/Cloud-Humans-TakeHome

Primary LanguageJava

Cloud Humans Backend Take Home

Run requirements

  • IntelliJ IDEA
  • Java 11 & Apache Maven

Running through IntelliJ

  • All you need to do is to start the application using the default application.properties profile.

Running via Terminal

  • In the root directory (at the pom.xml level), type:
mvn spring-boot:run

If you're using Windows, I encourage you to do that via Windows Powershell

Calling the API

Make a POST request to localhost:8080/api/v1/pro/evaluate, using a JSON structure as the example below:

{
  "age": 35,
  "education_level": "high_school",
  "past_experiences": {
    "sales": false,
    "support": true
  },
  "internet_test": {
    "download_speed": 50.4,
    "upload_speed": 40.2
  },
  "writing_score": 0.6,
  "referral_code": "token1234"
}

Main Technical Decisions

  1. DTO

Knowing that the JSON input wouldn't follow the Java Naming Conventions, I decided to use the DTO Data Transfer Object pattern. The library responsible for implementing the DTO is Model Mapper, and its implementation can be spotted below:

public EvaluationDTO evaluate(@RequestBody @Valid ProDTO proDTO) {
        var mapper = new ModelMapper();
        var pro = mapper.map(proDTO, Pro.class);

        Evaluation evaluation = this.proService.evaluatePro(pro);
        return mapper.map(evaluation, EvaluationDTO.class);
    }
  1. Project Architecture

As the aim of this project is to accurately return data based on the user's input, I tried to design the most efficient and readable architecture for this. I found that the following structure would fit:

src/main/java
  algorithm/ # Where the magic happens!
  controller/ # HTTP REST requests
  dto/ # Only Data Transfer Objects!
  enums/
  exception/ # Exceptions & Exception Handling
  model/ # Java Objects (or domain)
  repository/ # Just to represent a SQL Data Source
  service/ # Brings everything together :)

Relevant Comments about this Project

Taking a look over the code, I think that the best part of it is how clean & maintainable the algorithm's architecture is. When I first designed the methods, I tried to apply some popular best practices that would grant me a readable code. Honestly, if I couldn't reach it, I'm pretty sure that at least I'm almost there.

Now, let us analyze some things that I'm satisfied to deliver in this project:

  1. Well-written Unit Tests (see EligibilityAlgorithmTest and ProServiceTest)
  2. Input Validations (see ProDTO)
  3. The project architecture described previously
  4. This rich documentation! :D

Be welcome to drop a 🌟 if you want!