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Java CLI Customer Management System
Modular architecture and separation of concerns

Executive Technical Summary

A modular Java command-line application for managing customer records within a fixed-capacity system. The project emphasizes clean separation of concerns, centralized validation, and maintainable architecture through refactoring a monolithic implementation into cohesive domain, storage, validation, and orchestration components. The system supports validated data entry, indexed lookup by unique identifier, and range-based queries over customer sales data, demonstrating disciplined backend design and defensive programming practices.

 

Key Focus Areas: modular refactoring, data modeling, validation-first logic, and maintainable backend architecture.

System Architecture Overview

The system is organized around clearly defined layers that isolate responsibilities and enforce predictable data flow.

Architecture layers:

  • CLI Interface Layer: Menu-driven user interaction and command routing

  • Controller / Orchestration Layer: Coordinates application operations

  • Domain Layer: Customer model and business rules

  • Storage Layer: Fixed-capacity customer repository

  • Validation Layer: Centralized input and domain validation utilities

This architecture ensures that UI concerns never leak into domain or storage logic.

Repository Structure

The repository is structured to emphasize separation of concerns between customer data modeling, validation, storage, and application orchestration. The design reflects a refactoring from a monolithic implementation into cohesive components that support validated data entry, indexed lookup, and range-based queries.

 

java-cli-customer-management-system/

├── src/

│   ├── main/

│   │   └── java/

│   │       ├── customer/           # Customer domain model

│   │       ├── controller/         # Application orchestration

│   │       ├── storage/            # Fixed-capacity customer storage

│   │       ├── validation/         # Centralized validation logic

│   │       └── util/               # Shared helpers

│   └── test/

│       └── java/                   # Unit tests

├── README.md

└── pom.xml

Core Design Decisions & Rationale

Modular Refactoring from Monolithic Design

The project originated as a single-class implementation and was refactored into discrete components.

Rationale:

  • Improves readability and maintainability

  • Enables targeted testing

  • Clarifies architectural intent

 

Separation of Concerns

Each layer owns a single responsibility:

  • Input handling

  • Validation

  • Data storage

  • Business logic

This prevents tight coupling and simplifies future enhancements.

 

Centralized Validation Strategy

All validation logic is centralized rather than duplicated across the UI or domain layers.

Validation includes:

  • Required field presence

  • Data type and range checks

  • Unique identifier enforcement

This ensures consistent behavior across all operations.

 

Fixed-Capacity Data Management

Customer records are stored in a fixed-size structure to enforce explicit capacity constraints.

Rationale:

  • Demonstrates defensive programming

  • Forces explicit error handling

  • Highlights awareness of resource limits

Domain Model & Data Flow

The Customer domain model encapsulates customer attributes and exposes read-only access where appropriate.

Operational flow:

  1. User input collected via CLI

  2. Validation applied before storage

  3. Customer records stored in indexed structure

  4. Queries executed against validated data

  5. Results returned to the UI layer

Validation & Data Integrity Strategy

Validation enforces:

  • Non-null and non-empty fields

  • Numeric ranges for sales values

  • Uniqueness of customer identifiers

  • Safe handling of invalid or out-of-range input

Invalid data is rejected before persistence or query execution.

Query & Lookup Capabilities

The system supports:

  • Lookup by unique customer ID

  • Iteration over all customer records

  • Range-based queries on customer sales data

These operations demonstrate indexed access and controlled traversal of stored data.

Testing & Verification Approach

System behavior was verified through:

  • Manual execution scenarios

  • Boundary condition testing (capacity limits)

  • Validation failure cases

  • Query correctness checks

The architecture supports straightforward expansion into automated unit testing.

Tools & Technologies

  • Language: Java

  • Paradigm: Object-Oriented Programming

  • UI: Command-line interface

  • Validation: Centralized validation utilities

  • Build: Standard Java project structure

Outcome & Engineering Takeaways

Engineering Capabilities Demonstrated

  • Refactoring monolithic code into modular architecture

  • Designing validation-first backend systems

  • Managing fixed-capacity data structures

  • Implementing indexed lookup and range queries

  • Enforcing clean separation of concerns

 

System Qualities Achieved

  • Maintainability: modular, readable structure

  • Correctness: validation-enforced data integrity

  • Predictability: explicit capacity and error handling

  • Extensibility: prepared for future UI or persistence upgrades

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