Applied System Analysis

Master 2021/2022

Type: Compulsory course (System and Software Engineering)

Area of studies: Software Engineering

Delivered by: School of Software Engineering

Where: Faculty of Computer Science

When: 1 year, 1-4 module

Mode of studies: offline

Open to: students of one campus

Instructors: Konstantin Y. Degtyarev

Master’s programme: Software and Systems Engineering

Language: English

ECTS credits: 5

Contact hours: 66

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Abstract

The course 'Applied System Analysis' is offered to students of the Master's degree Program 'System and Software Engineering' (area code 09.04.04) in the School of Software Engineering, Faculty of Computer Science of the National Research University Higher School of Economics. The course is a part of MS curriculum pool of compulsory courses (1st year, Base Clause – General Scientific disciplines of the academic year’s curriculum, M.1 – General Courses of Specialization). It is a four-module course (semester A quartile 1 thru semester B quartile 4). In general, system analysis (SA) can be considered as a set of approaches, methods, and techniques aimed at understanding peculiarities of the problematic situation faced by its owner(s), and the development of improving interventions into the problem based on the options (alternatives) generated. As a rule, the causes of the problem are subjective, and they are related to one person or group of persons, his/her (their) perception of reality. Therefore, Applied System Analysis (ASA), i.e. the application of SA as a universal approach to solving problems in different fields of human activity (engineering, management, economics, to name a few), is based on the concepts of the problem, system, model, alternatives and monitoring. Classification of problems as well-defined (very rarely occurring in practice), weakly defined, and ill-defined ones (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.

Learning Objectives

The main objective of the course 'Applied System Analysis' 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, (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. In particular, the vast field of software engineering (SE) is concerned with such problems and their solutions that cannot always be fully understood and explained clearly, but nevertheless, we can claim that software engineers deal with systems, real physical products.

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

Introduction and overview of the course (in particular, comments concerning grading policy applied and course-related control activities).
Origins of systems analysis (SA). Notions of system, core definitions of a system (G.Klir, M.Mesarovic, et al.), 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?
Classification of systems (problems); systems, problems, and mental models, and problem-solving. SPE-pyramid (approach to grasp system’s structure), cognitive maps (B.Kosko, C.Eden), causal schemes (Causal Loop Diagrams / CLD), definition, and basic features – how to construct CLD, and what can we “see” in CLD (our perception)?
Systems and complexity. The role of models (modeling) in SA. Models of systems. The problematic situation, problem as a system, its analysis, and modeling.
Systems thinking. Hard and soft methodologies in the analysis of systems. Operations research, optimization problems (hard models in System Analysis / SA)
Structural analysis in systems studying, basics of Q-analysis (polyhedral dynamics) – notions of simplex and complex, structural vector, structural complexity, eccentricities of simplices. SA as a methodology of problem-solving, thinking in «big picture» terms while analyzing the problem.
Presentation and discussion of the course' homework (details and requirements for the homework are explained in advance)
Hypotheses in problem solving, use of heuristic methods in problem-solving (viz. informal analysis); who are the stakeholders? Stakeholder analysis and its importance.
Work with experts, Delphi method. Multi-criteria decision analysis (MCDA). Main steps in MCDM, decision-making models. AHP (and its core points), TOPSIS, VIKOR methods, and their discussion. System Analysis of goals.

Assessment Elements

Final Course Examination (FE)
Oral presentation of the work (HW) done + questions/answers session… The overall grade is obtained according to the formula that considers all assessments of passed (completed) control elements; there is no separate exam, an online session (in MS Teams), or offline sessions (everything depends upon the epidemiological situation) to discuss the final results
Homework (HW)
Students are free to choose a problem for consideration based on their own interests and preferences. Written report (paper) following IEEE, Elsevier, or Springer LNCS publ. template (offered to choose from). HW covers the task that is related to the field of IT / Software Engineering – we should not deviate from the program’s focus.
Course Examination (CE)
Computer-based test or written test (duration – 70 to 80 min.). If a student misses CE because of some valid reason, the situation has to be discussed with representatives (managers) of the Departmental (Program’s) Office of Studies.
Computer-based Quizzes (CB_Q1 and CB_Q2)
NOTE: The form and content of the Quizzes may vary depending on the peculiarities of their implementation and the type of questions to be included.
Computer-based quizzes (CB_Q3 and CB_Q4)
NOTE: The form and content of the Quizzes may vary depending on the peculiarities of their implementation and the type of questions to be included.

