feat(curriculum): add dynamic programming quiz to js v9 cert (#65995)

2026-05-28 18:26:54 +00:00 · 2026-03-01 18:39:40 +01:00
parent 95e293d23a
commit 787922295f
4 changed files with 252 additions and 1 deletions
@@ -3329,6 +3329,12 @@
          "In this lab, you will implement a function that converts an adjacency list representation of a graph into an adjacency matrix representation."
        ]
      },
+      "quiz-dynamic-programming-js": {
+        "title": "Dynamic Programming Quiz",
+        "intro": [
+          "Test what you've learned about dynamic programming in JavaScript with this quiz."
+        ]
+      },
      "lecture-understanding-functional-programming": {
        "title": "Understanding Functional Programming",
        "intro": [
@@ -0,0 +1,234 @@
+---
+id: 699a068cfe9bb7bccf2b7ec0
+title: Dynamic Programming Quiz
+challengeType: 8
+dashedName: quiz-dynamic-programming-js
+---
+
+# --description--
+
+To pass the quiz, you must correctly answer at least 9 of the 10 questions below.
+
+# --quizzes--
+
+## --quiz--
+
+### --question--
+
+#### --text--
+
+What are the two essential properties that must be present in a problem for dynamic programming to be an effective solution approach?
+
+#### --distractors--
+
+Fast execution time and minimal memory usage
+
+---
+
+Recursion capability and iterative loops
+
+---
+
+Sequential processing and parallel computation
+
+#### --answer--
+
+Overlapping subproblems and optimal substructure
+
+### --question--
+
+#### --text--
+
+What is the primary difference between the memoization and tabulation approaches in dynamic programming?
+
+#### --distractors--
+
+Memoization uses hash tables while tabulation uses arrays, making it more efficient.
+
+---
+
+Memoization is faster but uses more memory and CPU cycles than tabulation.
+
+---
+
+Memoization can only solve simpler problems than tabulation.
+
+#### --answer--
+
+Memoization is a top-down approach using recursion, while tabulation is a bottom-up approach using iteration.
+
+### --question--
+
+#### --text--
+
+Why do naive recursive solutions to dynamic programming problems typically have exponential time complexity?
+
+#### --distractors--
+
+Because they use exponential amounts of memory to store variables.
+
+---
+
+Because they require sorting data in exponential time.
+
+---
+
+Because they must check all possible permutations of the input.
+
+#### --answer--
+
+Because each recursive call branches multiple times, causing the same subproblems to be recalculated repeatedly.
+
+### --question--
+
+#### --text--
+
+What does optimal substructure mean in the context of dynamic programming?
+
+#### --distractors--
+
+The algorithm must use the most efficient data structure available.
+
+---
+
+The solution must minimize both time and space complexity simultaneously.
+
+---
+
+The problem must have a unique, single optimal solution.
+
+#### --answer--
+
+The optimal solution can be constructed from optimal solutions to its subproblems.
+
+### --question--
+
+#### --text--
+
+When implementing memoization, what happens when a function is called with arguments that have already been computed?
+
+#### --distractors--
+
+The function recalculates the result to ensure accuracy.
+
+---
+
+The function averages the old and new results for better precision.
+
+---
+
+An error is thrown because duplicate calculations are not allowed.
+
+#### --answer--
+
+The cached result is returned immediately without recomputation.
+
+### --question--
+
+#### --text--
+
+What is a key advantage of using tabulation instead of memoization?
+
+#### --distractors--
+
+Tabulation always requires less memory than memoization.
+
+---
+
+Tabulation can solve a broader class of problems.
+
+---
+
+Tabulation is always easier to implement and understand.
+
+#### --answer--
+
+Tabulation avoids recursion overhead and provides predictable sequential execution.
+
+### --question--
+
+#### --text--
+
+In a bottom-up dynamic programming solution, why are base cases initialized first?
+
+#### --distractors--
+
+To allocate memory for the data structure efficiently.
+
+---
+
+To prevent infinite loops in the algorithm.
+
+---
+
+To improve the time complexity of the algorithm.
+
+#### --answer--
+
+To provide foundational values upon which all larger subproblems are built.
+
+### --question--
+
+#### --text--
+
+How does dynamic programming transform the time complexity of problems that exhibit overlapping subproblems?
+
+#### --distractors--
+
+From polynomial to logarithmic by dividing the problem efficiently.
+
+---
+
+From quadratic to linear by optimizing loop structures.
+
+---
+
+From linear to constant by using hash tables.
+
+#### --answer--
+
+From exponential to polynomial by storing and reusing subproblem solutions.
+
+### --question--
+
+#### --text--
+
+What trade-off does dynamic programming typically make to achieve better time complexity?
+
+#### --distractors--
+
+It sacrifices code readability for faster execution.
+
+---
+
+It requires more complex algorithms that are harder to maintain.
+
+---
+
+It limits the size of problems that can be solved.
+
+#### --answer--
+
+It uses additional space to store intermediate results.
+
+### --question--
+
+#### --text--
+
+In which scenario would dynamic programming NOT be the appropriate algorithmic approach?
+
+#### --distractors--
+
+When the problem requires finding an optimal solution.
+
+---
+
+When the problem can be broken into smaller subproblems.
+
+---
+
+When space complexity must be minimized.
+
+#### --answer--
+
+When subproblems are independent and don't overlap.
@@ -0,0 +1,11 @@
+{
+  "name": "Dynamic Programming Quiz",
+  "isUpcomingChange": true,
+  "blockLabel": "quiz",
+  "blockLayout": "link",
+  "dashedName": "quiz-dynamic-programming-js",
+  "helpCategory": "JavaScript",
+  "challengeOrder": [
+    { "id": "699a068cfe9bb7bccf2b7ec0", "title": "Dynamic Programming Quiz" }
+  ]
+}
@@ -318,7 +318,7 @@
        {
          "dashedName": "dynamic-programming",
          "comingSoon": true,
-          "blocks": []
+          "blocks": ["quiz-dynamic-programming-js"]
        },
        {
          "dashedName": "functional-programming",