An Analysis of the Application of Randomized Selection Algorithms in Solving Computational Problems

dc.contributor.advisorHerendi, Tamás
dc.contributor.authorWang, Yuqi
dc.contributor.departmentDE--Informatikai Kar
dc.date.accessioned2025-06-26T20:47:45Z
dc.date.available2025-06-26T20:47:45Z
dc.date.created2025-04-17
dc.description.abstractThis study investigates the computational behavior of randomized selection algorithms in median finding and partial sorting, with a focus on time complexity, stability, and worst-case probability. Through mathematical analysis, it examines the performance of QuickSelect and Median-of-Medians across different data distributions, and quantifies the impact of random pivot selection. Experimental comparisons between Randomized QuickSort and deterministic HeapSort explore how input characteristics affect worst-case behavior. The findings aim to guide algorithm selection for large-scale data processing by clarifying the performance trade-offs of randomized methods.
dc.description.courseProgramtervező informatikus
dc.description.degreeBSc/BA
dc.format.extent42
dc.identifier.urihttps://hdl.handle.net/2437/394772
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectrandomized selection algorithms
dc.subjectrandomized algorithms
dc.subject.dspaceInformatics::Computer Science
dc.titleAn Analysis of the Application of Randomized Selection Algorithms in Solving Computational Problems
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