can we use only ArrayList and Hashmap to solve interview questions

It's true that you can solve many interview problems using an ArrayList or HashMap and Java Streams, but relying solely on this approach is generally not recommended for several reasons.

While streams offer a concise, readable way to process data, they are just a way to execute an algorithm. The interviewer wants to see your fundamental understanding of data structures and algorithms.

Here is a breakdown of why this approach is often insufficient:

1. Data Structure Ignorance (The Biggest Pitfall) 🧱

The core of an interview is proving you can choose the right tool for the job. A stream only processes the data structure you provide it; it doesn't fix the underlying structure's limitations.

• When a List/Map Fails: If the problem requires constant-time maximum/minimum retrieval, you need a PriorityQueue (Heap). If it requires guaranteed sorting, you need a TreeSet (Red-Black Tree). If you only use a List, you'd have to sort or scan it ($O(N \log N)$ or $O(N)$) repeatedly, which is a major efficiency fail.
• The Big O Question: If you solve a uniqueness problem by filtering an ArrayList ($O(N^2)$ total complexity) instead of using a HashSet ($O(N)$ total complexity), the interviewer will recognize the massive performance difference and deduce that you lack knowledge of more efficient structures.

2. Inefficient Stream Operations 🐢

While streams are powerful, they hide inefficiency if used carelessly:

• Sorting: Calling .sorted() on a stream has an $O(N \log N)$ time complexity. If the data only needs to be sorted once, fine. If you re-stream and re-sort repeatedly, it's very wasteful compared to a structure that keeps data sorted dynamically.
• Filtering Complex Criteria: For problems like finding shortest paths in a graph (BFS/DFS), a stream filter is completely inadequate. These problems require specific state management using Stacks, Queues, and iterative/recursive algorithms that are difficult or impossible to express efficiently using the standard Stream API.

3. Lack of Control and Debugging 🕵️

Streams are highly abstract, which can sometimes be a negative in an interview:

• State Management: Complex algorithms often require managing external state, modifying indices, or using multiple pointers (like in two-pointer problems). Streams are designed to be stateless and functional, making these imperative algorithms awkward or inefficient to implement.
• Debugging/Tracing: In a real-time debugging scenario during an interview, it's often easier for an interviewer to follow a simple for loop that iterates step-by-step than a complex, chained stream pipeline.

Conclusion

You should view List and Map as excellent defaults, and Streams as an excellent tool for processing them.

However, to impress an interviewer, you must demonstrate a broader toolkit. Be ready to explain why you chose a HashMap over an ArrayList for $O(1)$ lookups, or why a PriorityQueue is a better fit than a stream for finding the largest $K$ elements.

Relying on just List, Map, and Streams suggests a limited understanding of core data structure trade-offs.