Learning
  • Software Engineering Golden Treasury
  • Trail Map
  • Caching
    • Alternatives to use before using cache
    • Caching Architecture
    • Cache Invalidation and Eviction
    • Cache Patterns
    • Cache
    • Consistency
    • Distributed Caching
    • Issues with caching
    • Types of caches
  • Career
    • algo types
    • Backend Knowledge
    • Burnout
    • consultancy
    • dev-level
    • Enterprise Developer
    • how-to-get-in-tech-from-other-job
    • how-to-get-into-junior-dev-position
    • induction
    • Interview
    • junior
    • mid
    • New Job
    • paths
    • Principle/staff Engineer
    • Requirements for job
    • Senior Dev capabilities
    • learning
      • automating-beginner
      • company1
        • analyst-progression
        • core-eng-progression
        • dev-progression
        • perf-eng-progression
        • soft-deliv-progression
    • mentoring
      • mentor-resources
    • recruitment
      • questions
      • Spotting posers
  • Computer Science
    • boolean-algebra
    • Compiler
    • Finite State Machine
    • Hashing
    • Algorithms
      • Breadth Firth Search
      • complexity
      • Depth First Search
      • efficiency
      • Sliding Window
      • sorting
    • data-structures
      • AVL Trees
      • data-structures
      • Linked List
    • machines
      • Intel Machine
      • Turing Machine
      • von neumann machine
      • Zeus Machine
  • devops
    • The 5 Ideals
    • microservice
    • Artifact repository
    • Bugs and Fixes
    • Build police
    • cloud-servers
    • Deployments
    • Environments
    • GitOps
    • handling-releases
    • infrastructure-as-code
    • System Migrations
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    • On Premises Hosting
    • Properties/configuration
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    • Release
    • Roll Outs
    • serverless
    • Serverless
    • Cloud Services
    • Versioning
    • AWS
      • deploy-docker-esc
      • cloud-practitiioner-essentials-notes
        • Module 1 - Intro to AWS
        • Module 2 Compute in the cloud
        • Module 3 Global Infrastructure and Reliability
        • Module 4 Networking
        • Module 5 Storage and Databases
        • Security
        • 7 Monitoring and Aanlytics
        • 8 Pricing and Support
        • 9 Migration and Innovation
      • developer-associate
        • AWS Elastic Beanstalk
    • build-tools
      • Managing dependecies
      • Apache ANT
      • Gradle
        • Custom Plugins
        • local-jars
      • Project Management - maven
        • Archtypes
        • Build Lifecycles
        • Customising build lifecycle
        • Dependencies
        • Directory layout
        • jar-files
        • one-to-one
        • Modules
        • Phases
        • Maven Plugins
        • POM
        • profiles
        • setup
        • Starting a maven project
        • wrapper
    • CI/CD
      • Continuous Delivery
      • zookeeper
      • Continuous Integration (CI)
      • github-actions
      • Pipeline
      • Teamcity
    • Cloud computing
      • Overview
      • Service Models
      • Cloud Services
    • containers
      • Best Practices
      • Docker
    • Infrastructure
      • IT Infrastructure Model
      • Non functional Attributes (Quality Attributes)
        • Infrastructure Availability
        • Performance
        • Secruity
    • monitoring
      • Alerting
      • Monitoring & Metrics
      • Metrics
      • Ready pages
      • Splunk
      • Status pages
      • notes-devops-talk
      • logging
        • logging
        • issues
        • Logging
        • Logging
    • Service mesh
      • Service Discovery
      • Istio
    • Terraform
    • container-management
      • Kubernetes
        • commands-glossary
        • OLTP
        • config-maps
        • Links
        • ingress
        • SDP
        • minikube
        • filter
        • indexes
        • sidecar
        • continuous-deployment
  • General Paradigms
    • CAP theorem
    • designing data-intensive applications summary
    • a-philosophy-of-software-design-notes
    • Aspect oriented Programming (AOP)
    • Best Practice
    • Cargo Cult
    • Clean Code
    • Coding reflections
    • Cognitive Complexity
    • Complexity
    • Conventions
    • Design discussions
    • Design
    • Error Handling Checklist
    • Exceptions
    • Feature Flags/toggle
    • Functional requirements
    • Last Responsible Moment
    • Lock In
    • Named Arguments
    • Naming
    • Performance Fallacy
    • Quality
    • Redesign of a system
    • Resuse vs Decoupling
    • Rules for software designs
    • Sad Paths
    • Scaling Webservices
    • Scientific Method
    • stream-processing
    • Upstream and Downstream
    • Patterns
