Algorithms and Data Structures DSBA 2026/2027: различия между версиями
Nkmakarov (обсуждение | вклад) Нет описания правки |
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== Lecture Materials == | == Lecture Materials == | ||
''' | '''Sep 5''' | ||
* | * Exact string matching, naive algorithm, the preprocessing approach, Z-algorithm, the simplest linear-time algorithm | ||
* | * The Knuth-Morris-Pratt algorithm | ||
''Bibliography'': | ''Bibliography'': Gusfield, ch. 1, 2, 3 | ||
''' | '''Sep 12''' | ||
* | * The Boyer-Moore algorithm | ||
* | * The Aho-Corasick algorithm | ||
''Bibliography'': Gusfield, ch. 2, 3 | |||
'''Sep 19''' | |||
* Suffix trees: basic definition, naive algorithm to build | |||
* Suffix trees: Ukkonen's algorithm | |||
* Suffix trees applications: generalized suffix tree, the longest common substring for two strings, matching statistics | |||
''Bibliography'': Gusfield, ch. 5, 6, 7 | |||
== List of topics for exam == | == List of topics for exam == | ||
Текущая версия от 15:56, 19 сентября 2026
About
This page contains basic information for the course Algorithms and Data Structures 2 in 2026/2027 academic year at Bachelor’s Programme in Data Science and Business Analytics (DSBA).
Teachers and assistants
| Group | 251 | 252 | 253 | 254 | 255 | 256 |
|---|---|---|---|---|---|---|
| Lecturer | Nikita Makarov | |||||
| Seminar Instructor | Vladimir Kurenkov | Anton Shnipov | Anna Pronina | Simon Kondakov | ||
| Teaching Assistant | Leonid Pavlov | Maria Sudarikova | Dmitriy Gusev | Anastasia Bronnikova | Maria Samoylova | Yana Pavlova |
| Lecturer Assistant | Yana Arseneva | |||||
Grading
You may find your grades.
Formula
Final Grade = E * 0.4 + HW * 0.2 + Q * 0.2 + S * 0.2
- E - exam grade: rational number [0, 10] = sum of the grade for the oral and written parts, out of 5 each
- HW - homework grade: rational number [0, 10]
- Q - lecture quizzes grade: rational number [0, 10]
- S - seminar practice grade: rational number [0, 10]
rounding: each element in the formulae is rounded up
Plagiarism policy
If plagiarism is detected, the assessment element will be assigned a score of 0.
If the student is suspected of preparing the task not on his own, the teacher has the right to initiate additional verification or defense of this particular assessment element. Then such an assessment element will be graded based on the additional verification or the defense.
Home assignments
| Contest | Deadline | Topic |
|---|---|---|
Lectures
Lectures are held on Saturday, 14:40-17:40.
Lecture Materials
Sep 5
- Exact string matching, naive algorithm, the preprocessing approach, Z-algorithm, the simplest linear-time algorithm
- The Knuth-Morris-Pratt algorithm
Bibliography: Gusfield, ch. 1, 2, 3
Sep 12
- The Boyer-Moore algorithm
- The Aho-Corasick algorithm
Bibliography: Gusfield, ch. 2, 3
Sep 19
- Suffix trees: basic definition, naive algorithm to build
- Suffix trees: Ukkonen's algorithm
- Suffix trees applications: generalized suffix tree, the longest common substring for two strings, matching statistics
Bibliography: Gusfield, ch. 5, 6, 7
List of topics for exam
- [тема 1]
- [тема 2]
- [тема 3]