Author: Rony Barua

Understanding the Difference Between SDET and QA Analyst: The Essential Roles in Software Testing

In the fast-paced world of software development, ensuring the quality of a product is paramount. Software testing plays a crucial role in identifying defects, improving usability, and verifying the functionality of an application. However, within the field of software testing, two roles often cause confusion: Software Development Engineer in Test (SDET) and Quality Assurance (QA) Analyst. While both aim to deliver high-quality software, their approaches, skill sets, and responsibilities differ significantly. This article aims to clarify these differences and shed light on the impact each role has in modern software development.

What is a QA Analyst?

A Quality Assurance Analyst (QA Analyst) focuses on ensuring that the product meets user expectations, functional requirements, and overall usability. They are primarily concerned with manual testing and exploratory testing, evaluating the product from the end user’s perspective.

Key Responsibilities of a QA Analyst:

– Manual Testing: QA Analysts execute test cases manually to identify defects and ensure that the software meets its functional requirements. Manual testing is essential when testing user interfaces, workflows, and usability aspects that are challenging to automate. – Test Case Design: They write and design detailed test cases based on requirements, ensuring comprehensive coverage of the application’s functionality. – Exploratory Testing: QA Analysts engage in unscripted, exploratory testing to uncover potential edge cases and usability issues that automated tests may not identify. – Collaboration with Teams: They work closely with product owners, developers, and designers to validate workflows and ensure the application is user-friendly. – Bug Reporting and Tracking: Defects found during testing are logged, tracked, and managed using tools like JIRA, ensuring they are addressed before release.

Tools and Skills Used by QA Analysts:

– JIRA for bug tracking and project management. – TestRail for test case management and reporting. – Postman for API testing. – Knowledge of manual testing methodologies and test execution.

When is a QA Analyst Most Valuable?

– Small to medium-sized applications. – Early-stage projects where the product’s user interface and usability need detailed testing. – Projects that require human intuition for exploring new features and identifying potential user experience issues.

What is an SDET?

A Software Development Engineer in Test (SDET) is a specialized role that bridges the gap between development and testing. SDETs focus on test automation, creating frameworks and tools that ensure continuous testing across various stages of the Software Development Life Cycle (SDLC). They possess strong software development skills and are heavily involved in CI/CD pipelines, ensuring that quality is maintained at every stage of the development process.

Key Responsibilities of an SDET:

– Test Automation: SDETs write automated test scripts for unit tests, integration tests, UI tests, and performance tests. Automation significantly speeds up testing cycles and ensures comprehensive test coverage. – CI/CD Integration: SDETs are involved in setting up and maintaining Continuous Integration (CI) and Continuous Delivery (CD) pipelines. They ensure that automated tests are executed whenever code is integrated, allowing for fast feedback. – Building Test Frameworks: SDETs develop reusable test frameworks that can be applied across different projects, making it easier to scale testing as the application grows. – Performance and Load Testing: They also conduct performance tests, stress tests, and load tests to ensure the application can handle high traffic and remains stable under peak loads. – Shift-Left Testing: SDETs work alongside developers to shift testing earlier in the SDLC, allowing defects to be identified and fixed earlier in the development process, which reduces costs and speeds up time-to-market.

Tools and Skills Used by SDETs:

– Automation Tools: Selenium, Cypress, Playwright, Appium for automating UI and API tests. – CI/CD Tools: Jenkins, GitLab CI, CircleCI, Travis CI for integrating tests into the development pipeline. – Languages: Proficiency in programming languages like JavaScript, Python, Java, and C#. – Containerization: Tools like Docker and Kubernetes for creating test environments and ensuring tests run in consistent conditions.

When is an SDET Most Valuable?

– Large, complex applications where manual testing becomes inefficient. – High-velocity teams in Agile or DevOps environments, where quick releases and continuous testing are necessary. – Applications that require extensive automated regression, load, and performance testing.

Key Differences Between QA Analysts and SDETs


Which Role is More Impactful in Today’s Development Environments?

