deployment.
• The development teams also focus on metrics such as page load time and transaction speed to ensure the effectiveness of the platform.

Security practices

• Shopify employs an integrated approach to security, where automated security scans are a part of the development lifecycle.
• This includes vulnerability scanning tools such as Brakeman and Dependabot for automated dependency updates, allowing the known vulnerabilities to be quickly identified and patched.

Crafting a detailed code quality assurance plan is essential as it helps to ensure the software is robust, secure, and maintainable. Developers can continuously enhance the quality of their code by using proven practices like TDD, BDD, and CI/CD, automating tests, performing comprehensive code reviews, and assessing the codebase regularly.

To achieve long-term code quality, it’s important to implement key strategies and best practices, including static code analysis, modular design, and continuous feedback loops. These approaches help establish quality gates and ensure automation-driven delivery.

By following these strategies, teams can not only minimize defects but also boost productivity, enhance software performance, and improve user satisfaction.