      • Client-SDK-Pattern
      • ORM
      • Api gateway
      • Business Rules Engine
      • cache
      • Composition Root
      • Dependency Injection Containers
      • Dependency Injections
      • Double Dispatch
      • Exception Handling
      • Gateway pattern
      • Humble Object
      • Inheritance for reuse
      • Null Object Pattern
      • Object Mother
      • Patterns
      • Collection pipeline pattern
      • Service Locator
      • Setter constructor
      • Static factory method
      • Step Builder Pattern
      • telescopic constructors
      • Toggles
      • API
        • Aims of API designs
        • Avoid Checked Exceptions
        • Avoid returning nulls
        • Be defensive with your data
        • convience-methods
        • Fluent Interfaces
        • Loan Pattern
        • prefer-enums-to-boolean-returns
        • return-meaningful-types
        • Small intefaces
        • Support Lambdas
        • Weakest type
      • Gang of Four
        • Builder
        • Factory Pattern
        • Strategy Pattern
        • Template
        • abstract Factory
        • Adapter
        • Bridge Pattern
        • Chain of responsibility
        • Command Pattern
        • Composite Design Pattern
        • Decorator Pattern
        • Facade Pattern
        • Flyweight pattern
        • Guard Clause
        • Interpreter
        • html
        • Mediator Pattern
        • Memento Pattern
        • Observer
        • Prototype
        • Proxy
        • Singleton
        • State Pattern
        • Visitor Pattern
    • Architecture
      • Entity Component System
      • Integration Operation Segregation Principle
      • Adaptable Architecture
      • Architecture
      • C4 Modelling
      • cell-based
      • Clean/Hexagonal Architecture
      • Codifying architecture
      • Correct By configuration
      • Cost Base Architecture
      • Data Oriented Design
      • deliberate
      • Domain oriented DOMA
      • Event Driven Architecture
      • Evolutionary Architecture
      • examples
      • Feature Architecture
      • Framework and Libraries
      • functional-core-imperative-shell
      • Layered Architecture
      • Micro services
      • monoliths-to-services
      • Multi tiered Architecture
      • Multi tenant application
      • Resilient Architecture
      • stage event driven architecture (SEDA)
      • links spring rest app
      • Tomato Architecture
      • Tooling
      • Types of architecture
      • checklist
        • Checklist for new project
        • Back end Architecture Checklist
        • Front end Architecture Checklist
        • Mobile Architecture Checklist
      • Cloud Patterns
        • Command and Query Responsibility Segregation (CQRS)
        • Event Sourcing & CQRS
        • Asynchronous Request and Reply
        • Circuit Breaker
        • Retry
        • Sidecar
        • Strangler pattern
      • Domain driven design
        • value & entity
      • Microservices
        • Alternatives to choosing microservices first when scaling
        • Consistency in distributed systems
        • 12 Factor applications
      • Modularity
        • Module monolith vs Microservices
        • Spring Moduilth
      • Architecture Patterns
        • Hexagonal architecture
        • Inverting dependencies
        • Layering & Dependency Inversion Principle
        • Mappings
        • Vertical Slice architecture
        • Web Client Server
        • domain
          • Business and Data Layers Separation
          • DTO
          • Domain Model Pattern
          • Domain Object
          • Transaction Script/ Use Case pattern
        • Enterprise Patterns
          • Concurrency
          • Distribution strategies
          • Domain layer patterns
          • Layering/organisation of code
          • Mapping to datasource
          • Session State
        • Usecases
          • Use case return types
      • Serverless
        • Knative
    • Design architecture aims
      • back of envelope
      • Design ideas
      • Design mistakes
      • high-volume-design
      • ISO Quality Attributes
      • Non functional requirements
      • “Designing for Performance” by Martin Thompson
      • High Performance
      • Qaulity Attributes
        • Availability
        • System Availability
        • Fault Tolerance
        • interoperability
        • Latency
        • Maintability
        • Modifiability
        • Performance
        • Readability
        • Reliability
        • Scalability vs performance
        • Scalability
        • Scaling
        • statelessness
        • Testability
        • Throughput
      • System Design
      • web-scalability-distributed-arch
        • scalable-and-distributed-web-architecture
    • README
      • Conflict-free Replicated Data Type