The importance of each role largely depends on the nature of the project and the testing strategy adopted by the organization. – SDETs are crucial in large-scale, fast-paced environments, especially with frequent code changes and deployments. They enable continuous testing and feedback, which is essential in Agile and DevOps settings. Automation not only saves time but also increases test coverage, ensuring that defects are caught early in the development process. – QA Analysts remain invaluable for manual testing, especially in validating user experience, UI consistency, and edge-case scenarios that may be difficult to automate. Conclusion: Both SDET and QA Analyst roles are essential for delivering high-quality software. While the SDET role is focused on automation and scalability, the QA Analyst role ensures that the product is user-friendly and meets functional specifications. The key to success lies in the collaboration between these two roles, ensuring that software is thoroughly tested, performs well, and delivers a seamless experience to users.

Searching Across All Tables in SQL Server for Specific Data

Introduction

Searching for specific data in a database with hundreds of tables can be a challenge. This guide demonstrates how to dynamically search all tables in SQL Server for a specific value using a script. This approach is useful when you don’t know which table or column contains the data.

Why This is Useful

  • Large databases with many tables and columns.
  • Unfamiliarity with the database schema.
  • Debugging or data migration tasks.

The SQL Script

Below is a complete script you can use to search for any value across all tables and columns in your database. It works for text and GUIDs (uniqueidentifier), handles missing tables, and avoids syntax issues.

DECLARE @SearchValue NVARCHAR(255) = 'your_search_value'; -- Replace with your value
DECLARE @SQL NVARCHAR(MAX) = '';
DECLARE @TempSQL NVARCHAR(MAX) = '';

-- Dynamically build the SQL query for all text-based and uniqueidentifier columns
SELECT @TempSQL = (
    SELECT 
        CASE 
            WHEN OBJECT_ID(TABLE_SCHEMA + '.' + TABLE_NAME, 'U') IS NOT NULL THEN 
                'SELECT ''' + TABLE_SCHEMA + '.' + TABLE_NAME + ''' AS TableName, ''' + COLUMN_NAME + ''' AS ColumnName, ' +
                '[' + COLUMN_NAME + '] AS MatchFound ' +
                'FROM [' + TABLE_SCHEMA + '].[' + TABLE_NAME + '] ' +
                'WHERE [' + COLUMN_NAME + '] LIKE ''%' + @SearchValue + '%'' UNION ALL '
            ELSE ''
        END
    FROM INFORMATION_SCHEMA.COLUMNS
    WHERE DATA_TYPE IN ('char', 'varchar', 'text', 'nchar', 'nvarchar', 'ntext', 'uniqueidentifier')
    FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)');

-- Remove the trailing 'UNION ALL'
IF LEN(@TempSQL) > 10
    SET @SQL = LEFT(@TempSQL, LEN(@TempSQL) - 10);

-- Execute the dynamically generated SQL if valid
BEGIN TRY
    IF @SQL <> ''
        EXEC sp_executesql @SQL;
    ELSE
        PRINT 'No matching data found.';
END TRY
BEGIN CATCH
    PRINT 'An error occurred, but it was ignored: ' + ERROR_MESSAGE();
END CATCH;

How It Works

  1. Dynamic Query Generation:
    • The script dynamically generates SQL queries for all tables and columns where the data type matches char, varchar, nvarchar, text, ntext, or uniqueidentifier.
  2. Object Existence Check:
    • It uses OBJECT_ID to ensure tables exist before querying them, avoiding errors from missing tables or views.
  3. Error Handling:
    • A TRY...CATCH block ensures that any errors (e.g., syntax issues or inaccessible tables) are safely ignored.
  4. Safe Execution:
    • The script avoids invalid SQL by trimming trailing UNION ALL and skips non-existent objects.

Use Cases

  • Debugging: Locate specific data in a large database.
  • Data Migration: Identify where specific values are stored for migration.
  • Auditing: Ensure sensitive information is properly stored.

Security Testing for Critical Systems in Software Testing

Introduction:

In today’s increasingly interconnected world, software systems are central to the functioning of businesses, governments, and industries. Many of these systems, such as financial applications, healthcare systems, defense technologies, and critical infrastructure, handle sensitive data or control essential processes. For such systems, security is paramount. A security breach can lead to data loss, financial damage, compromised operations, or even loss of life. Therefore, ensuring the security of critical systems through rigorous testing is an essential component of the software development lifecycle.

What is Security Testing?

