Discover an easy Introduction to the Software Development Life Cycle (SDLC) in this video! Aleksandr Gushchin, a Delivery Manager for big clients, breaks down the SDLC in software engineering with a simple, clear approach. Learn the fundamentals, explore SDLC models, and uncover best practices that drive engineering excellence.

In just 40 minutes, you'll get a simplified overview—from "What is Software Development Life Cycle" to "Software Engineering Best Practices You Should Follow" and "What AI tools should Developers use?". See how agile methods and AI help senior programmers write better code, deliver business value faster, and reduce costs. If you're looking for a straightforward guide to the software development lifecycle, this video is a must-watch!

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👉 Software Delivery Cost Optimizer: https://aw.club/global/en/courses/engx-code-review

👉 EngX Code Review: https://aw.club/global/en/teams/software-delivery-cost-optimizer

NAVIGATION

0:00 Intro

1:19 Fundamentals of SDLC

3:01 Enhancing Efficiency in SDLC

4:27 Reducing Costs and Avoiding Waste

5:09 Importance of Market Research in SDLC

6:33 Initial Phases of SDLC

7:50 Solution Design and Custom Development

8:52 Implementation and Testing of Solutions

10:10 Ensuring High-Quality Development Standards

11:02 Effective Communication and Documentation

12:13 Managing Known and Stable Project Scopes

13:25 Application of Agile in Predictable Environments

14:19 Factory Model in Software Development

15:09 Handling Dynamic Project Environments

16:15 Strategy and Management in Unfamiliar Situations

17:09 Experimentation and Proof of Concept in SDLC

18:23 Importance of Clear Requirements and Testing

19:17 Enhancing Developer Focus and Testing

20:09 Quality Gates and Development Output

21:10 Addressing and Managing Technical Debt

22:10 Improving Performance with Quality Initiatives

23:32 Role of Unit Testing in Quality Assurance

24:24 Continuous Quality and Assurance Practices

25:24 Shift-Left Approach in Testing

26:05 Analyzing and Optimizing Delivery Pipelines

27:26 Role of AI in Streamlining SDLC Processes

28:52 Choosing the Right Management Methodology

30:10 Efficiency of Regression Testing and Automation

31:38 Agile and Continuous Delivery in Complex Projects

33:18 Advantages of Kanban and Continuous Delivery

34:26 Evaluating and Improving SDLC Processes

35:44 Reworking Tasks for Testability and Independence

37:14 Code Documentation and Traceability

38:20 Developer's Role in Business Value Delivery

39:27 Reducing Maintenance Costs through Quality Assurance

40:29 Utilizing AI for Routine Task Automation

41:37 Enhancing SDLC with Quality Gates

42:33 Implementing Advanced Security and Analysis Tools

43:48 AI Assistance in Development and Testing

45:23 Leveraging AI for Testing and Quality Improvement

47:26 Encouraging Continuous Learning and Engagement

47:26 Final words

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