Master
2026/2027
Applied System Analysis
ID 1120747
Type:
Compulsory course (System and Software Engineering)
Delivered by:
School of Software Engineering
Where:
Faculty of Computer Science
When:
1 year, 2, 3 module
Open to:
students of all HSE University campuses
Instructors:
Konstantin Y. Degtyarev
Language:
English
ECTS credits:
6
Contact hours:
66
Course Syllabus
Abstract
(certain parts of the course including supplementary materials are delivered in English, however, Russian language is also in active use in the course to enhance comprehension and understanding of the content) ||||| The course 'Applied System Analysis' (рус. Прикладной системный анализ) is offered to students of the Master's degree Program 'System and Software Engineering' (area code 09.04.04) in the Department of Software Engineering, Faculty of Computer Science at the National Research University Higher School of Economics. The course is a part of MS curriculum pool of compulsory courses (1st year, Base Clause – Module 'Major'). It is a two-module course (semester A quartile 2 thru semester B quartile 3). When it comes to the course materials, it can be noted that the system analysis (SA) in a broad sense can be considered as a set of approaches, methods, and techniques aimed at understanding peculiarities of the problematic situations faced by its owner(s), and the development of improving interventions into the problems based on the options (alternatives) generated in the course of the analysis performed. As a rule, the causes of the problem are subjective (this is related to the way people gradually come to understand things), and they are connected with one person or group of persons (stakeholders), his/her (their) perception of the reality. Therefore, Applied System Analysis (ASA), i.e. the application of SA as a universal approach to solving problems in different (applied) fields of human activity (engineering, management, economics, to name a few - almost everywhere), is based on the concepts of the problem, system, model(s), suggested alternatives and the choice of the 'best' alternative for the implementation (decision-making stage). Classification of problems as well-defined (very rarely occurring in practice), weakly defined, and ill-defined/ill-structured ones (the latter are more realistic and constantly arising in practice) requires the use of different models (approaches) in each particular situation. This fact has led to the formation of so-called 'hard' and 'soft' system methodologies (SSM) based on formal and informal approaches within the framework of system analysis, respectively. The aspects of such approaches are discussed within the framework of this course.
Learning Objectives
- The main objective of the course 'Applied System Analysis' (рус. Прикладной системный анализ) is to present, examine and discuss with students fundamentals and principles of both System Analysis and Systems Thinking that emerged in response to (1) a steadily growing complexity of problems arising in various areas of day-to-day and professional human activity, and (2) a necessity to structure problems and to present (viz. to develop mental/visual or formal model(s)) and to assess emerged situations complemented with a search for acceptable solutions (problem-solving) based on the analysis and the elaboration of alternatives for action (improving interventions in a given problematic situation). In particular, the vast field of software engineering (SE) is concerned with such problems and their solutions that cannot be fully understood and explained clearly from the very beginning, but nevertheless, we can claim that software engineers deal with systems, real products (refer to the course' Abstract).
Expected Learning Outcomes
- To formulate clearly potential role, attractive aspects / disputable points of SA approach use when solving problems arising in the present professional activity; to demonstrate the competence to credibly defend viewpoint(s).
- To know basic definitions related to Q-analysis (polyhedral dynamics) procedure.
- To know different definitions of the system; to understand the importance of systems thinking in solving engineering problems (and not only).
- To know the origins of systems analysis (SA) and history of SA emergence, basic concepts SA is grounded on.
- To know the specifics of causal loop diagrams (CLD as models), their use in systems studying; to be able to identify in CLD balancing (B) and reinforcing (R) loops that determine the dynamics of systems (problems).
- To understand heuristic approaches to problem solving (means-ends analysis, hill climbing, approach by analogies); to be able to apply them in solving problems.
- To understand how to draw conclusions concerning the peculiarities of system’s structure on the basis of analysis’ results obtained.
- To understand peculiarities of hard and soft approaches (methodologies) in systems modelling.
- To understand problem structuring approaches and to know how to improve insight (to make progress in analysis) into ill-structured problems.
- To understand the details and to carry out steps relating to the calculation of the structural vector of complex К (system’s model) and eccentricities of simplices.
- To understand the details of multi-criteria decision analysis (MCDA) approaches covered in the course and apply them while solving the learning tasks.
- To understand the importance of a systemic approach applied to complex problems arising within various human activities and to engineered systems, classification of problems (well-structured, unstructured and ill-structured).
- To understand the layered approach to systems thinking, the need to gradually move from the level of observed events to the identification of patterns and to further understanding of the system’s (problem’s) structure.
- To understand the particulars of working with experts, using Delphi method.
- To understand the purpose and relevance of a stakeholder analysis; to know the ways to perform a stakeholder analysis.