Security testing is the process of evaluating a software application or system to identify vulnerabilities, weaknesses, or threats that could lead to unauthorized access, data leakage, or manipulation. It aims to protect the system from malicious attacks, prevent data breaches, and ensure that sensitive information remains secure.

Security testing for critical systems involves assessing how the software behaves in the presence of malicious actors, incorrect usage, or unexpected inputs, and ensuring that the system meets required security standards and compliance regulations.

Key Objectives of Security Testing for Critical Systems:

  1. Identify Vulnerabilities: Detect flaws or weaknesses that could potentially be exploited by attackers. These vulnerabilities may exist in the software, system architecture, or its integration with other systems.
  2. Ensure Data Protection: Critical systems often handle sensitive information. Security testing ensures that data privacy measures are in place and that information is encrypted, masked, or securely stored.
  3. Verify Authentication and Authorization: Strong mechanisms for user authentication and authorization are vital for preventing unauthorized access to critical systems. Security testing ensures that only authorized users can access sensitive parts of the system.
  4. Detect and Mitigate Threats: Identify potential threats, including common attack methods such as SQL injection, cross-site scripting (XSS), and denial-of-service (DoS) attacks. The goal is to ensure that the system is resilient to such threats.
  5. Compliance with Regulations: Many critical systems are subject to industry-specific regulations, such as HIPAA (for healthcare), GDPR (for data privacy), or PCI-DSS (for payment systems). Security testing ensures that the system complies with these standards.

Types of Security Testing for Critical Systems:

  1. Vulnerability Scanning: Automated tools are used to scan the system for known vulnerabilities. These tools compare the system’s components against a database of known security flaws and provide insights into any potential weaknesses.
  2. Penetration Testing (Pen Test): Penetration testing involves simulating real-world cyber-attacks to identify exploitable vulnerabilities. Ethical hackers (or penetration testers) attempt to gain unauthorized access to the system by exploiting weaknesses in its design, implementation, or configuration.
  3. Static Application Security Testing (SAST): SAST involves reviewing the source code of the application without executing it. It identifies vulnerabilities at the code level, such as insecure coding practices, poor input validation, or missing security controls.
  4. Dynamic Application Security Testing (DAST): DAST is performed while the application is running. It focuses on identifying vulnerabilities that occur during the operation of the application, such as improper handling of user inputs or weak session management.
  5. Threat Modeling: Threat modeling helps identify potential security risks early in the software design phase. This involves analyzing how an attacker might exploit weaknesses and how various parts of the system might be targeted.
  6. Security Code Review: A manual or automated review of the application’s code to detect any weaknesses or flaws related to security. This often includes checking for issues such as poor input validation, hardcoded passwords, or insufficient data encryption.
  7. Risk Assessment: Risk assessments identify potential security threats based on system architecture, external threats, and business impact. This includes determining the likelihood of attacks and the impact of those attacks on the organization’s operations.

Best Practices for Security Testing in Critical Systems:

  1. Shift Left Security: Security testing should start early in the development lifecycle, not just during the testing phase. Integrating security into the DevOps process (DevSecOps) ensures that security is embedded throughout the design, development, and deployment stages.
  2. Continuous Security Testing: Security testing shouldn’t be a one-time event but an ongoing process. With the rapid pace of new threats and vulnerabilities emerging daily, continuous testing and monitoring of the system’s security posture is critical.
  3. Use of Automation Tools: While manual penetration testing and code reviews are essential, automated tools can significantly enhance the speed and thoroughness of security testing. Tools like OWASP ZAP, Nessus, and Burp Suite can automate common security tests.
  4. Security Awareness and Training: Developers, testers, and other stakeholders involved in critical systems should be trained to understand common security risks and how to avoid them. This includes recognizing common attack vectors and following best security practices during development.
  5. Patch Management: Vulnerabilities in critical systems often arise from outdated software or libraries. Regular patch management and updates ensure that known vulnerabilities are addressed and patched promptly.
  6. Simulation of Real-World Attacks: Use red teams (simulated adversarial attackers) to conduct security exercises that mimic real-world attacks. These exercises help assess the effectiveness of security controls, the response to incidents, and the ability to mitigate breaches.
  7. Zero Trust Architecture: In a zero-trust model, no user or system is trusted by default, even if they are inside the corporate network. Implementing zero trust in critical systems ensures that every access request is verified and validated, reducing the risk of internal or external breaches.
  8. Logging and Monitoring: Critical systems must have comprehensive logging and monitoring mechanisms in place to detect suspicious activities in real time. Security testing should verify the effectiveness of these mechanisms in identifying and responding to threats quickly.
  9. Incident Response and Recovery Planning: Security testing for critical systems should also assess the system’s ability to respond to security incidents. This includes verifying incident response procedures and the robustness of disaster recovery and business continuity plans.

