Models, algorithms, recurrences, summations, growth rates. Probabilistic tools, upper and lower bounds; worst-case and average-case analysis, amortized analysis, dynamization. Comparison-based algorithms: search, selection, sorting, hashing. Information extraction algorithms (graphs, databases).
DurationModels, algorithms, recurrences, summations, growth rates. Probabilistic tools, upper and lower bounds; worst-case and average-case analysis, amortized analysis, dynamization.
Comparison-based algorithms: search, selection, sorting, hashing. Information extraction algorithms (graphs, databases). Graphs algorithms: spanning trees, shortest paths, connectivity, depth-first search, breadth-first search.
A leader in interdisciplinary research and education
As the first school of its kind in the United States, the Indiana University Luddy School of Informatics, Computing, and Engineering is an innovator in a fast-paced and dynamic field. Our school on the IUPUI campus integrates computing, social science, and information systems design in unique ways.
More than 4,500 students—including over 1,400 at Luddy IUPUI—study informatics on IU campuses. Our top-notch programs and highly regarded faculty prepare them for the power and possibilities in computing and information technology.
The analysis and design of computer algorithms and their underlying data structures. Analysis of the timing and efficiency of algorithms. Study of lists, stacks, queues, trees, backtracking, searching, sorting and recursion.
In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments.
The Data Structures & Algorithms course begins with a review of some important Java techniques and nuances in programming. The course requires some prior knowledge of Java and object-oriented programming, but not in data structures or algorithms.
Algorithms and data structures are the essential frameworks for solving almost any computer engineering problem.
Survey of advanced algorithms and data structures such as heaps and heapsort, quicksort, red-black trees, B-trees, hash tables, graph algorithms, divide and conquer algorithms, dynamic programming, and greedy algorithms. Methods for proving correctness and asymptotic analysis.
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