      • Fallacies
      • Load balancing
      • Rate Limiting
      • Transactions
    • Patterns of Enterprise Application Architecture
      • Repository Pattern
      • Rules Engines
      • scatter-gather
      • Specification Design Pattern
      • Table Driven Development
      • Workflow Design Patterns
        • Triggers
    • Principles
      • Do It Or Get Bitten In The End
      • Dont Repeat Yourself
      • Habitability
      • Keep it simple
      • Responsibility Driven Design
      • Ya Ain’t Gonna Need It
      • Conceptual Overhead
      • CUPID
      • Reuse existing interfaces
      • Facts and Fallacies
      • locality of behaviour
      • Separation of Concerns
      • Simplicity
      • SLAP principle
      • Step down rule
      • Unix Philosophy
      • Wrong abstractions
      • SOLID
        • 1. Single Responsibility Principle
        • 2. Open Close Principle
        • 3. Liskov Substitution Principle
        • 4. Interface Segregation Principle
        • 5. Dependency Inversion Principle
        • GRASP (General Responsibility Assignment Software Principles)
        • Solid for packages
          • jobs
          • CCP
          • CRP
          • REP
          • egress
          • gossip-protocol
        • STUPID
    • programming-types
      • Coding to Contract/Interface
      • Links
      • Declarative vs Imperative Programming Languages
      • defensive-programming
      • Design by contract
      • Domain Specific Languages (DSL)
      • Event Driven
      • file-transfers
      • Logical Programming
      • Mutability
      • Self Healing
      • Simplicity
      • Type Driven Design
      • Value objects
      • Aspect Oriented Programming
      • Concurrent and Parallel Programming
        • Actor Model
        • Asynchronous and Synchronous Programming
        • Batch processing
        • Concurrency Models
        • SAP
        • Multithreading
        • Non Blocking IO
        • Optimistic vs Pessimistic Concurrency
        • Thread per connection or request model
        • Actor
        • aysnchronous-tasks
          • Computational Graphs
          • Divide and conquer
          • Future
          • Thread Pool
        • barriers
          • Barriers
          • Race conditions
        • design
          • agglomeration
          • Communication
          • Mapping
          • Partitioning
        • Liveness
          • Abandoned Lock
          • Deadlocks
          • Livelock
          • Starvation
        • locks
          • Read write lock
          • Reentrant lock
          • Try Lock
        • Mutual Exclusion
          • Data Races
          • Mutual Exclusion AKA Locks
        • performance
          • Amdahl's Law
          • Latency, throughput & speed
          • Measure Speed up
        • synchronization
          • Condition variable
          • producer consumer pattern
          • Semaphore
        • Threads and processes
          • Concurrent and parallel programming
          • Daemon Thread
          • Execution Scheduling
          • sequential-parallel
          • Thread Lifecycle
          • threads-and-processes
      • Functional Programming
        • Currying
        • design-patterns-to-func
        • imperative-programming
        • First class functions
        • Functional Looping
        • Higher Order Functions
        • Immutability
        • Issues with functional Programming
        • Lambda calculus
        • Lazy & Eager
        • map
        • Monad
        • Railway Programming
        • Recursion
        • Reduce
        • referential-transparacy
        • Referential transparency
        • Supplier
      • oop-design
        • Issues with object oriented code
        • Aggregation
        • Anti Patterns
        • Association
        • class-and-objects
        • Composition
        • general-laws-of-programming
        • general-notes
        • Getters and Setters
        • Inside out programming
        • Inversion of control
        • oop-design
        • Other principles
        • Outside in programming
        • Readability
        • Why OO is bad
        • README
          • abstraction
          • encapsulation
          • inheritance
          • Polymorphism
        • clean-code
          • Code Smells
          • Comments
          • Naming
          • CLEAN design
            • code is assertive
            • Cohesion
            • Connascence
            • Coupling
            • Encapsulation
            • Loose Coupling
            • Nonredundant code
      • Reactive Programming
        • reactive-programming
    • Projects and Software types
      • Applicatoin Development
      • Buying or creating software
      • Console Applications
      • Embedded Software development
      • Enterprise
