Prepare for smartnews technical interviews with 5 tracked LeetCode questions, sortable by difficulty and topic.
| Title | Difficulty | Topics | Frequency | LeetCode |
|---|---|---|---|---|
| Largest Palindromic Number | Medium | 100% | Solve | |
| LRU Cache | Medium | 100% | Solve | |
| Minimum Deletions to Make Character Frequencies Unique | Medium | 100% | Solve | |
| 3Sum | Medium | 68.9% | Solve | |
| Maximal Network Rank | Medium | 64.2% | Solve |
5 questions total
Company analytics
Questions tracked
5
Questions currently linked to smartnews
Topics represented
11
Distinct topics visible in this company set
Dominant difficulty
medium
100% of tracked questions
Avg frequency score
86.6
Mean frequency across this company question set
smartnews currently has 5 tracked questions linked to 11 topics, so this page is a good benchmark for how deep the dataset goes on one employer.
The most common topics for smartnews include Hash Table, Greedy, Sorting, and String. Hash Table alone appears 3 times in the visible topic distribution. That topic spread helps you identify whether this company is repeating a few patterns or testing across a broader surface area.
The current question set averages a frequency score of 86.6, and medium is the dominant difficulty bucket at 100% of tracked coverage. That makes it easier to decide whether to practice for repetition, complexity, or both.
smartnews related paths
This section answers the most practical questions about using the smartnews route as a company-specific LeetCode study page.
Start with the highest-frequency questions inside Hash Table, Greedy, and Sorting, then sort the table by frequency to build a shortlist. That gives you a faster first pass through smartnews's interview patterns than trying to cover every linked problem at once.
medium makes up 100% of the tracked smartnews question set. Use that split to decide whether your study plan should emphasize coverage, realistic interview pressure, or deeper problem solving.
Use this page to identify smartnews's strongest topic signal, then open Hash Table and the global most-asked or questions explorer routes to see whether that company-specific pattern is also common across the wider dataset.
