New DSA practice posts
What happened
Several fresh study posts surfaced: a specific Amazon SDE‑2 interview problem pointing to 'Time‑Based Key‑Value Store', an updated DSA primer with complexity notes and code snippets, and a curated 'top 50' problem list for interviews. ( ). Those resources bundle problem guidance across arrays, trees, graphs, DP and more—useful conduits for daily coding reps. (x.com)
Why it matters
One post ties an Amazon mid‑level interview question to the LeetCode problem "Time‑Based Key‑Value Store," which requires implementing set(key, value, timestamp) and get(key, timestamp) so the get operation returns the stored value whose timestamp is the largest one less than or equal to the query time. (x.com) (leetcode.com) A separate post flags an updated DSA primer that now annotates time and space costs and ships runnable code examples in common languages, making the notes easier to convert into practice runs and timed coding drills. (x.com) (dsaprimer.com) The standard approach to the time‑based key‑value problem stores, for each key, an ordered list of (timestamp, value) pairs and uses binary search — a method that repeatedly halves a sorted list to find a target — to find the largest timestamp not exceeding the query; that yields O(log m) search time where m is the number of entries for that key, while set usually appends in O(1) amortized time. (simplyleet.com) (leetcode.com) The curated "top 50" problem list referenced groups problems across arrays, trees, graphs and dynamic programming (DP, a technique that solves problems by combining solutions to overlapping subproblems), with entries that mirror common interview staples such as Two Sum and interval/graph traversal patterns found on LeetCode's top interview lists and community "top 50" repositories. (x.com) (leetcode.com) Community collections and GitHub sheets that mirror these posts (for example Striver’s A2Z sheet and several "Top‑50" GitHub repos) explicitly annotate pattern names (sliding window, two pointers, DFS/BFS, memoized DP) and often include complexity notes and language snippets, which makes matching a given interview prompt to the right pattern and complexity expectation faster during daily practice. (takeuforward.org) (github.com) References collected alongside these posts also surface example Amazon mid‑level (SDE II) question sets and candidate OA (online assessment) reports that include similar problems and input/output examples, which help validate that the time‑based key‑value pattern is being used to screen for correct handling of versioned data and efficient lookup under interview time limits. (github.com)
Key numbers
- Several fresh study posts surfaced: a specific Amazon SDE‑2 interview problem pointing to 'Time‑Based Key‑Value Store', an updated DSA primer with complexity notes and code snippets, and a curated 'top 50' problem list for interviews.
Quick answers
What happened in New DSA practice posts?
Several fresh study posts surfaced: a specific Amazon SDE‑2 interview problem pointing to 'Time‑Based Key‑Value Store', an updated DSA primer with complexity notes and code snippets, and a curated 'top 50' problem list for interviews. ( ). Those resources bundle problem guidance across arrays, trees, graphs, DP and more—useful conduits for daily coding reps. (x.com)
Why does New DSA practice posts matter?
One post ties an Amazon mid‑level interview question to the LeetCode problem "Time‑Based Key‑Value Store," which requires implementing set(key, value, timestamp) and get(key, timestamp) so the get operation returns the stored value whose timestamp is the largest one less than or equal to the query time. (x.com) (leetcode.com) A separate post flags an updated DSA primer that now annotates time and space costs and ships runnable code examples in common languages, making the notes easier to convert into practice runs and timed coding drills. (x.com) (dsaprimer.com) The standard approach to the time‑based key‑value problem stores, for each key, an ordered list of (timestamp, value) pairs and uses binary search — a method that repeatedly halves a sorted list to find a target — to find the largest timestamp not exceeding the query; that yields O(log m) search time where m is the number of entries for that key, while set usually appends in O(1) amortized time. (simplyleet.com) (leetcode.com) The curated "top 50" problem list referenced groups problems across arrays, trees, graphs and dynamic programming (DP, a technique that solves problems by combining solutions to overlapping subproblems), with entries that mirror common interview staples such as Two Sum and interval/graph traversal patterns found on LeetCode's top interview lists and community "top 50" repositories. (x.com) (leetcode.com) Community collections and GitHub sheets that mirror these posts (for example Striver’s A2Z sheet and several "Top‑50" GitHub repos) explicitly annotate pattern names (sliding window, two pointers, DFS/BFS, memoized DP) and often include complexity notes and language snippets, which makes matching a given interview prompt to the right pattern and complexity expectation faster during daily practice. (takeuforward.org) (github.com) References collected alongside these posts also surface example Amazon mid‑level (SDE II) question sets and candidate OA (online assessment) reports that include similar problems and input/output examples, which help validate that the time‑based key‑value pattern is being used to screen for correct handling of versioned data and efficient lookup under interview time limits. (github.com)