      • Framework Development
      • Games
      • Library development
      • Rewriting
      • White Label Apps
    • State Machines
      • Spring State Machine
  • Other
    • 10x devs
    • Aim of software
    • Choosing Technologies
    • Coding faster
    • Component ownership
    • developer-pain-points
    • Developer Types
    • Effective Software design
    • Full Stack Developer
    • Good coder
    • Issues with Software Engineering and Engineers
    • Learning
    • Logic
    • Role
    • Software Actions
    • Software craftmanship
    • Software Designed
    • Software Engineering
    • Software
    • article-summaries
      • General notes
      • Summary of The Grug Brained Developer A layman's guide to thinking like the self-aware smol brained
      • improve-backend-engineer
      • Optimising Api
      • Simple and Easy
    • README
  • Hardware
    • Cpu memory
    • Storage
  • Integration
    • GRPC
    • API
    • Apis and communications between apps
    • asynchronous and synchronous communications
    • Batch Processing
    • Communications between apps
    • Delivery
    • Distributed Computing
    • Entry point
    • Event Source
    • SDP
    • egress
    • Graphql
    • Idempotency
    • Libraries
    • Long Polling
    • Multiplexing & Demultiplexing
    • Publish Subscribe
    • Push
    • Request & Response
    • REST
    • Remote Method Invocation
    • Remote Procedure Calls
    • Server Sent Events
    • Short Polling
    • Sidecars
    • SOAP
    • Stateless and Stateful
    • Streams
    • Third Party Integrations
    • wdsl
    • Web Services
    • Webhooks
    • repository
    • Kafka
      • Kafka Streams
    • message-queues
      • ActiveMQ
      • Dead Letter Queue
      • JMS
      • Messaging
  • Languages
    • C
    • Choosing A Language
    • cobol
    • Composite Data Types
    • creating
    • Date time
    • Numbers
    • Pass by value vs Pass by reference
    • Primitive Data Types
    • REST anti-patterns
    • Rust
    • Scripting
    • Static typing
    • string
    • Task Oriented Language
    • assembly
    • Getting started
      • Functional Concepts
    • cpp
    • Java
      • Code style
      • Garbage Collection
      • Intellij Debugging
      • Artifacts, Jars
      • Java internals
      • Java resources
      • Java versions
      • JShell
      • Libraries
      • opinionated-guide
      • Starting java
      • Java Tools
      • Why use java
      • Advanced Java
        • Annotations
        • API
        • Database and java
        • Debugging Performance
        • Files IO
        • Finalize
        • JDBC
        • jni
        • Libraries
        • Logging
        • SAP
        • Memory Management
        • Modules
        • OTher
        • Packaging Application
        • Pattern matching
        • performance
        • Properties
        • Reference
        • reflection
        • Scaling
        • Scheduling
        • secruity
        • Serilization
        • Time in Java
        • validation
        • Vector
        • Concurrency and Multithreaading
          • Akka
          • ExecutorCompletionService
          • Asynchronous Programming
          • Concurrency and Threads
          • CountDownLatch
          • Conccurrent Data Structures
          • Executor Service
          • Futures
          • reactive
          • Semaphore
          • structured concurrency
          • Threadlocal
          • Threads
          • Virtual Threads
          • Mutual Exclusion
            • Atomic
            • Synchronized
            • Thread safe class
            • Threads
        • debug
          • heap-dumps
          • thread-dumps
        • functional
          • Collectors
          • Exception Handling
          • Flatmap
          • Functional Programming
          • Generators
          • Immutability
          • issues
          • Optional
          • Parallel Streams
          • Reduce
        • networks
          • HTTP client
          • servlet-webcontainers
          • sockets
          • ssl-tls-https
      • Basics of java
        • compilation
        • computation
        • Conditonal/Flow control
        • Excuting code
        • Instructions
        • Looping/Iterating
        • memory-types-variables
        • methods
        • Printing to screen/debugging
        • Setup the system
        • Data structures
          • Arrays
          • Arayslist/list
          • Map
      • Effective Java notes
        • Creating and Destroying Objects
        • Methods Common to All Objects
        • best-practice-api
        • Classes and Interfaces
        • Enums and Annotations
        • Generics
      • framework
        • aop
        • bad
        • Dagger
        • Databases
        • Lombok
        • Mapstruct
        • netty