Challenges in Security Testing for Critical Systems:

  1. Complexity: Critical systems are often large, complex, and interconnected with other systems, making it challenging to conduct exhaustive security testing.
  2. Evolving Threats: The landscape of cybersecurity threats is constantly changing, and new attack methods are developed regularly. This requires continuous learning, adaptation, and testing.
  3. Resource Constraints: Comprehensive security testing can be resource-intensive. Many organizations may face budget or time constraints when trying to implement thorough security testing for critical systems.
  4. False Positives and Negatives: Security testing tools can sometimes produce false positives (indicating vulnerabilities where none exist) or false negatives (failing to detect actual vulnerabilities), requiring human intervention and expertise to interpret results correctly.

Conclusion:

Security testing for critical systems is a vital part of software testing. It ensures that software is resilient to cyber threats, protecting both sensitive data and the integrity of the system. Given the potential consequences of security failures, organizations must adopt a comprehensive and proactive approach to security testing, integrating it early into the development lifecycle, using the latest tools and techniques, and ensuring continuous monitoring. By doing so, they can minimize the risk of cyber-attacks, maintain the trust of their users, and meet regulatory compliance requirements, all while safeguarding the functionality and security of critical systems.

Automation Testing with VS C#

Unlock the Power of Automation Testing with Visual Studio!

📅 Date: November 1, 2024
🕒 Time: 3 PM – 4 PM
📍 Hosted by IT Magnet

Are you ready to elevate your automation testing skills? Join me, Rony Barua, an experienced SQA Lead, as I host an exclusive webinar on Automation Testing with Visual Studio. This session is designed to guide both newcomers and seasoned professionals through the transformative potential of Visual Studio for automation testing. Whether you’re looking to refine your skills or gain insights into the latest techniques, this webinar is the perfect opportunity!

What You’ll Learn:

  • Setting Up Visual Studio for Automation: Learn how to configure and optimize Visual Studio for seamless automation testing.
  • Core Automation Techniques: Discover effective practices to streamline your testing processes.
  • Integration with Selenium and Other Tools: Explore integrations with popular tools to enhance your testing capabilities.
  • Best Practices and Real-World Tips: Get insights from my years of experience in the field and learn practical tips to avoid common pitfalls.

Why Join?

Automation testing is essential in today’s fast-paced development environment. By mastering Visual Studio as a testing tool, you’re not only improving your skills but also contributing to the efficiency and reliability of your projects.

API Testing with C# and RestSharp

API testing is an essential part of the software development lifecycle, focusing on the communication and data exchange between different software systems. It verifies that APIs are functioning correctly and meeting performance, reliability, and security standards. Using C# with the RestSharp library simplifies the process of interacting with RESTful APIs by providing an easy-to-use interface for making HTTP requests.

AI-driven Test Case Generation

Introduction
In today’s fast-paced software development environment, manual test case generation struggles to keep up with the ever-increasing complexity of systems, especially in Agile and DevOps-driven projects. AI-driven test case generation has emerged as a powerful solution to streamline and automate this process, leveraging artificial intelligence and machine learning (ML) to improve test accuracy, efficiency, and coverage.

This lecture will explore AI-driven test case generation, how it works, its advantages and challenges, and its application in modern testing environments.

What is AI-Driven Test Case Generation?

AI-driven test case generation automates the creation and optimization of test cases using AI techniques such as machine learning (ML) and natural language processing (NLP). By analyzing historical data, code structure, requirements, and user behavior, AI tools can produce test cases that cover critical functionalities, saving time and effort for testing teams.

Instead of manually writing test cases based on predefined requirements, AI-driven approaches can dynamically generate tests that adapt to the code, highlighting the most important areas to test, and identifying risks that human testers might overlook.

How Does AI-Driven Test Case Generation Work?

