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Software Engineering Job Interview – Full Mock Interview

freeCodeCamp.org・60 minutes read

Keith Galley conducts a mock software engineering interview with Kylie Ying focusing on object-oriented programming and dynamic programming. The interview assesses problem-solving abilities, data structure understanding, and coding skills through designing a Cloud reading application and detecting plagiarism using algorithms and dynamic programming.

Insights

Technical interviews for software engineering roles assess problem-solving skills, data structure and algorithm knowledge, and coding proficiency through real-world coding scenarios.
Object-oriented design and dynamic programming are crucial aspects of technical interviews, requiring candidates to demonstrate a deep understanding of these concepts to solve complex problems efficiently.

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Recent questions

What is the purpose of technical interviews for software engineering roles?
Technical interviews assess problem-solving ability, coding level, and understanding of data structures and algorithms for software engineering roles.
How is the design of an online Cloud reading application structured?
The design includes classes for books and libraries, managing active books, unique book IDs, and considerations for book content.
What approach is suggested to detect potential plagiarism in books?
Using dynamic programming to find the longest shared common section of text between two books is recommended to detect potential plagiarism.
How can the efficiency of dynamic programming solutions be optimized?
Memoization is recommended to avoid redundant calculations and optimize efficiency in dynamic programming solutions.
What advice is given for software engineering interviews?
During interviews, it's advised to ask questions, turn the interview into a conversation, start with a naive solution, optimize for efficiency, and implement the optimal solution to showcase problem-solving skills.

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Summary

00:00

Mock coding interview assesses problem-solving skills

Keith Galley conducts a mock full-length real-world coding technical interview with Kylie Ying for a software engineering role.
Object-oriented programming and dynamic programming are used to solve questions in the interview.
Technical interviews for software engineering roles involve working to a solution, optimizing it, and writing code or pseudocode on the spot.
The purpose of these interviews is to assess problem-solving ability, understanding of data structures and algorithms, and coding level.
The interview involves Keith Galley mock interviewing Kylie Ying, simulating a real software engineering interview.
CoderPad is used for the interview, allowing code sharing and collaboration.
The interview starts with 20 minutes of designing object-oriented structures and then moves to an algorithms question.
The problem involves designing an online Cloud reading application similar to Amazon Kindle for short stories.
Requirements include users having a library of books, setting an active book, remembering the user's last reading position, and displaying one page at a time.
The design involves classes for books and libraries, with considerations for book content, active book management, and unique book IDs.

18:02

Managing Books in Library System

The Library contains a collection of books and an active book, initially set as an empty dictionary and none, respectively.
To add a book, pass the title and content, create a new book with an ID, increment the ID counter, and add the book to the collection.
To remove a book based on its ID, use the delete function in Python to remove it from the collection in place.
Setting the active book is done based on the ID provided.
The reading application displays one page of text at a time.
To display a page, access the active book from the collection and call the display function.
Considerations for increasing font size include calculating characters per page and adjusting content indexing accordingly.
For multiple users sharing books, store book details in a SQL table with unique IDs for global identification.
To detect potential plagiarism, design an algorithm to find the two books with the longest shared common section of text.
A possible approach involves using pointers to compare substrings of the books for shared characters, aiming to identify the longest shared section efficiently.

37:20

"Optimizing substring search with dynamic programming"

The discussion revolves around finding the longest common substring between two sentences.
The proposed solution involves dynamic programming to optimize the process.
The approach includes defining subproblems and base cases to build up to the final solution.
A single-line recurrence expression is suggested to streamline the process.
Memoization is recommended to avoid redundant calculations and optimize efficiency.
The runtime complexity of the dynamic programming solution is discussed.
The application of the solution to a library of books to detect plagiarism is explored.
Criteria for identifying potential plagiarism cases, such as shared substrings, are outlined.
The interviewee demonstrates a thorough understanding of the problem and proposes practical solutions.
The interviewer provides feedback on the comprehensive coverage of both algorithmic and object-oriented design aspects.

57:42

Enhancing Object-Oriented Design and Algorithm Mastery

The interviewee discussed the need for further breakdown of classes in the object-oriented design, suggesting a separate display class for handling font sizes and characters per page.
They mentioned the challenge of understanding the structure of IDS and suggested a more robust system to avoid collisions, proposing the use of titles and authors for unique identification.
The interviewee appreciated the uniqueness of IDS to prevent collisions and suggested using titles and authors for identification.
In the algorithm section, the interviewee commended the interviewee for explaining thought processes and starting with a naive solution before refining it.
They highlighted the iterative approach in the algorithm section, starting with a naive solution and progressing towards a more optimal one.
The interviewee suggested potential improvements in the dynamic programming solution, such as considering punctuation and testing for edge cases.
They discussed the challenge of dynamic programming and the importance of practice in mastering such concepts.
The interviewee praised the interviewee for explaining their thought process and rebounding well when faced with challenging questions.
They emphasized the significance of testing in software engineering and suggested mentioning testing cases during interviews.
The interviewee proposed the idea of following up after an interview with solutions to questions that were not answered optimally, showcasing dedication and problem-solving skills.

01:12:21

Python: Pseudocode-like language for algorithm focus

Python is considered almost like pseudocode, making it easy to focus on algorithms rather than syntax. However, in a specific problem, the individual was too lazy to implement a certain part and had trouble with underlining, resorting to turning it into a comment. During interviews, it's advised to ask questions, turn the interview into a conversation to showcase teamwork skills, repeat questions to ensure understanding, start with a naive solution, then optimize for efficiency, and finally implement the optimal solution.

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