        • resliance4j
        • RxJava
        • Vert.x
        • Spring
          • Spring Data Repositories
          • actuator
          • cloud-native
          • H2 Db in Spring
          • Initializrs
          • JDBC Template
          • Java Persistence API (JPA)
          • kotlin
          • Pitfalls and advice
          • PRoxies
          • Reactive
          • spring security
          • spring-aop
          • Spring Boot
          • spring-jdbc
          • Spring MVC
          • Spring Testing
          • Testing
          • Transaction
          • patterns
            • Component Scan Patterns
            • Concurrency
            • Decorator Pattern in Spring
        • Micronaut
          • DI
        • Quarkus
          • database
          • Links
      • Intermediate level java
        • String Class
        • Assertions
        • Casting
        • Clonable
        • Command line arguments
        • Common Libraries/classes
        • Comparators
        • Where to store them?
        • Shallow and Deep Copy
        • Date and Time
        • Enums
        • Equals and Hashcode
        • Equals and hashcode
        • Exceptions
        • Final
        • Finally
        • Generics
        • incrementors
        • Null
        • packages and imports
        • Random numbers
        • Regex
        • Static
        • toString()
        • OOP
          • Accessors
          • Classes
          • Object Oriented Programming
          • Constructors
          • Fields/state
          • Inheritence
          • Interfaces
          • Methods/behaviour
          • Nested Classes
          • Objects
          • Static VS Instance
          • Whether to use a dependency or static method?
        • Other Collections
          • Other Collections
          • Arraylist vs Linkedlist
          • LinkedHashMap
          • Linked List
          • Priority queue
          • Sequenced Collections
          • Set
          • Shallow vs Deep Copy
          • Time Complexity of Collections
          • What Collection To use?
    • kotlin
      • Domain Specific Language
      • learning
      • Libraries
      • Personal Roadmap
      • Links
    • Nodejs
      • Performance
  • Management & Workflow
    • Agile
    • Take Breaks
    • # Communication
    • Engineering Daybook
    • Estimates
    • Feedback Loops
    • Little's law
    • Managing Others
    • poser.
    • Presentations
    • self-improvement
    • software-teams
    • Task List
    • trade-off
    • Types of devs
    • Type of work
    • Waterfall Methodology
    • coding-process
      • Bugs
      • Code Review
      • Code Reviews
      • Documentation
      • Done
      • Handover
      • Mob Programming
      • Navigate codebase
      • Pair Programming
      • Pull Requests
      • How to do a story
      • Story to code
      • Trunk based development
      • Xtreme Programming (XP)
      • debugging
        • 9 Rules of Thumb of Dubugging
        • Debugging
        • using-debugger
      • Legacy code
        • Legacy crisis
        • Working with legacy code
    • Managing work
      • Theory of constraints
      • Distributed Teams
      • estimations
      • Improving team's output
      • Kanban
      • Kick offs
      • Retrospectives
      • Scrum
      • Sign offs
      • Stand ups
      • Time bombs
      • Project management triangle
    • Notion
    • recruitment
      • In Person Test
      • Interviews
      • Unattended test
  • Networks
    • Content Delivery Network - CDN
    • DNS
    • cache control
    • Cookies and Sessions
    • Docker Networking
    • Duplex
    • Etags
    • HTTP Cache
    • HTTP - Hyper Text Transfer Protocol
    • HTTP/2
    • Http 3
    • Internet & Web
    • iptables
    • Keep alive
    • Leader Election
    • Load balancer
    • long-polling
    • Network Access Control
    • Network Address Translation (NAT)
    • Network Layers
    • Nginx
    • OSI network model
    • Persistent Connection
    • Polling
    • Proxy
    • Quic
    • reverse-proxy
    • servers
    • Server sent events (SSE)
    • SSH
    • Streaming
    • Timeouts
    • Url Encoding
    • Web sockets
    • WebRTC (Web Real-Time Communication)
    • Wireshark
    • tcp/ip
      • Congestion
      • IP - Internet Protocol
      • TCP - Transmission Control Protocol
  • Operating Systems
    • Cloud Computing
    • Distributed File Systems
    • Distributed Shared Memory
    • Input/Output Management
    • Inter-Process Communication
    • Threads and Concurrency
    • Virtualization
    • Searching using CLI
    • Bash and scripting
    • Booting of linux
    • makefile
    • Memory Management
    • Processes and Process Management
    • Scheduling
    • Scripting
    • Links
    • Ubuntu
    • Unix File System
    • User groups
