Software Projects Management

Course: Software engineering

Structural unit: Faculty of Computer Science and Cybernetics

Title
Software Projects Management
Code
ОК.10
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
4
Learning outcomes
LO.01 Know and systemically apply in software design domain analysis and modeling methods, information requirements elicitation and input data collection methods. LO.02 Justify the choice of software requirements engineering, engineer, analyse, classify and prioritize requirements. LO.03 Know and apply fundamental concepts and methodologies of information processes modeling. LO.04 Estimate and choose methods and models for software systems development, deployment, maintenance and their management during all stages of software process. LO.05 Develop and estimate software design strategies; justify, analyze and estimate previously made design decision from the final software product quality perspective. LO.09 Know and apply modern professional standards, codes and regulations for software engineering. LO.10 Be able to make organizational and management decisions under uncertainty.
Form of study
Distance form
Prerequisites and co-requisites
1) know perspective: software systems life cycle models; software systems design approaches; procedural and object-oriented programming concepts; software, organizational and technological instruments for software systems competitive quality ensuring and managing within their development process; discrete optimization methods; mathematical statistics methods; 2) can: adopt software system development methodology and implementation language(s) appropriate for its purpose under available resources; create software systems artifacts within the methodology adopted with appropriate quality for stakeholders within procedural and object-oriented programming paradigms; solve linear and Boolean programming problems; calculate data sample standardized statistics;
Course content
The purpose is Students’ mastering actual technologies for effective software projects performing and training them as successful project managers, team members, project officers. After learning the discipline Students shall: a) know:  basics and methods for particular projects goals, both engineering improvement and stuff development, projects owner strategic goals sustain coordination;  (agile) software project and project portfolio life cycle Models of a (as to PMBoK 6.7 ed., IPMA ICB v.4, DSTU ISO 215XX, 10006, PRINCE2TM);  (agile) software project efficiency and effectiveness basic criteria and methods for its effective management based on their grounded assessments;  approaches for effective software projects management system engineering. б) can:  choose software project management technologies meeting its purpose under current conditions and manage it with timely uncertainties, risks and problems handling by means of dedicated tools such as MS Project, Bitrix, Trello;  effectively balance heterogeneous software projects within the system to manage them.
Recommended or required reading and other learning resources/tools
1. Rudnichenko M.D. Navchalniy posibnik z discipliny «Suchasna teoriya upravlinnya IT-proektamy» dla studentiv specialnosti 126 Informaciyni systemy i tehnologii / Uporyad.: M.D.Rudnichenko, N.O.Shibaeva. – Odesa, ONPU, 2020. – 132 s. 2. Yakimchyk V.S. Zasoby planuvannia ta realizacii IT-proektiv: rekomendacii do vyvchennya discipliny: navch. posib. dla studentiv specialnosti 122 / V.S.Yakimchyk –Kyiv, KPI im.Igorya Sikorskogo, 2018. – 52 s. 3. Kon M. Ocinyuvannia і planuvannia v Agile / M.Kon – Fabula, 2019. – 356 s. 4. Reynvoter Dg.G. Yak pasty kotiv / Dg.G. Reynvoter – Fabula, 2020. – 320 s 5. Wiegers K. Software Requirements Essentials. Core Practices for Successful Business Analysis / K.Wiegers, C. Hokanson – Addison-Wesley, 2023. – 208 p.
Planned learning activities and teaching methods
Lectures, individual work, recommended literature learning, laboratory classes.
Assessment methods and criteria
Intermediate assessment: Maximal available points: 60 points. 1. Module test No.1: RN 1.1, RN 1.2, RN 1.3, RN 2.2, RN 4.2– 20/12 points. 2.Module test No.2: RN 1.3, RN 1.4, RN 1.5, RN 4.2 – 20/12 points. 3. Laboratory class No.1: RN3.1, RN3.2, RN4.1, RN 4.2 – 4 бали/2 бали. 4. Laboratory class №2: RN3.2, RN4.1, RN4.2 – 4 бали/2 бали. 5. Laboratory class №3: RN2.1, RN3.1, RN3.2, RN4.1, RN4.2 – 4 бали/2 бали. 6. Laboratory class №4: RN2.1, RN3.1, RN3.2, RN4.1, RN4.2 – 3 бали/1 бал. 7. Laboratory class №5: RN2.1, RN3.1, RN3.2, RN4.1, RN4.2 – 5 балів/3 бали. Final assessment (in the form of exam): Maximal available points: 40 points. Learning results to be assessed: RN 1.1, RN 1.2, RN 1.3, RN 1.4, RN 1.5, RN 2.1, RN 2.2. The form of exam: writing. Task types are 4 writing tasks (2 tests, research and theoretical question).
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Olha O. Slabospytska
Department of Intelligent Software Systems
Faculty of Computer Science and Cybernetics

Departments

The following departments are involved in teaching the above discipline

Department of Intelligent Software Systems
Faculty of Computer Science and Cybernetics