Quick Answer
The answer is LinkedHashSet, which is the best collection for an LRU cache implementation in Java because it combines a hash table with a doubly linked list to maintain insertion order while providing O(1) average-time complexity for add, remove, and contains operations. When a session is accessed, you remove and re-add it to the LinkedHashSet, which moves it to the end of the iteration order; when the cache exceeds its maximum size of 1000, you simply remove the first element (the least recently used). This directly solves the O(n) linear scan problem of a LinkedList, where searching for an existing session to update its position was the performance bottleneck. On the Oracle Certified Professional Java SE 17 Developer 1Z0-829 exam, this question tests your understanding of collection performance characteristics and the subtle difference between insertion order and access order—a common trap is confusing LinkedHashSet with TreeSet or HashSet, which lack predictable ordering. Remember the memory tip: "LinkedHashSet links order with hash speed, making LRU a breeze."
This 1Z0-829 practice question tests your understanding of working with arrays and collections. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A developer is implementing a cache that stores recent user sessions. The cache should maintain the most recently accessed session at the end, and when the cache reaches its maximum size (1000), it should remove the least recently accessed session (i.e., the oldest). The developer chooses a LinkedList to store sessions, adding new sessions at the end and removing from the front. However, performance is poor because searching for an existing session to update its position requires O(n) linear scan. Which collection should replace the LinkedList to improve performance while maintaining the removal order?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "least"
Why it matters: You want the option with minimum overhead, fewest steps, or lowest impact — not the most feature-rich or comprehensive answer.
TreeSet
Why wrong: Sorted order, not access order.
HashSet
Why wrong: No order guarantee.
LinkedHashSet
O(1) add, remove, contains; maintains insertion order; can reinsert to move to end.
ArrayList
Why wrong: Removal from front is O(n).
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
LinkedHashSet
LinkedHashSet (C) maintains insertion order (which can be used to represent access order if reinserted on access) and provides O(1) average-time complexity for add, remove, and contains operations. By removing and re-adding a session upon access, it moves to the end, and the oldest (first inserted) can be removed from the front when the size exceeds 1000, solving the O(n) scan problem of LinkedList.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
TreeSet
Why it's wrong here
Sorted order, not access order.
HashSet
Why it's wrong here
No order guarantee.
LinkedHashSet
Why this is correct
O(1) add, remove, contains; maintains insertion order; can reinsert to move to end.
Clue confirmation
The clue word "least" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
ArrayList
Why it's wrong here
Removal from front is O(n).
Common exam traps
The trap here is that candidates often choose HashSet for speed but forget that order is required, or choose TreeSet thinking sorted order helps, but neither maintains insertion/access order for LRU eviction.
Detailed technical explanation
LinkedHashSet extends HashSet and uses a doubly linked list internally to maintain the order of elements (insertion order by default, but can be configured for access order via LinkedHashMap). In a cache scenario, reinserting a key on access effectively moves it to the end of the linked list, making the oldest element at the head for O(1) removal. This is the same mechanism used by Java's LinkedHashMap with access-order=true, which is the classic LRU cache implementation.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the 1Z0-829 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
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FAQ
Working with Arrays and Collections — This question tests Working with Arrays and Collections — Read the scenario before looking for a memorised answer..
The correct answer is: LinkedHashSet — LinkedHashSet (C) maintains insertion order (which can be used to represent access order if reinserted on access) and provides O(1) average-time complexity for add, remove, and contains operations. By removing and re-adding a session upon access, it moves to the end, and the oldest (first inserted) can be removed from the front when the size exceeds 1000, solving the O(n) scan problem of LinkedList.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "least". You want the option with minimum overhead, fewest steps, or lowest impact — not the most feature-rich or comprehensive answer.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 25, 2026
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