Programming Practices For Software Engineers

Published 1/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.10 GB | Duration: 6h 46m

Master software engineering practices to improve your code quality and efficiency. Design for future without complexity!

What you'll learn
Interface design principles in depth
Software practices to write readable and production ready code
Programming practices applicable to every programming language
Principles to follow while tackling niche problems like performance and debugging
Importance of programming practices in building high performance code without making the code unreadable

Requirements
Basic knowledge about any programming language. You will learn the principles needed to shape your skills into potent practices.
A working knowledge about software development in general. Ability to appreciate iterative nature of design will come in handy.
Simple snippets of few lines used as examples and quick checks.
No particular programming language is targetted. If you have practiced with any programming language in past 6 months you can understand everything in the course!
If you have recently learned your first programming language, just be patient with the content. It will definitely add focus to whatever project you pick up next.

Description
Welcome to the "Programming Practices for Software Engineers" course on Udemy!In this course, you will learn the best programming practices that every software engineer should know. In addition, we will cover code organization, testing, debugging, performance, notation, and refactoring.Throughout the course, you will work on hands-on exercises to apply these concepts and improve your programming skills. We will also cover how to work in a team and collaborate with other software engineers.By the end of this course, you will have a solid understanding of the programming practices that will help you become a successful software engineer. In addition, you will be able to write clean, efficient, and well-organized code and have the skills to work effectively in a team environment.This course suits software engineers of all levels, from beginners to experienced professionals. No programming experience is required, but familiarity with a programming language would be helpful. So, if you want to improve your programming skills and become a better software engineer, this course is for you!Why are programming practices needed?Programming practices are essential in software engineering because they help ensure that the software is high quality, easy to maintain, and easy to modify. Some examples of programming practices that are important in software engineering include:Writing clean, well-documented code helps other developers understand and work with the code more easily.Using version control: This allows developers to track changes to the code over time and makes it easier to collaborate with other team members. Making readable code changes makes the version control a repository to understand the evolution of code.Adhering to coding standards: This helps to ensure that the code is consistent and easy to read, which makes it easier to maintain and modify.Automating testing: This helps catch bugs early and ensures that the code is high quality.Using consistent programming practices helps make the code more reusable and easier to understand while debugging and tuning.Overall, good programming practices can help to improve the efficiency and effectiveness of software development, which can lead to better software products.

Overview
Section 1: Introduction

Lecture 1 Objective

Lecture 2 Sincere Request before getting started

Section 2: Programming Style

Lecture 3 Programming Style : Section Introduction

Lecture 4 Why programming style matters?

Lecture 5 Naming : Desired Characteristics

Lecture 6 Naming Practices : Variable names - 1

Lecture 7 Naming Practices : Variable names - 2

Lecture 8 Naming Practices : Variable names - 3

Lecture 9 Naming Practices : Function Names

Lecture 10 Naming Practices : Importance of being accurate

Lecture 11 Expressions and Statements : Indentation

Lecture 12 Expressions and Statements : Natural Expression

Lecture 13 Expressions and Statements : Parantheses

Lecture 14 Expressions and Statements : Complexity

Lecture 15 Expressions and Statements : Side Effects

Lecture 16 Consistency and Idioms : Overview

Lecture 17 Consistency and Idioms : Loops

Lecture 18 Consistency and Idioms : else if

Lecture 0 Quick check

Lecture 19 Macros

Lecture 20 Magic Numbers

Lecture 21 Code Comments

Lecture 22 Section Summary

Section 3: Algorithms and Data Structures w.r.t Programming Practices

Lecture 23 Algorithms and Data Strcutures : Section Introduction

Lecture 24 Necessity to understand practices around data structures and algorithms

Lecture 25 Algorithms : Search

Lecture 26 Algorithms : Sorting

Lecture 27 Algorithms : Libraries

Lecture 28 Algorithms : O - Notation

Lecture 29 Data Strcutures : Dynamic Arrays

Lecture 30 Data Strcutures : Lists

Lecture 31 Data Strcutures : Trees

Lecture 32 Data Strcutures : Hash Tables

Lecture 33 Algorithms & Data Strcutures : Summary

Section 4: Interface Design : Programming practices and principles with example

Lecture 0 Sort quick check

Lecture 34 Interface Design : Section Introduction

Lecture 35 Design and Implementation in general

Lecture 36 Introduction to interface design programming practices

Lecture 37 Interface Example : Prototype design version

Lecture 38 Design considerations

Lecture 39 Interface Example : Library

Lecture 40 Interface Specifications

Lecture 41 Interface Design : General Principles

Lecture 42 Hiding implementation a.k.a abstraction

Lecture 43 Interface Design : General Principles extended

Lecture 44 Resource Management programming practices

Lecture 45 Error Handling programming practices

Lecture 46 User Interfaces

Section 5: Debugging: Navigating the development and production

Lecture 47 Debugging : Section Introduction

Lecture 48 Debugging practices overview

Lecture 49 Debuggers in general

Lecture 50 Debugging practices for easy bugs

Lecture 51 Debugging practices for hard bugs

Lecture 52 Debugging Challenges

Section 6: Testing : Programming practices beyond roles and designations

Lecture 53 Software Testing: Section Introduction

Lecture 54 Testing Overview

Lecture 55 Test as you code or Test Driven Development

Lecture 56 Test Automation

Lecture 57 Systematic testing practices

Lecture 58 Considerations while software testing in general

Lecture 59 Ownership of testing

Section 7: Performance: Measure what matters. Fix only what matters!

Lecture 60 Software Performance : Section Introduction

Lecture 61 Performance practices overview

Lecture 62 Basic steps to appraoching performance issues

Lecture 63 Guideline programming practices for dealing with performance improvement

Lecture 64 Timing and profiling for performance

Lecture 65 Performance improvement strategies

Lecture 66 Code tuning for better performance

Lecture 67 Estimation

Lecture 68 Optimal space utilization for better performance

Section 8: Portability: Practices to ensure code works everywhere

Lecture 69 Software Portability: Section Introduction

Lecture 70 Overview

Lecture 71 Role of language in portability

Lecture 72 Environmental factors to be considered in practices dealing with portability

Lecture 73 Role of system interface and practices to handle the portability concerns

Section 9: Notation: Being proactive is the only way!

Lecture 74 Notation: Section Introduction

Lecture 75 Overview

Lecture 76 Programming Language

Lecture 77 Data formatting practices

Lecture 78 Regular Expressions

Lecture 79 Programmable tools

Lecture 80 Tool chains: Compilers, Interpreters, Virtual Machines

Lecture 81 Code Generation

Lecture 82 Just in Time compilation

Section 10: Conclusion

Lecture 83 Closing remarks.

Lecture 84[Bonus Lecture]

Beginner and intermediate experience developers. No language bar all Python, Java, Scala, C++, Rust, GoLang, jаvascript, etc. developers will benefit from the practices and principles being shared in the course.,Software professional with 4-8 years of experience will benefit from the practices to take back to their teams,Students learning programming language can use the additional design perspective from the course for their upcoming project.,All developers curious about programming and software practices that make systems robust and scalable for decades,Programmers looking to upskill in their career by building expertise in software design and productive software engineering.


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