1. Data Structures and Algorithms

(core curriculum 2-th year of studies, semester 3, 2 hours/week lecture + 2 hours/week lab, Romanian)

Fundamental Data Structures (Data types, Abstract Data Types-ADT, Objects): Algorithms (Definition, Analyze of Algorithms, Asymptotic Notation, Algorithms Profiling): Sorting (Internal sorting, External sorting); Strings (ADT String, Implementation, String Search); Recursivity (Recursive Algorithms, Recursive Data Structures); Lists (ADT List, Implementation Techniques, Special Lists: Circular Lists, Double Linked Lists, Stacks, Queues. Multilists, Generalized Lists); Tables (ADT Table, Implementation Techniques, Hash Tables)

2. Design and Analyze of Algorithms

(core curriculum 2-rd year of studies, semester 4, 2 hours/week lecture + 2 hours/week lab,, Romanian)

Advanced Data Structures. Trees (ADT Tree, Implementation Techniques, Binary Trees, Binary Search Trees, Trie Trees, Balanced Trees, AVL Trees, Optimal Search Trees, Huffman Trees, B-Trees, Binary B-Trees); Sets (ADT Set, Advanced Implementations Techniques, Merge&Find Sets, Merge&Split Sets); Graphs (ADT Graph, Implementation Techniques, Undirected Graphs, Fundamental Traversal Techniques, Spanning Trees, Graphs and Connections, Articulation Points, Biconnected Components); Weighted Graphs, Minimum Cost Spanning Trees (Prim, Kruskal, Priority Search Algorithms); Directed Graphs (Dijkstra, Floyd, Warshall Algorithms), Directed Acyclic Graphs; Strong Components; Network Flows; Graph Matching.

3. Structured Development for Real-Time Systems

(optional, 5-th year of studies, semester 9, 3 hours/week lecture + 1 hours/week lab + 1 hour/week project, Romanian)

Real-Time Systems. Definition; Real-Time Modeling Issues; RT Modeling Heuristics; Modeling Transformations; Control Transformations (Modeling and Specifying); Data Transformations (Modeling and Specifying); Stored Data (Modeling and Specifying); Organizing the Model; Essential Model Heuristics; Defining System Context; Modeling External Events; Deriving the Behavioral Model; Implementation Modeling Heuristics; Real-Time UML; Requirement Analysis of RTS; Defining the Object Structure; Defining the Object Behavior; Architectural Design; Mechanistic Design; Detailed Design

4. Software Process Management

(master, PhD curriculum 6-th year of studies 3 hours/week lecture + 1 hours/week proj, English)

Part1: Introduction (SPM definition, objectives, processes, activities, tasks, software developing process, project life cycles, management process); Technologies for SW products development (MS Technology, Oracle Technology, Rational-Rose Technology, RUP Technology, Siemens development technology (P04901, P04903))
Part 2:SW Project Management. Fundamentals (terms, fundamental rules, the contract, development cycle); The Definition Phase (Problem analysis, Problem Specification, Analysts); SW Size Estimation Methods (Wide-band Delphy Method, Fuzzy-Logic Method, Standard Component method, Function Point Method, Proxy-based Estimation); SW Costs Estimation Methods (Analogy, Expert Judgement, Top Down, Bottom-Up, Parkinson Method); Cost Estimation Models(EE Model, LOC-FP Model, Parametric Models: COCOMO 81, COCOMCO II, PRICE S, SEER-SEM Model); The Project Plan: Overview, Phase Plan, Organization Plan,Test Plan, Change Control Plan, Documentation Plan, Training Plan, Review and Reporting Plan, Installation and Operation Plan, Resources and Deliverables Plan, Project Plan Index; Planning Tools; Acceptance Criteria; The Design Phase (The Design Specification,The Designers, Design Guidelines, Design tools); The Programming Phase:Conventional Organization, Team Organization, Change Control, Management Activities during Programming Phase, Levels of Management; System Test Phase, System Testing, CustomerTraining; The Acceptance Phase;The Installation and Operation Phase; Special Considerations: Big projects, Small Projects, Writing Proposals Guide; Case Study.

Last modification: January 2014


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