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?
      • Approval Testing
      • Bad Testing
      • End to end tests
      • Honeycomb
      • Testing Microservices
      • Mutation testing
      • Property based testing
      • Smoke Testing
      • social-unit-tests
      • solitary-unit-tests
      • Static Analysis Test
      • Unit testing
  • Version Control - Git
    • Branch by Abstraction
    • feature-branching
    • Git patches
    • Trunk Based Development
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Coding faster

Learning keyboard shortcuts: Using keyboard shortcuts can save a lot of time when coding, as it eliminates the need to constantly reach for the mouse.

Familiarizing oneself with the tools and technologies being used: This can make the coding process faster and more efficient, as developers will know how to navigate the tools and technologies they are working with.

Using code snippets and templates: Developers can save a lot of time by using code snippets and templates that they can easily insert into their code.

Refactoring code: Cleaning up and reorganizing existing code can make the coding process faster and more efficient.

Continuous learning and staying up-to-date with new technologies: This can help developers improve their skills and stay ahead of the curve, making them more efficient coders.

Collaboration with other developers: Collaborating with other developers can also help to improve coding speed and efficiency, as developers can share ideas and learn from each other.

Using version control: Using version control systems like Git can help developers keep track of their code and collaborate with other team members more efficiently.

Automating repetitive tasks: Developers can use tools such as scripts or macros to automate repetitive tasks, which can save a lot of time in the long run.

Pair programming: This is a technique where two developers work together on the same code, sharing ideas and discussing solutions in real-time. This can help to improve coding speed and efficiency as well as knowledge sharing.

Using a consistent coding style: Having a consistent coding style throughout a project can make it easier to read and understand the code, which can help speed up the coding process.

Using a good development environment: Having a good development environment can help developers to work more efficiently, by providing features such as code completion, debugging tools, and code formatting.

Prioritizing tasks and focusing on one task at a time: Developers can increase their coding speed by prioritizing tasks and focusing on one task at a time, rather than trying to multitask.

Practicing and honing your skills: Practicing coding regularly can help developers to improve their skills and become more efficient coders over time.

Using a code linter: A code linter is a tool that checks your code for errors and inconsistencies, which can help to identify and fix problems quickly and improve coding speed.

Using a code profiler: A code profiler is a tool that helps to identify performance bottlenecks in your code, which can help to optimize the code and make it run faster.

Adopting a test-driven development approach: Test-driven development (TDD) is a software development technique where developers write tests for their code before writing the code itself. This approach can help to improve coding speed by catching errors early and ensuring that the code is working as expected.

Using a code review process: A code review process where code is reviewed by other developers can help to identify and fix errors and inconsistencies quickly, which can improve coding speed.

Breaking down large problems into smaller tasks: breaking down large problems into smaller tasks can make it easier to tackle them, and help developers to focus on one thing at a time, which can improve coding speed.

Using a time tracking tool: using a time tracking tool can help developers to track how much time they spend on different tasks and identify areas where they can improve their efficiency.

Using the Pomodoro technique: the Pomodoro technique is a time management method that can help developers to work more efficiently by breaking work into shorter intervals, with frequent breaks.

Automating repetitive deployments: Automating repetitive deployments can help developers to deploy code quickly and easily, without having to manually perform the same steps over and over again.

Using a code generation tool: A code generation tool can help to automate the process of creating repetitive or boilerplate code, which can save a lot of time and improve coding speed.

Using a code formatter: A code formatter can help to automatically format your code, making it consistent and easier to read, which can improve coding speed.

Using a containerization tool: Containerization tools such as Docker can help developers to quickly and easily set up development environments, which can improve coding speed and efficiency.

Using a code analysis tool: A code analysis tool can help developers to identify and fix issues in their code, such as security vulnerabilities, which can improve coding speed and efficiency.

Using a code collaboration tool: A code collaboration tool can help developers to work together more efficiently, by allowing them to share code, discuss changes and track progress.

Using a code documentation tool: A code documentation tool can help developers to quickly and easily document their code, which can make it easier to understand and maintain, which can improve coding speed and efficiency.

Using a code management tool: A code management tool can help developers to keep track of their code, collaborate with others, and easily rollback to previous versions of the code, which can improve coding speed and efficiency.

Using a code optimization tool: A code optimization tool can help developers to identify and fix performance issues in their code, which can improve coding speed and efficiency.

Using a code search tool: A code search tool can help developers to quickly find the code they need, which can improve coding speed and efficiency.

Using a code coverage tool: A code coverage tool can help developers to identify which parts of their code are not being tested, which can improve coding speed and efficiency.

Using a code review tool: A code review tool can help developers to automate the code review process, which can improve coding speed and efficiency.

Using a code merge tool: A code merge tool can help developers to easily merge code changes from multiple developers, which can improve coding speed and efficiency.

Using a code versioning tool: A code versioning tool can help developers to keep track of different versions of their code, which can improve coding speed and efficiency.

Using a code comparison tool: A code comparison tool can help developers to compare different versions of code, which can improve coding speed and efficiency.

Using a code commenting tool: A code commenting tool can help developers to add comments to their code, which can make it easier to understand and maintain, which can improve coding speed and efficiency.

Using a code backup tool: A code backup tool can help developers to easily backup their code, which can improve coding speed and efficiency.

Using a code sharing tool: A code sharing tool can help developers to share code with others, which can improve coding speed and efficiency.

Using a code optimization technique: Optimizing the code using techniques such as caching, indexing, or using data structures can improve the performance and hence speed of the code.

Using a code review checklist: Having a checklist of things to check during code review can help developers to focus on the most important aspects of the code, which can improve coding speed and efficiency.

Using a code review bot: A code review bot is a tool that automates the code review process by analyzing the code and providing feedback and suggestions for improvements.

Using a code profiling tool: A code profiling tool can help developers to identify bottlenecks in their code, which can improve coding speed and efficiency.

Using a code refactoring tool: A code refactoring tool can help developers to improve the structure and organization of their code, which can improve coding speed and efficiency.

Using a code snippet manager: A code snippet manager can help developers to easily access and reuse commonly used code snippets, which can improve coding speed and efficiency.

Using a code completion tool: A code completion tool can help developers to quickly complete code snippets, which can improve coding speed and efficiency.

Using a code visualization tool: A code visualization tool can help developers to visualize the structure of their code, which can improve coding speed and efficiency.

Using a code analysis service: A code analysis service can help developers to analyze their code for security vulnerabilities, performance issues, and coding standards compliance, which can improve coding speed and efficiency.

Using a code snippet library: A code snippet library can help developers to quickly find and reuse code snippets, which can improve coding speed and efficiency.

Using a code optimization service: A code optimization service can help developers to optimize their code for performance, which can improve coding speed and efficiency.

Using a code generation service: A code generation service can help developers to automatically generate code based on specific templates and requirements, which can improve coding speed and efficiency.

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