Risk management in software project scheduling using bayesian networks

MINISTRY OF EDUCATION AND TRAINING 
HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY 
Nguyen Ngoc Tuan 
RISK MANAGEMENT IN SOFTWARE PROJECT SCHEDULING 
USING BAYESIAN NETWORKS 
PhD DISSERTATION ON SOFTWARE ENGINEERING 
Hanoi – 2021 
MINISTRY OF EDUCATION AND TRAINING 
HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY 
Nguyen Ngoc Tuan 
RISK MANAGEMENT IN SOFTWARE PROJECT SCHEDULING 
USING BAYESIAN NETWORKS 
Major: Software Engineering 
Code No.: 9480103 
PhD DISSERTATION ON SOFTWARE ENGINEERING 
SUPERVISORS: 
1. Assoc. Prof. Huynh Quyet Thang 
2. Dr. Vu Thi Huong Giang 
Hanoi – 2021 
 1 
DECLARATION: 
I certify that this thesis and the work presented in it are products of my 
own work, and that any ideas or quotations from other people work published 
or otherwise, are fully acknowledged in accordance with the standard referen-
cing practices of the discipline. 
This thesis has not been submitted for any degree or other purposes. 
 Hanoi, February 19, 2021 
 Nguyễn Ngọc Tuấn 
SUPERVISORS: 
Assoc. Prof. Huỳnh Quyết Thắng Dr. Vũ Thị Hương Giang 
 2 
Acknowledgements 
First of all, I would like to express my sincere gratitude to my first supervisor 
Associate Professor Huynh Quyet Thang for his invaluable guidance and support 
throughout my research. Professor Thang has supported me all the way, all the time. 
It is his patience that keeps me always committed to doing this research and 
reaching the end of PhD student period. I am also very grateful to my second 
supervisor Dr. Vu Thi Huong Giang whose bright hints and expertise has been 
always helpful to me. 
My special thanks go to Ms. Vo Thi Huong, Ms. Bui Thi Quynh Nga, Mr. 
Tran Trung Hieu, Mr. Tran The Anh, Mr. Tran Bao Ngoc and Mr. Cao Manh 
Quyen, who were master and bachelor students at School of ICT, Hanoi University 
of Science and Technology and helped me with building the tools as well as testing 
our models. 
I am also indebted to Dr. Nguyen Thanh Nam (former CEO of FPT and 
former President of FSOFT), Mr. Luu Quoc Tuan (Tinh Van Outsourcing Jsc.), Mr. 
Ngo Quang Vinh (Evizi), Mr. Nguyen Huy Binh (FIS) who provide helpful real 
software project data and valuable expertise judgments on the data. 
Finally, my greatest appreciation is to my family, especially to my wife Tran 
Thi Bich Ngoc. Without their love, patience and sacrifice, this achievement would 
never be possible. 
 3 
Summary 
Software project management is an art and science of planning and leading 
software projects. In software industry, project managers mostly rely on their 
experience and skills to manage their projects and lack of scientific tools to support 
them. 
Risk management is a crucial part of software project management that helps 
prevent software disasters. In this research, risks are defined as uncertain events or 
conditions that, if they occur, they would have a bad impact on one or more 
software project outcomes (cost, time, quality). Identifying and dealing with risks or 
uncertainty in early phases of software development life cycle would lessen long-
term cost and enhance the chance of the project success. The most important part of 
risk management is risk analysis which assesses the risks and their impact to the 
outputs of the software project. To overcome subjective assessment based on 
development team’s experience, the team needs a quantitative risk analysis method. 
Software project scheduling is one part of software project planning. Since in 
practice, most software projects are over-budget and behind schedule, software 
project scheduling needs to be taken into careful consideration. We come up with 
the following questions: 
 How to schedule software projects better? 
 How to better manage risks in software projects? 
 How to quantitatively analyse risks? 
 Some researchers say that Bayesian Networks can be used to quantify uncertain 
factors in (general) project scheduling and improve project risk assessment and 
analysis. Our research is aimed at taking those advantages of Bayesian Networks 
into software project scheduling by addressing common software project features. 
The research provides answers to the above questions with probabilistic 
approaches and tools to assess the impacts of risk factors on software project 
scheduling; proposing list of common risk factors and Bayesian Network model of 
these risk factors; and proposing advanced scheduling methods based on 
incorporating Bayesian Networks into popular scheduling techniques such as CPM, 
PERT or agile iteration scheduling etc. Bayesian Networks help quantify the 
factors, and hence help better manage them as well as enhancing the predictability 
of things happen in the project. 
