CSCI 202 - Data Structures

1. Demonstrate with proficiency basic procedural and object-oriented concepts of computer programming.
2. Demonstrate use of a variety of data structures, including:
   1. Stacks and queues
   2. Sets and maps
   3. Linked lists,
   4. Binary trees, AVL trees, and B-Trees,
   5. Hash tables and graphs
3. Demonstrate fundamental computing algorithms, including:
   1. Sorting
   2. Sequential and binary searches
   3. Insertion, deletion, and balancing trees
   4. Hash tables and collision-avoidance
   5. Directed, undirected and weighted graphs
   6. In-order, depth- and breadth-first graph traversals.
   7. Recursive traversal of various data structures.
   8. Regular expressions and Regex
   9. Demonstrate basic algorithmic analysis:
   10. Analyze the performances of an algorithm with various input sizes
   11. Compare upper and average complexity bounds
   12. Differentiate best, average and worst-case behaviors
   13. Describe algorithm complexity in notation (big O, little O, omega and theta)
   14. Contrast standard complexity classes
   15. Determine empirical measurements of performance
   16. Evaluate time and space tradeoffs in algorithms
   17. Determine whether a recursive or iterative solution is most appropriate for a problem
   18. Identify a variety of real-world problems in computer science solvable using various data structures
4. Demonstrate the effective use of software engineering principles and practices:
   1. Compare various data structures for a given problem
   2. Investigate factors other than computational efficiency that influence the choice of algorithms.
   3. Apply consistent documentation and program style standards that contribute to the readability and maintainability of software.
   4. Conduct peer code reviews (focused on common coding errors) on program components.
   5. Differentiate between program validation and verification.
   6. Investigate potential vulnerabilities in provided programming code.
   7. Use software tools to evaluate, test, and debug programs.
5. Demonstrate the principles of secure programming and design:
   1. Investigate security vulnerabilities in various data structures
   2. Implement programs that properly handle exceptions and error conditions.
   3. Describe key terms in cryptology, including cryptography, cryptanalysis, cipher, cryptographic algorithm, and public key infrastructure.
   4. Use a cipher to encrypt plaintext into ciphertext.
   5. Describe the use of cryptographic hash functions for authentication and data integrity.
   6. Contrast symmetric and asymmetric encryption in relation to securing electronic communications and transactions.
   7. Describe security concerns in designing applications for use over networks.
   8. Illustrate secure connectivity among networked applications.
6. Analyze the goals of parallelism and concurrency.
   1. Describe various programming constructs for synchronization.
   2. Contrast low-level data races with higher level races.
   3. Investigate methods, such as mutual exclusion, used to avoid race conditions.
   4. Discuss security vulnerabilities related to parallelism and concurrency.
7. Discuss the history of programming languages, and be able to compare languages for features and applicability.
8. Discuss the concept of a virtual machine and the use of intermediate languages, and/or linked libraries.
9. Discuss interpreters, compilers, and the machine-dependent and -independent aspects of translation.

• Algorithmic analysis
• Interpreters
• Artificial Intelligence
• Linked libraries
• Basic procedural concepts
• Linked Lists
• Compliers
• Object-oriented programming
• Cryptography
• Recursion
• Data Structures
• Regular Expressions
• Expert Systems
• Security
• Fundamental computing algorithms
• Software engineering principles
• Graphs
• Trees
• History of programming languages
• Virtual machine
• Intermediate languages

 
Course Addendum - Syllabus (Click to expand)