Introduction

Oracle technical interviews are known for their depth and complexity, and one such problem about generating sentences using anagrams stands out as a comprehensive test of analytical and problem-solving skills. This article recounts how a candidate, with the assistance of CSOAHelp, effectively approached and excelled in this challenging task.

---

Problem Description

Task:

• Given a list of words (wordSet) and a list of sentences (sentences), each word in the sentences can be replaced by its anagram from the wordSet.
• The goal is to calculate the total number of distinct sentences that can be generated by replacing words with their anagrams.

Example:

wordSet = ["listen", "silent", "it", "is"]  
sentence = "listen it is silent"  

Generated Sentences:  
1. listen it is silent  
2. listen it is listen  
3. silent it is silent  
4. silent it is listen

Objective:
For each sentence, return the total number of possible sentences that can be generated.

---

Clarification Questions

In the initial phase of the interview, the candidate, guided by CSOAHelp, asked key clarifying questions to ensure a clear understanding of the problem:

1. Are words case-sensitive?
   • Answer: No, all words are considered in lowercase.
2. Are all words in the sentences guaranteed to exist in wordSet?
   • Answer: Yes.
3. Does the word order in a sentence need to be preserved?
   • Answer: Yes, the order must remain unchanged.
4. How do we determine if two words are anagrams?
   • Answer: Sort the letters in both words. If the sorted results match, the words are anagrams.

---

Solution Approach

Core Idea

1. Build an Anagram Map:
   • For each word in wordSet, sort its letters and use the sorted result as the key in a dictionary.
   • The value of each key represents the count of words in wordSet that are anagrams of that key.
   • Example:text复制代码wordSet = ["listen", "silent", "it", "is"] Anagram Map: { "eilnst": 2, "it": 1, "is": 1 }
2. Calculate Sentence Variants:
   • For each sentence, split it into words and look up the anagram count for each word in the anagram map.
   • Multiply the counts of all words in the sentence to get the total number of variants for that sentence.
3. Optimize Storage and Lookup:
   • Store only the counts of anagrams in the dictionary to save memory.
   • Use precomputed values for fast lookup during sentence processing.

---

Interview Process Recreation

Step 1: Building the Anagram Map

The candidate, following CSOAHelp's guidance, explained the process of building an anagram map:

• Iterate over wordSet.
• For each word, sort its letters and use the sorted result as the dictionary key.
• Increment the value associated with each key by 1 to record the count of its anagrams.

Example Execution:

Input: wordSet = ["listen", "silent", "it", "is"]  
Output: { "eilnst": 2, "it": 1, "is": 1 }

Step 2: Calculating Sentence Variants

For the sentence "listen it is silent", the candidate walked through the process:

1. Split the sentence into words: ["listen", "it", "is", "silent"].
2. Query the anagram map for each word:
   • "listen" → 2
   • "it" → 1
   • "is" → 1
   • "silent" → 2
3. Multiply the counts: 2 × 1 × 1 × 2 = 4.

The candidate highlighted the importance of correctly initializing a result variable (now) to 1 and multiplying it with each word’s anagram count during traversal.

---

Step 3: Addressing Edge Cases

The interviewer posed a series of edge cases to test the candidate's robustness:

• What if sentences is empty?
  • Response: Return an empty list.
• What if wordSet contains duplicate words?
  • Response: Handle duplicates naturally as they do not affect the logic due to dictionary-based counting.

CSOAHelp encouraged the candidate to clearly articulate these scenarios, demonstrating attention to detail and thorough understanding.

---

Optimization Discussion

The interviewer probed the candidate on optimizing the solution for larger datasets. Key points discussed:

1. Time Complexity:
   • Building the map: O(N⋅Llog⁡L), where N is the number of words in wordSet and L is the average word length.
   • Processing sentences: O(M⋅W), where M is the number of sentences and W is the average number of words per sentence.
2. Space Complexity:
   • O(K）, where Kis the number of unique anagram keys in the map.

---

Feedback and Candidate Evaluation

The candidate received positive feedback for:

1. Logical and structured problem-solving.
2. Clear communication of ideas and optimization strategies.
3. Thorough handling of edge cases and clarifications.

The interviewer appreciated the collaboration facilitated by CSOAHelp, which ensured the candidate's responses were polished and well-articulated.

---

Conclusion

This interview scenario highlights how CSOAHelp enables candidates to navigate challenging problems with confidence. By providing structured guidance and addressing potential pitfalls, CSOAHelp empowers candidates to perform at their best in high-stakes interviews. If you're preparing for technical interviews like Oracle's, consider leveraging CSOAHelp for comprehensive support and preparation!

如果您也想在面试中脱颖而出，欢迎联系我们。CSOAHelp 提供全面的面试辅导与代面服务，帮助您成功拿到梦寐以求的 Offer！

If you need more interview support or interview proxy practice, feel free to contact us. We offer comprehensive interview support services to help you successfully land a job at your dream company.