Software engineering: JavaScript

Code in:JavaC#PythonJavaScript

The course is the same for all four languages, and the code here is in JavaScript. Every module says which lessons of the language you need before it.

Module 0

Welcome

1 lesson · what the course teaches and what you need to know

1. 1Welcome

Module 1

Design patterns

14 lessons · Strategy, Observer, Builder, State…

1. 1Why patterns
2. 2Strategy
3. 3Observer
4. 4Factory Method and Simple Factory
5. 5Builder
6. 6Singleton and Dependency Injection
7. 7Adapter and Facade
8. 8Decorator
9. 9Composite
10. 10Command
11. 11State
12. 12Template Method and Iterator
13. 13Repository
14. 14The shop: which pattern where

Module 2

Clean code and refactoring

8 lessons · names, functions, smells, small steps

1. 1Names in code
2. 2Functions: one job, few parameters, no hidden side effects
3. 3Comments that lie and comments that help
4. 4Code smells: long method, large class, duplication, primitives instead of types, long if chains
5. 5Tests as a safety net
6. 6Refactoring in small steps
7. 7SOLID without dogma
8. 8Exercise: a messy class, cleaned up step by step

Algorithms and complexity

Module 3

Complexity

5 lessons · Big-O, time and memory, measuring

1. 1Time complexity: counting steps
2. 2Big-O: how the work grows
3. 3Best, average and worst case
4. 4Space complexity
5. 5Amortized complexity

Module 4

Searching

3 lessons · linear and binary search

1. 1Linear search
2. 2Binary search
3. 3Binary search on the answer

Module 5

Sorting

6 lessons · insertion, merge, quick, heap, counting

1. 1Insertion sort and selection sort
2. 2Merge sort and "divide and conquer"
3. 3Quick sort and the bad pivot
4. 4Heap and heap sort
5. 5Counting sort and radix sort
6. 6Stable sorting and the built-in sort

Module 6

Recursion

4 lessons · the call stack, divide and conquer

1. 1The call stack from the inside
2. 2From recursion to a loop
3. 3Fast exponentiation
4. 4Divide and conquer and the recursion tree

Module 7

Data structures

8 lessons · array, list, hash table, trees, heap

1. 1The dynamic array from the inside
2. 2Linked list
3. 3Stack and queue
4. 4Hash table
5. 5Binary search tree
6. 6Priority queue
7. 7Trie
8. 8Union-find

Module 8

Graphs

6 lessons · BFS, DFS, Dijkstra, dependencies

1. 1Graph: adjacency list and matrix
2. 2BFS: the fewest stops
3. 3DFS: islands and cycles
4. 4Topological sorting
5. 5Dijkstra
6. 6Minimum spanning tree

Module 9

Dynamic programming

5 lessons · memoisation, tables, knapsack

1. 1Overlapping subproblems
2. 2The coin change problem
3. 3The knapsack problem
4. 4The longest common subsequence and diff
5. 5How to recognise a DP task

Module 10

Greedy algorithms

2 lessons · when they work and when they fail

1. 1Greedy algorithms and when they work
2. 2When a greedy algorithm fails

Module 11

Problem-solving techniques

4 lessons · two pointers, sliding window, prefix sums

1. 1Two pointers
2. 2Sliding window
3. 3Prefix sums
4. 4A hash table as a counter

Module 12

Project: city navigation

1 lesson · the map as a graph, BFS, Dijkstra

1. 1City navigation

Module 13

Concurrency and race conditions

9 lessons · locks, deadlock, async

1. 1Why threads
2. 2Race condition
3. 3Locking
4. 4Atomic operations and immutable objects
5. 5Deadlock
6. 6Producer and consumer
7. 7A pool of threads and tasks
8. 8async is not a thread
9. 9Testing concurrent code

Module 14

Security for developers

9 lessons · untrusted input, passwords, sessions, tokens, secrets

1. 1Untrusted input
2. 2Injections: when data becomes a command
3. 3XSS: someone else’s script in your page
4. 4Passwords
5. 5Sessions, cookies and CSRF
6. 6JWT and its traps
7. 7Secrets in code and in git
8. 8Dependencies: other people’s code that yours runs
9. 9Cryptography you don't write yourself

Module 15

Software architecture

9 lessons · layers, modules, events, APIs, caching, scaling

1. 1Layers
2. 2Hexagonal and clean architecture
3. 3Monolith, modular monolith, services
4. 4Events and queues
5. 5Transactional outbox
6. 6API design: contract, versions, retried requests
7. 7Caching
8. 8Scaling
9. 9ADR: architecture decision records

Module 16

The architect at work

9 lessons · NFRs, trade-offs, integration, migrations, review

1. 1Non-functional requirements you can measure
2. 2Trade-offs
3. 3When the neighbour is slow: timeout, retry, circuit breaker
4. 4A transaction across services (saga)
5. 5Integrating old and foreign systems
6. 6Changing a live system (strangler fig, expand–contract)
7. 7Architecture review
8. 8The enterprise landscape and capabilities
9. 9Your first architecture task

Practice

Tasks

Every task from the lessons in one place, by module.