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Introduction to the Theory of Computing 2

Bevezetés a számításelméletbe 2
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
Bevezetés a számításelméletbe 2
Introduction to the Theory of Computing 2
Subject code BMEVISZAA04
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 2 2 0
type (linked/independent) derived course
Assessment type vizsga
Credits 5
Subject coordinator
DR. Wiener Gábor
position: egyetemi docens
Responsible department
Számítástudományi és Információelméleti Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website http://cs.bme.hu/bsz2
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme

1) Basic notions of graph theory: graph, simple graph, degree of a vertex, subgraph, induced subgraph, walk, trail, tour, path, cycle, isomorphism.

2) Connected graph, connected component, tree, spanning tree. Existence of a spanning tree.

3) Storing graphs: adjacency list, adjacency matrix. Directed graphs. Efficiency of graph algorithms. Deciding connectivity, finding a shortest path (with unit edge lengths): Breadth First Search.

4) Computing a minimum weight spanning tree: Kruskal's algorithm.

5) Euleri trails and tours, necessary and sufficient conditions on their existence. Hamiltonian paths and cycles. Necessary conditions on their existence: the maximum number of components after deleting k nodes. Sufficient conditions: theorems of Dirac and Ore.

6) Bipartite graphs, their characterization with odd cycles. Chromatic number. Greedy coloring, upper bound on the chromatic number in terms of the maximum degree. Maximum clique size, its relation to the chromatic number, Zykov's construction.

7) Optimal coloring of interval graphs. Matching, vertex cover, independent set, edge cover. Relation between the sizes of the maximum matching and the minimum vertex cover. Gallai's theorems.

8) Computing a maximum matching in a bipartite graph, the augmenting path algorithm, its optimality. Kőnig's theorem on the equality between the sizes of a maximum matching and a minimum vertex cover.

9) Edge-chromatic number, its relation to the maximum degree, Vizing's theorem.Kőnig's theorem on the edge coloring of bipartite graphs.

10) The maximum flow problem: the notions of network, flow, overall value of a flow. The augmenting path algorithm for computing a maximum flow. The notion of an st-cut of a network, and its capacity.

11) Ford-Fulkerson theorem, Edmonds- Karp theorem. The integer valued maximum flow problem. The problem of edge-disjoint s-t paths, Menger's corresponding theorem.

12) The problem of edge-disjoint paths in undirected graphs, the problems of vertex-disjoint paths in directed and undirected graphs, Menger's corresponding theorems. The notions of k-connectivity and k-edge-connectivity, Menger's corresponding theorems.

13) The shortest path problem with real edge length in directed graphs, the Bellman-Ford algorithm.

14) Summary and review.

The goal of the subject is to acquire the fundamental mathematical knowledge (in the area of linear algebra and number theory) necessary for software engineering studies.  Students successfully completing the course will be able to: (K3) understand and apply the notions and the knowledge covered by the course;(K3) individually solve practical problems related to the material of the course;(K2) apply the algorithms covered by the course;(K2) prove certain theorems covered by the course;(K3) during their further studies, identify situations where fields of knowledge covered by the course are applicable and apply them successfully.

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

2 hours of lecture and 2 hours of problem solving each week. The lecture introduces new theory and the role of practice classes is to deepen the acquired knowledge by applying it on problems. Since practice classes closely follow the material of corresponding lectures, a thorough knowledge of the material covered by the lectures is expected from the students. The common work done on practice classes (including homeworks) is an inherent part of the learning process. Lectures in most cases build on the material of previous weeks, it is typically impossible to follow the new material without the preliminary knowledge provided by them.

Tanulástámogató anyagok

Online források
Online course book: http://cs.bme.hu/bsz2/jegyzet/. (in Hungarian); The midterms and scoring guides of the last decade can also be found on the website of the course. 

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
High school level mathematics.
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
High school level mathematics.
General rules
Requirements: Signature: There will be 1 midterm during the semester. In order to acquire the signature, the result of the midterm must be at least 24 points out of 60. Final exam: In order to take the final exam students must have a valid signature. The final exam is oral. The final score is based on the score of the midterm (40%) and the score of the oral exam (60%).  The final grade based on the final score is as follows. 0-39,9: fail (1), 40-54,9: pass (2), 55-69,9: satisfactory (3), 70-84,9: good (4), 85-100: excellent (5).   Pre-exam is not allowed. Additional possibilities: One retake of the midterm is possible free of charge in order to acquire the signature or to improve on the score of a succesful midterm. One further retake is possible in order to acquire the signature for an official fee.
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses

Not provided.

Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.