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Understanding Algorithms and Data Structures: Key Concepts in Computer Science

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This course provides an in-depth exploration of algorithms and data structures, emphasizing their critical role in computer science. Students will learn the definitions of data structures, algorithms, and abstract data types (ADTs), and how they relate to the implementation of programs. The course focuses on resource usage, particularly time complexity and space complexity, using asymptotic analysis. Key points include the importance of understanding how data is stored and manipulated within a computer system. Join us for enlightening discussions and practical applications.

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Understanding Algorithms and Data Structures: Key Concepts in Computer Science

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  1. CSCI 311 – Algortihms and Data Structures http://www.eg.bucknell.edu/~csci311 Steve Guattery Dana 335a (department office) x7-3828 guattery@bucknell.edu http://www.eg.bucknell.edu/~guattery

  2. This course does not have a lab, but it does have a recitation that meets Thursday afternoons. We will meet tomorrow. Assignment: Read Appendix A and Section 3.2 in the text.

  3. What is a data structure? “A data structure consists of a base storage method (e.g., an array) and one or more algorithms used to access or modify that data.” “A data structure is how information is stored in the computer; a data type is a data structure plus its operations.” Key point: Data structures determine how data is stored on a computer. They are part of an implementation.

  4. What is an algorithm? “A sequence of computational steps that transform the input to the output.” “A problem-solving method suitable for implementation as a computer program.” Key points: Algorithms are not (necessarily) implementations. They are often described in terms of mathematical objects (e.g., ordered array, tree, graph) that may or may not immediately correspond to a data structure.

  5. What is an abstract data type (ADT)? An ADT specifies the data and operations that will be used in a data type, but does not specify the implementation. ADTs serve as a bridge from an algorithmic description to an implementation using data structures.

  6. Process for creating a program: Real-world problem on real-world objects ↓ Mathematical representation of problem and objects + algorithm(s) ↓ Computer implementation on data structures

  7. The Big Question for This Course: Resource usage of algorithms and data structures. What resources do they use?

  8. Resources for algorithms and data structures: • Time (instructions/machine cycles) • Space (memory) • We will focus mainly on time.

  9. We want algorithmic comparisons to be: • independent of processor (abstract step) • independent of implementation (ignore start-up overhead and constants) • related to how the resource depends on problem size (asymptotic analysis)

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