  1. Data Analysis
    AI-based tools use data from multiple sources, such as:
    • Historical test data: Past test cases, bug reports, and test execution logs.
    • User interactions: Analyzing how users interact with the system to detect potential problem areas.
    • Source code: Static code analysis to detect patterns and complexities.
    This data helps train the AI models to generate relevant test cases by learning patterns of common defects, usage scenarios, and code areas that need focus.
  2. Natural Language Processing (NLP)
    NLP plays a significant role in understanding natural language specifications, like user stories or business requirements. By analyzing these documents, AI can automatically convert requirements into test cases that align with the intended behavior of the software.
  3. Model-Based Testing
    AI tools can also create models that represent the system’s behavior or user flow. Based on these models, they can generate comprehensive test cases covering all possible scenarios, edge cases, and user paths.
  4. Risk-Based Test Case Generation
    AI can prioritize test cases based on risk analysis, such as:
    • Code complexity.
    • Areas prone to defects.
    • Recently modified code.
    • Critical functionalities or components.
    This approach ensures that high-risk areas are tested more thoroughly, improving the likelihood of catching defects early.
  5. Self-Updating Test Cases
    One of the biggest advantages of AI-driven tools is the ability to maintain and update test cases automatically. As the software evolves, the AI tools can detect changes in the code and automatically adapt test cases, making it easier to keep up with rapid development cycles.

Advantages of AI-Driven Test Case Generation

  1. Speed and Efficiency
    AI tools can generate test cases much faster than manual efforts, making the process more efficient. This speed is particularly valuable in Agile and DevOps environments where rapid iteration is common.
  2. Better Coverage
    AI ensures broader and more comprehensive test coverage by analyzing patterns that humans might miss. This leads to more thorough testing, particularly in complex systems with multiple variables.
  3. Cost-Effectiveness
    Automated test generation reduces the need for extensive human intervention, significantly lowering costs associated with manual test writing and maintenance.
  4. Scalability
    AI can easily scale to accommodate large and complex projects, generating thousands of test cases quickly without needing additional resources.
  5. Adaptability
    As code changes, AI-driven tools can adapt the test cases accordingly, maintaining relevance even in dynamic development environments. This is particularly beneficial in continuous integration and continuous delivery (CI/CD) pipelines.

Challenges of AI-Driven Test Case Generation

  1. Data Dependency
    AI tools require large volumes of high-quality data to be effective. Poor or insufficient data may result in suboptimal test cases.
  2. Complex Setup
    The initial setup of AI-driven systems can be complex, requiring knowledge of AI/ML algorithms, testing frameworks, and training data. It may take time and effort before the system becomes fully functional.
  3. Tool Expertise
    Not all testing teams are familiar with AI-based tools, and additional training may be required to effectively implement and maintain these systems.
  4. Trust in AI
    Some teams may be reluctant to trust AI-generated test cases over manual ones. Ensuring that AI-driven tests align with business requirements and actual software behavior can require oversight.

Use Cases

  • Regression Testing: AI tools can quickly generate test cases for regression testing, ensuring that recent changes haven’t introduced new bugs.
  • User Experience Testing: By analyzing user behavior data, AI can create test cases to mimic real-world user scenarios, improving UX testing.
  • Security Testing: AI can identify potential vulnerabilities in the code and generate relevant test cases, helping teams catch security issues early.

Conclusion

AI-driven test case generation is transforming how software testing is performed. By leveraging AI’s ability to analyze data, adapt to changes, and optimize testing efforts, teams can increase test efficiency, improve coverage, and reduce the time and cost of testing. However, while AI offers many advantages, it requires proper setup, high-quality data, and a clear strategy to maximize its benefits.

Incorporating AI in test generation is becoming essential in today’s fast-evolving software landscape, especially in Agile and DevOps workflows.

Embracing Quality: A Deep Dive into Software Testing and Quality Assurance at Uttara University

As technology continues to evolve at a rapid pace, the demand for quality software has never been greater. In response to this need, I’m excited to announce that I will be leading a series of lectures on Quality Assurance (QA) and Software Testing at Uttara University under the EDGE project.

Why Quality Assurance Matters

Quality Assurance is more than just finding bugs; it’s about ensuring that software meets the highest standards of quality and reliability. With the increasing complexity of software applications, effective QA practices are essential for delivering products that not only meet user expectations but also perform well under real-world conditions.

