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 CSE 373: Data Structures & Algorithms, Spring 2015
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Final Study Guide, CSE 373 Spring 2015

Exam Policies

  • Closed book
  • Closed notes
  • No calculators or other electronic devices
  • Begins promptly at 2:30 and ends promptly at 4:20
  • Bring your student ID to the exam

Topics Covered

The final exam is cumulative but more weight (probably roughly two thirds) will be given to topics covered since the midterm. So, review all topics covered in lecture or homework assignments except a few topics clearly marked as optional (notably AVL deletion and the details of the proof for the lower bound for comparison sorting).

For advanced topics like dynamic programming, backtracking, p vs. np, np-completeness, you DO need to know the BASIC ideas about how they work. I will not ask you to write any code or do any proofs on these topics, but you SHOULD understand the main idea behind how they work.

Exam Format and Sample Exams

Our exam will consist of various types of short-answer questions. You may be asked to write or read Java code or pseudocode. It will be similar in style to the midterm.

Below we have repeated the sample midterms from the study guide for the midterm. Because our final exam is cumulative, it makes sense to provide questions from old midterm exams. In addition, we have provided a few additional sample questions, but we do not have as many available.

Please understand these caveats:

  • Topics covered on these exams may not be the exact same topics covered on our exam; please see above for the topics covered on our exam. We did not study B trees, leftist heaps, or skew heaps.
  • The sample exams are provided as a study guide, not as any guarantee of the format of our actual exam in terms of length or type of questions.

Sample exams:

Midterm 1:

Midterm 2: Final:

Some additional questions   unsolved   solved

Note:

We encourage students to post their own questions for others on the discussion board or send the staff suggestions

Additional Study Suggestions

  • Re-work problems from lecture and homework.
  • Do additional problems from the textbook.
  • Practice analysis of algorithms.


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