    • Linux
  • Other Topics
    • Finite state machine
    • Floating point
    • Googling
    • Setup
    • Unicode
    • Machine Learning
      • Artificial Intelligence
      • Jupyter Notebook
    • Blockchain
    • Front End
      • Single Page App
      • cqrs
      • css
      • Debounce
      • Dom, Virtual Dom
      • ADP
      • htmx
      • Island Architecture
      • Why use?
      • Java and front end tech
      • mermaidjs
      • Next JS
      • javascript
        • Debounce
        • design
        • Event loop
        • testing
        • Typescript
        • react
          • Design
          • learning
          • performance
          • React JS
          • testing
      • performance
      • Static website
    • jobs
      • Tooling
      • bash text editor - vim
      • VS code
      • scaling
        • AI Assistant
        • Debugging
        • General features and tips and tricks
        • IDE - Intellij
        • Plugins
        • Spring usage
  • persistance
    • ACID - Atomicity, Consistency, Isolation, Durability
    • BASE - Basic Availability, Soft state, Eventual Consistency
    • Buffer
    • Connection pooling
    • service
    • Database Migrations - flywaydb
    • Databases
    • Eventual Consistency
    • GraphQL
    • IDs
    • indexing
    • MongoDB
    • Normalisation
    • ORacle sql
    • Partitioning
    • patterns
    • PL SQL
    • Replication and Sharding
    • Repository pattern
    • Sharding
    • Snapshot
    • Strong Consistency
    • links
    • Files
      • Areas to think of
    • hibernate
      • ORM-hibernate
    • Indexes
      • Elastisearch
    • relationships
      • many-to-many
      • SDP
      • serverless
      • x-to-x-relationships
    • sql
      • Group by
      • indexes
      • Joins
      • Common mistakes
      • operators
      • performance
    • types
      • maven-commands-on-intellij
      • in-memory-database-h2
      • Key value database/store
      • Mongo DB
      • NoSQL Databases
      • Relational Database
      • Relational Vs Document Databases
  • Security
    • OAuth
    • API Keys
    • Certificates and JKS
    • Cluster Secruity
    • Communication Between Two Applications via TLS
    • Cookies & Sessions
    • CORS - Cross-Origin Resource Sharing
    • csrf
    • Encryption and Decryption
    • Endpoint Protection
    • JWT
    • language-specific
    • OpenID
    • OWASP
    • Secrets
    • Secruity
    • Servlet authentication and Authorization
    • vault
  • Testing, Maintainablity & Debugging
    • Service-virtualization and api mocking
    • a-test-bk
    • Build Monitor
    • Builds
    • Code coverage
    • consumer-driven contract testing
    • Fixity
    • Living Documentation
    • Mocks, Stubs & Doubles
    • patterns
    • Quality Engineering
    • Reading and working with legacy code
    • Reading
    • remote-debug-intellij
    • simulator
    • Technical Debt
    • Technical Waste
    • Test cases
    • Test Data Builders
    • Test Pyramids
    • Test Types
    • Testing Good Practice
    • Testing
    • What to prime
    • What to test
    • Debugging
      • Debugging in kubernetes or Docker
    • fixing
      • How to Deal with I/O Expense
      • How to Manage Memory
      • How to Optimize Loops
      • How to Fix Performance Problems
    • Legacy Code
      • Learning
      • Legacy code
      • techniques
    • libraries
      • assertj
      • Data Faker
      • Junit
      • mockito
      • Test Containers
      • Wiremock
      • Yatspec
    • Refactoring
      • Code Smells
      • refactoring-types
      • Refactoring
      • Technical Debt
      • pyramid-of-refactoring
        • Pyramid of Refactoring
    • Test first strategies
      • Acceptance Testing Driven Developement (ATDD)
      • Behaviour Driven Development/Design - BDD
      • Inside out
      • Outside in
      • Test driven development (TDD)
    • testing
      • Acceptance tests
      • How Much Testing is Enough?
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      • Honeycomb
      • Testing Microservices
      • Mutation testing
      • Property based testing
      • Smoke Testing
      • social-unit-tests
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      • Static Analysis Test
      • Unit testing
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On this page
  • What
  • mockito
  • mocks
  • How to control final classes
  • How to verify non injected objects
  • Links
  • stubs
  • Limitations
  • Dummy
  • Spy
  • Fakes
  • Mocks
  • Interaction Testing
  • With state testing
  • London/mockist school
  • chicago/classic school
  • Mocking frameworks
  • why
  • Problems with mocking
  • alternative - use real implementations
  • alternative - use fake implementations
  • Links
  • Mocking third party