 4 
This research first takes a literature review on (general) project planning issues, 
project scheduling techniques, project scheduling tools, uncertainty and risk 
characteristics in software projects, risk management processes, project risk analysis 
in order to apply state-of-the-art techniques into software projects (Chapter 1). 
After that, Bayesian Networks are applied in building and experimenting risk 
factors in software project scheduling. BRI (Bayes Risk-Impact) algorithm is 
proposed to assess risk factors’ impact on software scheduling (Section 2.1). The 
first set of risk factors with 5 risk factors are examined using a probabilistic own-
built tool CKDY to analyse risks in software project scheduling (Section 2.2). 
The research proposes an advanced algorithm for agile iteration scheduling 
using Bayesian Networks. The advantages of this method are providing a schedule 
and the probability of finishing agile iteration on time (Section 3.1). In addition, the 
author goes further with a more refined list of 19 risk factors in software scheduling 
and uses them in software scheduling methods. The research also incorporates 
Bayesian Network with CPM and PERT scheduling techniques in traditional 
software projects together with the Bayesian Networks of common risk factors 
(Section 3.2 and Section 3.3). The list of 19 risk factors in agile software 
development is also examined in agile iteration scheduling (Section 3.4). The 
experimental results show that our models are reliable and our approaches have 
practical implications, i.e. we can take advantage of Bayesian Networks in 
modelling and quantifying risks/uncertainty in software projects. 
 5 
How to read this report? 
The author highly recommends that you read this report from beginning to the 
end. However, if at any point you want to look at specific important pieces of 
information, the following guide could be helpful: 
 To get the motivation, the overview of related work, the objectives, the 
scope, the hypothesis and methodology of this research, please go to the 
Introduction section. 
 To get an overview of software project scheduling and risk management in 
software project scheduling, please go to Sections 1.1, 1.2 and 1.3. 
 To get an overview of Bayesian Networks, please go to Section 1.4. 
 To get details on main contributions and key findings of the research, please 
read Chapter 2 and Chapter 3. 
 To get information on common risk factors in software project scheduling, 
you can have a look at Section 2.3. 
 The Chapter 2 is about building tools and doing experiments on applying 
Bayesian Networks into risk management in software project planning 
(Section 2.1) and some key risk factors (Section 2.2). 
 The Chapter 3 is about incorporating Bayesian Networks and common risk 
factors into software project scheduling techniques such as CPM (Section 
3.2), PERT (Section 3.3), Agile software development scheduling (Section 
3.4). 
 To get to know the conclusions, the limitations as well as the further research 
of the study in this PhD thesis, please read the Conclusion section. 
 6 
Content 
Acknowledgements ............................................................................................... 2 
Summary.. ................................................................................................................ 3 
How to read this report? ...................................................................................... 5 
List of symbols and abbreviations ................................................................. 10 
List of tables.......................................................................................................... 12 
List of figures ........................................................................................................ 13 
Introduction ........................................................................................................... 15 
Motivation.................................................................................................................................... 15 
Related work .............................................................................................................................. 18 
Research scope ......................................................................................................................... 20 
Research objectives .................................................................................................................. 20 
Scientific and realistic meaning ............................................................................................... 21 
Research hypothesis and methodology ................................................................................. 21 
Expected results ........................................................................................................................ 21 
Structure of the thesis ............................................................................................................... 22 
Chapter 1. Overview of software project scheduling and risk 
management.......................................................................................................... 23 
1.1. Software project management and software project scheduling ................................ 23 
1.1.1. Software project management ................................................................................. 23 
1.1.2. Software project scheduling ...................................................................................... 25 
1.2. Software project scheduling methods and techniques ................................................ 26 
1.2.1. Overview ...................................................................................................................... 26 
1.2.2. Traditional scheduling methods and techniques ................................................... 26 
1.2.3. Agile software project scheduling ............................................................................ 31 
1.3. Risk management in software project scheduling ........................................................ 33 
 7 
1.3.1. Overview of project risk management ..................................................................... 33 
