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  • The fundamentals of JUnit 5 and how it differs from earlier versions.
  • Writing unit tests using JUnit 5 annotations and assertions.
  • Understanding Mockito and its role in mocking dependencies.
  • Implementing Test-Driven Development (TDD) to enhance code reliability.
  • Testing Spring Boot applications with JUnit 5 and Mockito.
  • Handling exceptions, mocking methods, and verifying interactions with Mockito.
  • Writing database-related tests using JPA and ensuring data consistency.
  • Creating integration tests to validate end-to-end functionality.
  • Debugging test failures and improving application quality.
  • Best practices for test automation and writing maintainable test cases.

This comprehensive course is designed to help developers, testers, and software engineers master the art of unit testing and mocking with JUnit 5 and Mockito. Through hands-on examples, detailed explanations, and best practices, you'll gain a deep understanding of unit testing, test-driven development (TDD), annotations, assertions, mocking techniques, and exception handling. Whether new to testing or looking to refine your skills, this course provides everything you need to build robust and reliable applications.

  • Basic understanding of Java programming and object-oriented concepts.
  • Familiarity with IDEs like IntelliJ IDEA, Eclipse, or Java IDE.
  • A basic understanding of database operations (JPA or JDBC) is helpful but not mandatory.
  • Eagerness to learn practical unit testing and mocking techniques.
  • Java developers and software engineers looking to improve their testing skills.
  • QA engineers and testers are eager to understand and implement unit testing in Java.
  • Students and beginners interested in learning the basics of JUnit 5 and Mockito.
  • Professionals aiming to implement Test-Driven Development (TDD) practices in real-world projects.
  • Developers working on Spring Boot applications who want to build more reliable and maintainable code.
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  • Section 1 : Module 1 13 Lectures 00:38:19

    • Lecture 1 :
    • introduction Practical Junit Mockito Preview
    • Lecture 2 :
    • What is Unit Testing and Test Driven Development
    • Lecture 3 :
    • What is Junit
    • Lecture 4 :
    • What are Annotations in Java
    • Lecture 5 :
    • BeforeEach Annotation
    • Lecture 6 :
    • AfterEach Annotation
    • Lecture 7 :
    • BeforeAll and AfterAll Annotation
    • Lecture 8 :
    • Test Annotation
    • Lecture 9 :
    • Disabled Annotation
    • Lecture 10 :
    • DisplayName Annotation
    • Lecture 11 :
    • Parameterized Test and ValueSource Annotation
    • Lecture 12 :
    • Repeated Test Annotation
    • Lecture 13 :
    • Tag Annotation
  • Section 2 : Module 2 3 Lectures 00:11:35

    • Lecture 1 :
    • Life cycle of a Junit Test
    • Lecture 2 :
    • What is meant by Assertion
    • Lecture 3 :
    • Different Assertion methods
  • Section 3 : Module 3 7 Lectures 00:45:42

    • Lecture 1 :
    • Package structure and Dependency
    • Lecture 2 :
    • Writing Our First Junit and Mockito Test
    • Lecture 3 :
    • Applying BeforeEach and AfterEach to our Test scenarios
    • Lecture 4 :
    • Applying BeforeAll and AfterAll to the test scenarios
    • Lecture 5 :
    • Code Coverage By Writing Test for Different Scenarios
    • Lecture 6 :
    • Static Import of Assert Function
    • Lecture 7 :
    • Writing Test for Complex Object with multiple Assertions
  • Section 4 : Module 4 4 Lectures 00:34:39

    • Lecture 1 :
    • Usage of Mock Annotation to avoid dependencies getting null value
    • Lecture 2 :
    • Using When Then to bypass the dependency in our testing logic
    • Lecture 3 :
    • Test case for Get All Properties method in controller
    • Lecture 4 :
    • Test case for update price method in controller
  • Section 5 : Module 5 6 Lectures 00:44:10

    • Lecture 1 :
    • Test case for Converter DTO to Entity
    • Lecture 2 :
    • Test case for Converter Entity to DTO
    • Lecture 3 :
    • Testing Saved Property of Service Layer
    • Lecture 4 :
    • Test case for Get All Properties in Service
    • Lecture 5 :
    • Test case for Update All Properties in Service
    • Lecture 6 :
    • Test case for Update Descriptionfor Property in Service
  • Section 6 : Module 6: 3 Lectures 00:15:13

    • Lecture 1 :
    • Testing Exception Scenario -Part-1
    • Lecture 2 :
    • Testing Exception Scenario - Part-2
    • Lecture 3 :
    • Testing the Model or DTO classes
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Hello, I'm Akhil, a Senior Data Scientist at PwC specializing in the Advisory Consulting practice with a focus on Data and Analytics.
 
My career journey has provided me with the opportunity to delve into various aspects of data analysis and modelling, particularly within the BFSI sector, where I've managed the full lifecycle of development and execution.
 
I possess a diverse skill set that includes data wrangling, feature engineering, algorithm development, and model implementation. My expertise lies in leveraging advanced data mining techniques, such as statistical analysis, hypothesis testing, regression analysis, and both unsupervised and supervised machine learning, to uncover valuable insights and drive data-informed decisions. I'm especially passionate about risk identification through decision models, and I've honed my skills in machine learning algorithms, data/text mining, and data visualization to tackle these challenges effectively.
 
Currently, I am deeply involved in an exciting Amazon cloud project, focusing on the end-to-end development of ETL processes. I write ETL code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, and execute scripts via EMR services. The processed data is then loaded into Postgres SQL (RDS/Redshift) in full, incremental, and live modes. To streamline operations, I’ve automated this process by setting up jobs in Step Functions, which trigger EMR instances in a specified sequence and provide execution status notifications. These Step Functions are scheduled through EventBridge rules.
 
Moreover, I've extensively utilized AWS Glue to replicate source data from on-premises systems to raw-layer S3 buckets using AWS DMS services. One of my key strengths is understanding the intricacies of data and applying precise transformations to convert data from multiple tables into key-value pairs. I’ve also optimized stored procedures in Postgres SQL to efficiently perform second-level transformations, joining multiple tables and loading the data into final tables.
 
I am passionate about harnessing the power of data to generate actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, I would love to connect. Let’s explore the endless possibilities that data analytics can offer!
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