Course Contents
- Введение и обзор курса. Что понимается под системным анализом (СА). Какова роль прилагательного 'прикладной' (англ. Applied) в названии дисциплины? Понятие системы и основные определения системы. Модели и моделирование в анализе проблемных ситуаций.Отсутствуют
- Systems thinking, problem-solving, and systems engineering. Stages of SA. System approach and system paradigm. Problem and system – is there any relationship between them? What is a system in problem-solving? System analysis in professional activity.None
- Classification of systems (problems); systems, problems, and mental models, and problem-solving. Systems and complexity. The role of models (modeling) in SA. Problem as a system, its analysis, and modeling. Systems Mapping (русс. системное картирование)
- Discussion of Causal Loop Diagrams (CLD). Hard and soft methodologies in the analysis of systems. Operations research, hard models in System Analysis/SA, modeling and analysis of structural aspects of systems (Q-analysis)Additionally, the following title is recommended to students (free access source): Pete Barbrook-Johnson, Alexandra S. Penn. Systems Mapping. How to build and use causal models of systems, https://link.springer.com/book/10.1007/978-3-031-01919-7, Palgrave Macmillan, 2022, 186 p. (the book "... explores a range of new and older systems mapping methods focused on representing causal relationships in systems")
- Soft models in system analysis. SPE-pyramid (approach to grasp system’s structure), cognitive maps (e.g. B.Kosko, C.Eden, et al.), causal schemes (Causal Loop Diagrams / CLD), definition, and basic features.
- Detailed presentation of Q-analysis procedure - transition from simple binary matrix to simplicial complex, analysis of results (structural aspects of the system under modeling). Rich pictures, PQR formula, CATWOE analysis. Specificities of SSM.are provided during lecture hours and in seminars
- Classification of stakeholders, influence-importance matrix (IIM), Olander’s model (matrix). Who are the stakeholders? Stakeholder analysis and its importance.
- SWOT-analysis and its use in the field of software engineering. Quantitative modifications of SWOT-analysis and their use in tackling practical problems
- Work with experts. Multi-criteria decision analysis (MCDA). Main steps in MCDM, decision-making models. MCDM – managerial and engineering levels.
- Analytic Hierarchy Process (AHP) and TOPSIS approaches. Computational steps and comments. Hypotheses in problem solving, use of heuristic methods in problem-solving (viz. informal analysis).Approaches discussed form the core of one of the Homeworks in the course
Assessment Elements
- Контрольная работа 1 (Q1) в форме домашнего заданияДанное домашнее задание посвящена рассмотрению диаграмм причинных связей применительно к моделированию выбранной проблемной ситуации, связанной с профессиональной деятельностью студентов
- Презентация результатов домашнего задания (Q4)презентация (до 10-ти минут) результатов выполненной работы Q3 (выполняется по группам из 2-х человек) + сессия "вопрос-ответ", касающаяся теоретического материала и деталей выполненной данной группой работы
- Контрольная работа 4 (Q4) в форме домашнего задания (текст подготовленного отчета)контрольная работа, охватывающая соотв. материал дисциплины (выполняется в виде домашнего задания с последующей презентацией выполненной работы). Текст отчета и короткая презентация оцениваются отдельно. Данная контрольная работа выполняется в группах из 2-х студентов
- Контрольная работа 3 (Q3) в форме домашнего заданиявсе детали задания обсуждаются со студентами на занятии, предшествующем дате проведения контрольной работы (выполнения домашнего задания)
- Контрольная работа 2 (Q2) в форме домашнего заданияконтрольная работа, охватывающая соотв. материал дисциплины (детали домашнего задания обсуждаются во время часов семинарских занятий)
Interim Assessment
- 2026/2027 3rd module0.2 * Контрольная работа 4 (Q4) в форме домашнего задания (текст подготовленного отчета) + 0.15 * Контрольная работа 1 (Q1) в форме домашнего задания + 0.2 * Презентация результатов домашнего задания (Q4) + 0.2 * Контрольная работа 2 (Q2) в форме домашнего задания + 0.25 * Контрольная работа 3 (Q3) в форме домашнего задания
Bibliography
Recommended Core Bibliography
- Gorod, A., Gandhi, S. J., Sauser, B., White, B. E., & Ireland, V. (2014). Case Studies in System of Systems, Enterprise Systems, and Complex Systems Engineering. Boca Raton: CRC Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=802172
- Jaap Schaveling, & Bill Bryan. (2018). Making Better Decisions Using Systems Thinking. Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.spr.sprbok.978.3.319.63880.5
- Системный анализ, оптимизация и принятие решений : учеб. пособие для вузов, Козлов, В. Н., 2010
- Теория и методы принятия решений, а также Хроника событий в Волшебных Странах : учебник для вузов, Ларичев, О. И., 2002
- Теория систем и системный анализ : учебник для вузов, Волкова, В. Н., 2010
Recommended Additional Bibliography
- Системный анализ : учебник для вузов, Антонов, А. В., 2006