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  1. Testing, Maintainablity & Debugging

Mocks, Stubs & Doubles

What

  • Mocking is used for protocol testing - it tests how you'll use an API, and how you'll react when the API reacts accordingly.

  • Ideally (in many cases at least), that API should be specified as an interface rather than a class - an interface defines a protocol, a class defines at least part of an implementation.

  • Test doubles turn integration tests into unit/isolation tests

  • https://8thlight.com/blog/uncle-bob/2014/05/14/TheLittleMocker.html

  • https://martinfowler.com/articles/mocksArentStubs.html

  • https://javacodehouse.com/blog/mockito-tutorial/

  • https://www.codurance.com/publications/2019/04/08/introduction-to-test-doubles

  • http://xunitpatterns.com/Mocks,%20Fakes,%20Stubs%20and%20Dummies.html

mockito

  • https://stackoverflow.com/questions/22867680/how-does-mockito-mock-interfaces

  • https://www.toptal.com/java/a-guide-to-everyday-mockito

mocks

  • Cannot mock final class/methods using mockito 1.x, need latest version (use inline dependency)

How to control final classes

  • If class is final but in your scope of change

    • Add an interface to the class to be controlled, and create a test class that implements that interface, then inject it into the system under test

  • If class is final but not in your scope of change

    • Cannot add an interface

    • Can wrap the dependency (adapter), replace the call of the actual with the adapter in codebase and mock the adapter in the tests

How to verify non injected objects

  • When a object is instantiated in the class under test, and want to verify that this object is used, we can use argumentcaptor

  • Thus when we it is used (we check the captor is used in the mehtod we verify) then can grab use the object that was captured, use its method and assert on them

Links

  • https://stackoverflow.com/questions/10598898/mockito-numberformat-mocking-nullpointer-in-when-method

stubs

  • provide canned answers to calls made during the test, usually not responding at all to anything outside what's programmed in for the test

  • Stubbing is the process of giving behavior to a function that otherwise has no behavior on its own—you specify to the function exactly what values to return (that is, you stub the return values).

  • ie From mockito: when(...).thenReturn(...)

  • typically done through mocking frameworks

  • stubbing is appropriate when you need a function to return a specific value to get the system under test into a certain state

  • each stubbed function should have a direct relationship with the test’s assertions.

  • real implementations or fakes are still preferred because they don’t expose implementation details and they give you more guarantees about the correctness of the code compared to stubbing

Limitations

Dummy

  • are passed around but never actually used. Usually they are just used to fill parameter lists.

Spy

  • are stubs that also record some information based on how they were called. One form of this might be an email service that records how many messages it was sent.

Fakes

  • A fake is a lightweight implementation of an API that behaves similar to the real implementation but isn’t suitable for production

  • for example, an inmemory database, wiremock

  • Using a fake is often the ideal technique when you need to use a test double, but a fake might not exist for an object you need to use in a test, and writing one can be challenging because you need to ensure that it has similar behavior to the real implementation, now and in the future

  • Normally use an already written on

    • otherwise it is hard to create, as it must mimic the real implementation and must be maintained

Mocks

  • are pre-programmed with expectations which form a specification of the calls they are expected to receive. They can throw an exception if they receive a call they don't expect and are checked during verification to ensure they got all the calls they were expecting

Interaction Testing

  • is a way to validate how a function is called without actually calling the implementation of the function. A test should fail if afunction isn’t called the correct way; for example, if the function isn’t called at all, it’s called too many times, or it’s called with the wrong arguments.

