5 Junior Java Mistakes That Kill Job Offers (and How to Fix Them)

In the competitive landscape of 2025, technical interviewers are looking for more than just code that compiles. They are scanning for maintainability, scalability, and “production-readiness.”

Many candidates solve the algorithmic challenge but fail the “smell test.” They write code that works in a LeetCode sandbox but would cause outages or memory leaks in a real-world Spring Boot microservice. These subtle habits often signal to hiring managers that a candidate is still stuck in a “student mindset.”

In this article, we will dissect five common mistakes that distinguish junior applicants from professional engineers. We will provide the bad code, the professional fix, and the reasoning behind it so you can refactor your habits before your next interview.

Prerequisites and Environment

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To follow the examples below, ensure you are familiar with the current standard ecosystem:

• JDK: Java 21 (LTS) or Java 23.
• IDE: IntelliJ IDEA or Eclipse.
• Dependencies: While standard libraries suffice for most examples, we assume a familiarity with SLF4J for logging and Lombok (optional, though we will use Records for purity).

1. The Silent Killer: Swallowing Exceptions

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Nothing makes a Senior Engineer reject a code review faster than an empty catch block or printing a stack trace to standard output.

The Mistake

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Junior developers often treat exceptions as annoyances to be silenced so the code compiles.

// ❌ The Rookie Way
public User loadUser(String filePath) {
    try {
        // Assume logic to read file
        return new User(filePath);
    } catch (Exception e) {
        e.printStackTrace(); // Stops the logs, but kills observability
        return null;         // Returns null, leading to NPEs later
    }
}

Why It Fails

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1. Observability Loss: e.printStackTrace() prints to stderr, which is often lost in modern containerized environments (Kubernetes/Docker) where structured logging is required.
2. Generic Catching: Catching Exception hides critical errors like NullPointerException that should crash the flow, conflating them with expected IO errors.

The Professional Fix

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Use a Logger, catch specific exceptions, and either recover or rethrow a custom runtime exception.

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;

public class UserService {
    private static final Logger logger = LoggerFactory.getLogger(UserService.class);

    // ✅ The Pro Way
    public String loadUserConfig(Path path) {
        try {
            return Files.readString(path);
        } catch (IOException e) {
            // Log with context, but don't swallow
            logger.error("Failed to read user config from path: {}", path, e);
            // Translate to a domain exception
            throw new UserConfigurationException("Unable to load configuration", e);
        }
    }
}

class UserConfigurationException extends RuntimeException {
    public UserConfigurationException(String message, Throwable cause) {
        super(message, cause);
    }
}

2. The “Return Null” Trap

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In 2025, returning null from a method that returns a collection or an object is largely considered technical debt.

The Mistake

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Returning null forces the consumer of your API to write defensive code (if (x != null)). If they forget, the application crashes.

The Professional Fix

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1. For Collections: Return an empty collection.
2. For Objects: Use java.util.Optional.

import java.util.Collections;
import java.util.List;
import java.util.Optional;

public class CustomerRepository {

    // ❌ Avoid this
    public List<String> findOrdersBad(String customerId) {
        if (customerId == null) return null; // Risky
        return db.getOrders(customerId);
    }

    // ✅ Prefer Empty Collections
    public List<String> findOrdersGood(String customerId) {
        if (customerId == null) return Collections.emptyList();
        List<String> orders = db.getOrders(customerId);
        return orders != null ? orders : Collections.emptyList();
    }

    // ✅ Prefer Optional for single values
    public Optional<Customer> findCustomer(String id) {
        Customer customer = db.findById(id);
        return Optional.ofNullable(customer);
    }
}

3. String Concatenation in Loops (Performance Killer)

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This is a classic interview question, but many candidates still fail it in take-home assignments.

The Mistake

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Strings in Java are immutable. When you concatenate inside a loop using +, Java creates a new String object and a new StringBuilder instance for every single iteration.

// ❌ O(N^2) Performance Disaster
public String createCSV(List<String> items) {
    String csv = "";
    for (String item : items) {
        csv += item + ","; // Creates massive memory churn
    }
    return csv;
}

The Visualization

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Here is why this kills performance. The “Old String” is discarded and garbage collected, while a “New String” is allocated repeatedly.

The Professional Fix

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Use StringBuilder explicitly, or better yet, String.join or Streams.

import java.util.List;
import java.util.stream.Collectors;

public class CsvBuilder {

    // ✅ Efficient Approach 1: StringBuilder
    public String createCSV(List<String> items) {
        StringBuilder sb = new StringBuilder();
        for (String item : items) {
            sb.append(item).append(",");
        }
        return sb.length() > 0 ? sb.substring(0, sb.length() - 1) : "";
    }

    // ✅ Modern Approach (Java 8+)
    public String createCSVModern(List<String> items) {
        return String.join(",", items);
    }
}

4. Coding Like It’s Java 7 (Ignoring Modern Syntax)

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Java evolves rapidly (every 6 months). Using outdated syntax signals that you don’t keep up with the industry.

The Comparison

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Hiring managers love to see candidates using Records, var, and Switch Expressions. It shows you care about conciseness and readability.

The Professional Fix

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Adopt Records for DTOs (Data Transfer Objects).

// ❌ Verbose
public class Point {
    private final int x;
    private final int y;
    
    public Point(int x, int y) { 
        this.x = x; 
        this.y = y; 
    }
    // ... insert 20 lines of equals(), hashCode(), toString()
}

// ✅ Modern Java 21 Style
public record Point(int x, int y) {}

public class GeometryService {
    public void process() {
        // Use 'var' for local variables when type is obvious
        var point = new Point(10, 20);
        System.out.println(point); // toString() is automatic!
    }
}

5. Leaking Mutable State

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Concurrency bugs are the hardest to debug. A common mistake is exposing internal lists or maps through getters, allowing external classes to modify the internal state of your object.

The Mistake

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You implement a cache or a list, but you return the actual reference to the list.

public class OrderManager {
    private List<String> orders = new ArrayList<>();

    // ❌ Dangerous: External code can clear your internal list!
    public List<String> getOrders() {
        return orders;
    }
}

The Professional Fix

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Return an unmodifiable view or a defensive copy.

import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

public class OrderManager {
    private final List<String> orders = new ArrayList<>();

    public void addOrder(String order) {
        orders.add(order);
    }

    // ✅ Safe: Callers can read, but cannot modify
    public List<String> getOrders() {
        return Collections.unmodifiableList(orders);
    }
    
    // ✅ Alternative: Return a copy (Java 10+)
    public List<String> getOrdersCopy() {
        return List.copyOf(orders);
    }
}

Conclusion

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Moving from a “Junior” to a “Professional” Java developer isn’t just about memorizing algorithms; it’s about writing code that is robust, readable, and safe for production.

Summary of Actionable Steps:

1. Stop swallowing exceptions. Log them properly.
2. Eliminate Nulls. Use Optional and empty collections.
3. Mind your Loops. Use StringBuilder or String.join.
4. Update your Syntax. Use Records and var.
5. Protect your State. Use unmodifiable collections.

By applying these patterns in your next technical assignment or pair programming interview, you signal to the interviewer that you are ready to contribute to a professional codebase on day one.

Happy Coding!