Interim Assessment

2021/2022 2nd module
[LINEAR FORMULA] Progress (interim) grades are made up of the following components: Course Examination (CE) – end of Module 2 (Semester A Quartile 2), computer-based quiz 1 (CB_Q1), and computer-based quiz 2 (CB_Q2). CE also implies the arrangement of computer-based testing (answers to questions offered supplied with short comments). The subject area covered by tests embraces those course’ topics that are discussed during both lectures and seminars up to the date announced. The computer-based test may contain both single-choice and multiple-choice questions; the grade for the test is specified by the test program automatically (short comments to answers given must be provided). If a student misses CE because of some valid reason (only this case is covered by the document!), the situation has to be discussed with representatives (managers) of the Departmental (Program’s) Office of Studies. The course examination (CE) is assessed on the ten-point scale (usual rounding takes place after the weighted sum’s calculation is completed). The interim assessment is cumulative, i.e. it takes into account all grades obtained by the end of Module 2 (examination week period). Please, pay attention to the fact that the missed CE is eligible for retaking during the re-examination period (January-February 2022). Thus, the interim grade is calculated as a weighted sum of individual components mentioned above, i.e. O(IA_Mod_2) = 0.2*O(CE) + 0.05*O(CB_Q1) + 0.05*O(CB_Q2), no blocking. Max result (end of Module 2) is 2.4, which stands for the grade "excellent" (8 out of 10) on the 5-point scale ('A' grade (viz. very good) on the ECTS scale) - see also https://www.hse.ru/studyspravka/Scale/. This grade (please, pay attention to the fact that it is the only grade corresponding to the "excellent" level) implies a deep understanding of the subject (topics under consideration) within the course' syllabus and active independent work related to the study of recommended material, its wise structuring.
2021/2022 4th module
[LINEAR FORMULA] Homework assignment (HW) – 2nd-3rd modules (Sem. A Quartile 2 – Sem. B Quartile 3) is prepared by students individually (x1) or in groups by two (x2, at most), herewith a group prepares single electronic (PDF format solely) report, which is of the form of a scientific paper (5 to 8 pages in x1 case, and 8 to 11 pages in x2 case) in IEEE or other well-established formats (following IEEE, Elsevier or Springer LNCS publ. format template – selected links will be provided at course’ webpages in LMS / in MS Teams); see also https://www.overleaf.com/gallery/tagged/academic-journal). Students are free to choose a problem to consider based on their own interests and preferences (linked to fields of IT / Software Engineering – we should not deviate from the program’s focus.). The work is started (appr. in the second part of December 2021. All reports must be submitted in the electronic form to the instructor through HSE Learning Management System (LMS) / OneDrive storage for consideration before the date day_x, which is set (last decade of March 2022 - the very beginning of April 2022 as a rough estimate) and announced at the beginning of Module 3. All reports are checked and graded by the instructor on the ten-point scale by the end of the 4th Module as the latest, and O(HW_Report) gives the assessment for the 4th Module of the course. Please, be informed in advance that failure to comply with specified deadline day_x for submission of the report leads automatically to the reduction of O(HW_Report) by 0.3 points for each delayed day. The conditions for students should be the same, regardless of the subsequent date of the HW presentation. Finally, the overall course grade on the ten-point scale is obtained as O(Total) = O(IA_Mod_2) + 0.1*O(CB_Q3) + 0.1*O(CB_Q4) + 0.3*O(HW_Report) + 0.2*O(FE) (usual rounding takes place after calculations are done, no blocking), where O(HW_Report) is a grade for a text of the HW report (paper) as such subject to reduction if any – see note above, O(CB_Q3) and O(CB_Q4) are grades for quizzes #3 and #4, correspondingly, whereas O(FE) is a grade obtained for the presentation (of the HW) done – questions related to topics covered by the course and submitted HW report are asked to students. The resultant grade O(Total) >= 4 (after rounding) means successful completion of the course (grade "Pass"), while grade of 3 or lower means unsuccessful result (grade "Fail"). The final grade for the course is drawn from the cumulative grade (in fact, the presentation of homework acts as an oral exam covering the course material). Pay attention to the fact that grades 9 ("excellent - exceeds expectations" / A+ grade (very good with distinction) on the ECTS scale) or 10 ("excellent - significantly exceeds expectations" / A++ grade (very good with excellence) on the ECTS scale) are given to students who take the initiative to go beyond the course' syllabus, for example, study additional materials (in-depth and well-organized independent work associated with structuring of additional material - in particular, from the electronic resources of the HSE library) and create on their basis a product (conduct qualitative research with obtaining interpretable results, which can be the basis for preparing a publication or represent a virtually complete text for presentation at a conference/publication) that is potentially useful to the instructor, other students, and being regarded as significant; reveal critical (creative) thinking that goes beyond excellent level (of originality of thinking); perform tasks of advanced complexity; offer an innovative solution that demonstrates a higher level of mastery of the stateed educational results on particular element(s) of control or more than excellent mastery of the entire course content (the material under consideration).

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

Authors

DEGTYAREV KONSTANTIN YUREVICH

Course Syllabus