Course Overview

Throughout this course, we will explore key concepts and methodologies in QA and software testing, including:

  1. Introduction to Quality Assurance: Understanding the principles of QA, its importance in the software development lifecycle, and the role of QA professionals.
  2. Testing Methodologies: Delving into various testing types such as unit testing, integration testing, system testing, and acceptance testing. We will also discuss manual vs. automated testing and when to use each approach.
  3. Test Planning and Design: Learning how to create effective test plans, design test cases, and establish testing criteria that align with project requirements.
  4. Defect Tracking and Reporting: Best practices for identifying, documenting, and communicating defects to ensure timely resolution.
  5. Tools and Technologies: An overview of popular testing tools (like Selenium, JUnit, and Postman) and how they can enhance the testing process.
  6. Real-World Applications: Case studies and practical exercises to apply the concepts learned and prepare students for real-world QA challenges.

Learning Outcomes

By the end of this course, students will be equipped with the knowledge and skills to:

  • Understand the critical role of QA in software development.
  • Develop comprehensive test plans and cases.
  • Utilize various testing tools effectively.
  • Analyze and report on testing outcomes to drive improvements.

Join the Journey

I am passionate about sharing my knowledge and experiences in QA and software testing. This course will not only provide theoretical insights but also hands-on experience that prepares students for careers in this vital field.

I look forward to engaging discussions, collaborative projects, and fostering a deeper understanding of quality assurance among aspiring software professionals.

Stay tuned for updates, and let’s embark on this journey towards achieving excellence in software quality together!

Using Paste Special in Visual Studio to Generate C# Classes from JSON

Visual Studio offers a feature called “Paste Special” that allows you to easily generate C# classes from JSON objects. This is particularly useful when working with web APIs or any JSON data, as it automates the creation of data models that match the JSON structure.

  1. Copy the JSON Object:
    • Ensure you have your JSON object copied to the clipboard. For example
  1. Open Visual Studio:
    • Launch Visual Studio and open the project where you want to add the new classes.
  2. Add a New Class File:
    • In Solution Explorer, right-click on the folder where you want to add the new class.
    • Select Add > New Item….
    • Choose Class and give it a meaningful name, then click Add.
  3. Use Paste Special:
    • Open the newly created class file (e.g., MyClass.cs).
    • Delete any default code in the class file.
    • Go to Edit > Paste Special > Paste JSON as Classes.
  4. Review the Generated Code:
  5. Visual Studio will automatically generate C# classes that correspond to the JSON structure. For the example JSON, it would generate something like this:

How to input value into an international number text box in selenium

Below is the text box and the corresponding HTML:

If I used sendkeys, sometimes it may not working

driver.findElement(By.name(“mainphone”)).sendKeys(“(02)2222-2222”);
driver.findElement(By.id(“mobilephone”)).sendKeys(“05-5555-5555”);

If sendkeys() methods are not working then use following two ways to input text:

Before sendkeys() use click() method to click inside textfield i.e:

driver.findElement(By.name("mainphone")).click();
driver.findElement(By.name("mainphone")).sendKeys("(02)2222-2222");   
driver.findElement(By.id("mobilephone")).click();
driver.findElement(By.id("mobilephone")).sendKeys("05-5555-5555");

Open chrome mobile emulator with selenium c#

Hi guys, I am going to run a test mobile emulator with selenium and VS C#

Import

using System;
using System.Threading;
using NUnit.Framework;
using OpenQA.Selenium;
using OpenQA.Selenium.Support.UI;
using OpenQA.Selenium.Chrome;

Driver Utils Class

First of all delclaring the webdriver, which will be used for open specfic browser

namespace SeleniumAutomation
{
[TestClass]
public class Setup
  {
       IWebDriver webDriver;
  }
}

Open Chrome

[Test]
public void Open_Browser()
{
 webDriver = new ChromeDriver();

}

Open Chrome Mobile Emulator

 [Test]
 public void Mobile_Emulator_Browser()
 {
 ChromeOptions chromeCapabilities = new ChromeOptions();
 chromeCapabilities.EnableMobileEmulation("Pixel 5");
 webDriver = new ChromeDriver(chromeCapabilities);

 }

I think it will be helpful to run chrome in mobile emulator