1.3.2. Project risk analysis ................................................................................................... 35 
1.3.3. Unknown risks ............................................................................................................. 36 
1.3.4. Risk aspects in software project scheduling .......................................................... 36 
1.4. Bayesian Networks ............................................................................................................ 37 
1.4.1. Probabilistic approach using Bayesian Networks .................................................. 37 
1.4.2. Bayesian Inference..................................................................................................... 39 
1.4.3. Bayesian Networks and project risk management ................................................ 40 
1.5. Chapter remarks ................................................................................................................ 42 
Chapter 2. Common risk factors and experiments on Bayesian 
Networks and software project scheduling .................................................. 44 
2.1. Application of Bayesian Networks into schedule risk management in software 
project .......................................................................................................................................... 44 
2.1.1. Common risk factors in software project management ........................................ 45 
2.1.2. Bayesian Networks of risk factors ............................................................................ 46 
2.1.3. Risk impact calculation .............................................................................................. 58 
2.1.4. Bayesian Risk Impact algorithm ............................................................................... 61 
2.1.5. Tool and experiments ................................................................................................ 61 
2.1.6. Conclusion and contribution ..................................................................................... 66 
2.2. Experiments on common risk factors ............................................................................. 67 
2.2.1. Discovering the top ranked risk factors ................................................................... 68 
2.2.2. Tool CKDY ................................................................................................................... 71 
2.2.3. Experiments and analysis ......................................................................................... 73 
2.2.4. Conclusion and contribution ..................................................................................... 77 
2.3. Proposed common risk factors in software project scheduling................................... 78 
2.3.1. The 19 common risk factors in traditional software project .................................. 78 
2.3.2. The 19 common risk factors in agile software project .......................................... 80 
2.4. Chapter remarks ................................................................................................................ 82 
 8 
Chapter 3. Incorporation of Bayesian Networks into software project 
scheduling techniques ....................................................................................... 83 
3.1. Applying Bayesian Networks into specific software project development ................ 83 
3.1.1. Introduction .................................................................................................................. 83 
3.1.2. Optimized Agile iteration scheduling ....................................................................... 84 
3.1.3. Optimization model for Agile software iteration ........... ... onal Journal of Project Management, 21, 
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 130 
Index 
A 
agile iteration scheduling ............................. 3, 4, 83, 94 
agile software development 4, 21, 22, 26, 31, 33, 35, 93, 
94, 119, 128, 129 
B 
Bayesian Networks .... 3, 4, 5, 18, 22, 37, 40, 44, 46, 83, 
94, 104, 114, 118, 119, 120, 121, 123, 124, 125 
BNs18, 19, 21, 22, 38, 40, 41, 42, 43, 44, 46, 58, 67, 69, 
71, 76, 77, 80, 82, 83, 84, 87, 88, 94, 95, 99, 100, 
102, 103, 104, 107, 109, 114, 115, 117, 118 
BRI .................................... 4, 10, 22, 44, 61, 66, 82, 119 
C 
CKDY ..... 4, 19, 22, 44, 67, 68, 71, 76, 77, 82, 119, 128 
CPM .... 3, 4, 5, 10, 17, 18, 20, 22, 26, 27, 28, 29, 43, 67, 
77, 94, 95, 98, 99, 100, 103, 104, 113, 114, 118, 119 
M 
makespan ................................................................... 91 
P 
PERT ... 3, 4, 5, 10, 11, 17, 18, 19, 20, 22, 26, 28, 29, 43, 
67, 77, 103, 104, 105, 106, 108, 112, 114, 118, 119, 
123 
project management . 3, 5, 16, 17, 18, 21, 23, 24, 26, 28, 
30, 33, 36, 42, 44, 45, 46, 63, 64, 65, 70, 125, 129 
Q 
quantitative risk analysis ............................ 3, 16, 17, 35 
R 
risk analysis ............ 3, 4, 16, 17, 30, 35, 36, 40, 41, 125 
risk factors 3, 4, 5, 18, 19, 20, 21, 22, 30, 42, 43, 44, 45, 
46, 47, 52, 58, 60, 61, 62, 63, 65, 66, 67, 68, 69, 70, 
71, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 94, 95, 
96, 98, 102, 103, 104, 105, 106, 107, 114, 117, 118, 
119, 120, 128 
Risk management.................................... 3, 33, 121, 128 
risks .. 3, 4, 15, 16, 17, 18, 19, 20, 21, 22, 33, 34, 35, 36, 
37, 41, 42, 44, 58, 61, 62, 65, 66, 67, 71, 72, 77, 78, 
80, 82, 83, 84, 87, 94, 95, 97, 99, 100, 103, 104, 105, 
106, 107, 114, 117, 119, 120 
S 
Scrum .................................... 31, 33, 115, 116, 126, 129 
Software project management ........................... 3, 23, 24 
Software project scheduling ........................ 3, 25, 26, 84 
T 
The RBCPM Method............................................... 98 
The RBCPM Model ................................................. 95 
the tool BAIS ................................ 90, 92, 115, 116, 118 
The tool RBCPM .................................................... 99 
The tool RBPERT ................................................ 108 
U 
uncertainty .... 3, 4, 16, 17, 18, 21, 26, 28, 29, 30, 31, 33, 
34, 35, 36, 40, 41, 42, 44, 67, 83, 84, 87, 94, 100, 
103, 104, 114, 118, 120, 123