  • interaction testing is typically done through mocking frameworks

  • Interaction testing is sometimes called mocking

  • it is preferred to test code through state testing

  • it can only validate that certain functions are called as expected. It requires you to make an assumption about the behavior of the code; for example, “If database.save(item) is called, we assume the item will be saved to the database."

  • Leaks details to test

  • when to use

    • You cannot perform state testing because you are unable to use a real implementation or a fake

    • Differences in the number or order of calls to a function would cause undesired behavior

    • PREFER TO PERFORM INTERACTION TESTING ONLY FOR STATE-CHANGING FUNCTIONS

    • you should perform interaction testing only for functions that are state-changing

With state testing

  • you call the system under test and validate that either the correct value was returned or that some other state in the system under test was properly changed

  • it actually validates this assumption (such as by saving an item to a database and then querying the database to validate that the item exists)

  • if cannot state, use interaction testing, but also use integration testing

London/mockist school

chicago/classic school

Mocking frameworks

  • A mocking framework is a software library that makes it easier to create test doubles within tests;

    • it allows you to replace an object with a mock, which is a test double whose behavior is specified inline in a test.

  • The use of mocking frameworks reduces boilerplate because you don’t need to define a new class each time you need a test double.

why

  • Essential for testing and not want to call anything which can have consequences (ie state change (internally or externally), production calls, charges for services)

  • If you want to verify the behavior of the system under test (SUT), using mockito can be more effective as it allows you to verify interactions between the SUT and its collaborators.

Problems with mocking

  • When you mock something you’re removing all confidence in the integration between what you’re testing and what’s being mocked.

    • You will need to do separate tests for integration part, to see that it actually works

  • mocking is somewhat overused - often you're not really interested in the exact interaction, you really want a stub... but mocking framework can be used to create stubs, and you fall into the trap of creating brittle tests by mocking instead of stubbing. It's a hard balance to get right though.

  • When using verify (to check a dependency has been called) this ties the test to the implementation/structure of the code, rather than the behaviour

    • better to have stub injected, and assert on the stub

    • dependencies are part of the constructor and thus public

  • Can lead to mocking everything except the SUT

    • This can make test brittle

    • SUT is not necessarily a class, but can be a bunch of objects to test the behaviour

    • Over-reliance on mocks can lead to tests that are not representative of the real-world behavior of the system, resulting in tests that are less effective and less reliable.

  • SUT with lots of dependencies and interactions, and use of mocks can make tests more complex and unclear with lots of extra code

  • Leaks implementation details into your test

    • Ideally, a good test should need to change only if user-facing behavior of an API changes; it should remain unaffected by changes to the API’s implementation

  • Use of mocking frameworks can lead to false sense of security

    • MAke tests hard to maintain

    • makes refactoring harder, as tests will break

    • bug finding hard

  • test doubles, does not have exact sameness as the real implementation, so always some form of security that it is give correct evaluations

  • https://engineering.talkdesk.com/double-trouble-why-we-decided-against-mocking-498c915bbe1c

  • https://youtu.be/7AGQ9dhWCX0 Test Doubles Are A Scam – Matt Diephouse

  • Mocking can add additional processing time during the build process, slowing down the overall build time.

alternative - use real implementations

  • makes refactoring easier

  • known as classical testing

  • tests are more realistic, more confidence in the system

  • Using real implementations can cause your test to fail if there is a bug in the real implementation.

    • A real implementation is preferred if it is fast, deterministic, and has simple dependencies. For example, a real implementation should be used for a value object

    • for more complex code, using a real implementation often isn’t feasible

      • ie database or network calls, edge of app. these can be mocked

      • ie for nondeterministic code such as external servers, time, randommness

  • Can be slow

  • Need to construct the object graph for the SUT, can be complex

    • Should use the same mechanism as test, and adjust (ie factories) to replace mocked dependencies

alternative - use fake implementations

  • Instead of a real implementation, use an inmemory version

  • This a fake or stub

  • If there is a logic which mimics the actual impl in the fake, it needs to be tested to ensure it matches the real impl and be used with accuracy in the tests

Links

  • https://medium.com/javascript-scene/mocking-is-a-code-smell-944a70c90a6a

  • https://chemaclass.medium.com/to-mock-or-not-to-mock-af995072b22e

Mocking third party

  • This should not be done, should avoid mocking third party code

  • https://youtu.be/v6hP2MXoVrI Don't Mock 3rd Party Code

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