Software Quality Assurance (SQA) and Secure Coding using Python Training by Tonex
(5 Days)
Course Description
This comprehensive course is designed to equip software developers, quality assurance professionals, and aspiring cybersecurity specialists with the knowledge and skills required to ensure software quality and security throughout the development lifecycle using the Python programming language. Participants will learn how to implement effective Software Quality Assurance (SQA) practices and secure coding techniques to create robust and secure Python applications. This course will cover best practices, tools, and methodologies essential for building reliable, high-quality, and secure software.
Learning Objectives:
By the end of this course, participants will be able to:
- Understand the principles of Software Quality Assurance (SQA) and its importance in software development.
- Apply secure coding practices to develop Python applications that are resilient to common vulnerabilities.
- Identify and mitigate security risks in Python code.
- Use testing frameworks and automation tools for SQA in Python.
- Perform code reviews and analyze code for quality and security.
- Develop strategies for continuous integration and continuous delivery (CI/CD) with a focus on security.
- Create secure APIs and web applications using Python.
- Implement secure authentication and authorization mechanisms.
- Analyze and secure data storage and transmission in Python applications.
Audience:
This course is ideal for software developers, software engineers, quality assurance professionals, and individuals interested in software security who have a basic understanding of Python programming. It is suitable for both beginners looking to strengthen their Python skills and experienced developers aiming to enhance their knowledge of secure coding and software quality assurance.
Course Modules:
Pre-test 1
Module 1: Introduction to Python SQA
- Overview of Software Quality Assurance
- Importance of SQA in Python Development
- Common Challenges in Python Software Quality
Module 2: Writing Effective Test Cases
- Understanding Test Case Design
- Best Practices in Python Test Case Documentation
- Handling Edge Cases and Exceptions in Python
Module 3: Python Testing Frameworks
- Overview of PyTest and Unittest
- Setting Up and Configuring Testing Environments
- Executing and Analyzing Test Results
Module 4: Automated Testing Strategies
- Introduction to Test Automation
- Building and Executing Automated Test Scripts in Python
- Integrating Automated Testing into Development Workflows
Module 5: Code Analysis in Python
- Utilizing Static Analysis Tools
- Identifying and Addressing Code Smells
- Continuous Monitoring for Code Quality Improvement
Module 6: Continuous Integration and Delivery (CI/CD) for Python Projects
- Implementing CI/CD Pipelines for Python Applications
- Automated Deployment and Release Management
- Ensuring Consistency and Reliability in Python Software Delivery
Module 7: Introduction to Secure Coding with Python
- Principles of secure coding
- Secure development lifecycle
- Input Validation and Sanitization
- Sanitizing user inputs
- Authentication and Authorization
- Secure File Handling
- File access and permissions
- Preventing directory traversal
- Sensitive data protection
- Cryptography and Data Encryption
- Secure API Development
- Secure Code Review and Testing
Workshop 1: Software Quality Assurance (SQA) workshop using python
- Role of automation in SQA.
- Automated Testing with Python
- Unit Testing with unittest
- Test Automation Frameworks
- Web and API Testing with Python
- Web Testing with Selenium
- API Testing with requests
Workshop 2: Python security and Programming Best Practices (Hands-on)
- Security Logging and Analytics: Implementing security logging and analytics to detect and respond to security incidents.
- Attack Detection and Defense: Strategies and tools for detecting and defending against cyberattacks.
- Tools to Analyze Insecure Packages: Tools and practices to analyze and secure third-party packages used in your Python applications.
- Errors and Exception Handling: Properly handling errors and exceptions is essential for creating robust and secure Python applications. It helps prevent crashes and provides graceful error messages.
- Modules and Packages: Python uses modules and packages for code organization and reuse. Understanding how to create, import, and use modules and packages is crucial.
- Securing File Systems: Ensuring the security of your file system and file operations is essential, especially when dealing with sensitive data.
- Paths, Directories, and Filenames: Understanding how to work with file paths, directories, and filenames securely is important for file operations.
- Network Services: Python can be used to develop network applications. Understanding network protocols, security, and best practices is crucial for secure network services.
Workshop 3: Writing Secure Python Applications: General best practices for writing secure Python applications, including input validation, authentication, and authorization.
- Securing Dangerous Operations: Implementing security measures when performing potentially dangerous operations.
- Using Variables and Functions: In Python, variables are used to store data, and functions are blocks of reusable code. Properly managing variables and functions is essential for code organization and security.
- Classes: Python is an object-oriented programming language, and classes are used for defining objects and their behaviors.
- Regular Expressions: Regular expressions (regex) are powerful tools for pattern matching and text manipulation. They are often used in data validation and parsing.
- Parsing Command-Line Options: Parsing command-line arguments securely is important for creating command-line applications.
- Safely Handling Untrusted Data: Properly handling data from untrusted sources to prevent security vulnerabilities like injection attacks.
- Managing eval() Permissions: Limiting the use of the eval() function to prevent code injection vulnerabilities.
- Embedding Code Snippets: Embedding authentication data securely within your code.
- DB-API: Database programming in Python using the DB-API standard.
- Log File Analysis: Analyzing log files for security incidents and anomalies.
- Security Filters: Implementing security filters to protect against attacks like Cross-Site Scripting (XSS).
- Packet Analysis: Analyzing network packets for security monitoring and intrusion detection.
- Flow Control: Flow control includes concepts like conditional statements (if, else), loops (for, while), and branching, which are crucial for controlling the execution flow of your program securely.
- Sequences: Sequences in Python include lists, tuples, and strings. Understanding how to work with these data structures is fundamental to Python programming.
- Working with Files in Python: Python provides various modules and functions for working with files, which is important for reading, writing, and managing data securely.
- Nested and Returning Values: Nesting functions and returning values from functions are common practices in Python programming.
- Sorting: Sorting data is a common task in programming. Python offers built-in functions and modules for sorting data efficiently.
Post-tests
Final Project:
Participants can work on a small final project where they apply the knowledge gained during the workshop.