Hironori Washizaki, "SWEBOK Guide and Software Services Engineering Education," 2025 IEEE Symposium on Services and Software Engineering Education (part of IEEE SERVICES 2025), July 11th, Helsinki

1. SWEBOK Guide and Software Services
Engineering Education
SERVICES, SSE 2025 July 11th, Helsinki
Hironori Washizaki, IEEE Computer Society President (Waseda University)

2. Waseda University, Tokyo, Japan
• A top institution of higher education
• 50,000 students in 13 undergraduate and 21
postgraduate schools
• Founded in 1882 by Shigenobu Okuma, former
Prime Minister of Japan
• Strong alumni network of over 660,000
members: 8 prime ministers of Japan; 3 prime
ministers of Korea; important figures of Japanese
literature (incl. Haruki Murakami); founders of
leading companies, incl. Fast Retailing (UNIQLO),
Sony, Samsung, Ito En, Lotte, CJ Group, POSCO
2
Japanese University Life https://www.youtube.com/watch?v=qjTqeejCWY0
• Has hosted many international software
engineering and computing conferences
– SPLC 2013, IEEE ICST 2017, IEEE COMPSAC 2018
(partially), ACM VRST 2018, ICIAM 2023, IEEE
VCIP 2024, IEEE CSEE&T 2023
– Strong software engineering team: Prof.
Hironori Washizaki, Prof. Tomoji Kishi, and Prof.
Naoyasu Ubayashi

3. 375,000+
Community Members
1031
Global Chapters
157
Countries with Computer
Society Members
For over 75 years, the Computer Society has
empowered the people who advance technology by
delivering resources and solutions that computing
students and professionals need to achieve goals at
all stages of their careers.
3
• Engage more students and
early career professionals
• Engage more industry
individuals and organizations
• Lead the way in new technical
areas
Goals
• Empower and diversify
volunteer base
• Nimbleness in execution
• Diversity and inclusion
Themes
3

4. Agenda
• SWEBOK Guide evolution
• Emerging areas/topics and educational implication
• BOK comparison: SWEBOK and Software Services Engineering BOKs
4

5. What Is Software Engineering?
• IEEE Std. 610.12-1990 Glossary of Software
Engineering Terminology and ISO/IEC/IEEE
Systems and Software Engineering Vocabulary
(SEVOCAB) defines software engineering as
“the application of a systematic, disciplined,
quantifiable approach to the development,
operation, and maintenance of software; that
is, the application of engineering to software.”
5

6. Does software engineering form a
legitimate profession?
6

7. Legitimation of Professional Authority
Professional’s judgment and
advice are oriented toward
a set of substantive values
7
Paul Starr, “The Social Transformation of American Medicine,” Basic Books, 1982.
Knowledge and competence of
the professional have been
validated by a community
Consensually validated
knowledge and competence rest
on rational, scientific grounds
7

8. Towards a Body of Knowledge
Activities (and
practices)
Body of
Knowledge
Islands of
Knowledge
8
Every profession is based on a body of knowledge (BOK),
which is a collection of knowledge items or areas generally
agreed to be essential to understanding a particular subject.

9. Knowledge Area
Topic Topic
Reference
Material
Body of Knowledge Skills Competencies Jobs / Roles
SWEBOK
Software Engineering Professional Certifications
SWECOM
EITBOK
Learning courses
9
Guide to the Software Engineering Body of Knowledge (SWEBOK)
https://www.computer.org/education/bodies-of-knowledge/software-engineering
• Guiding researchers and practitioners to identify and have
common understanding on “generally-accepted-knowledge”
in software engineering
• Foundations for certifications and educational curriculum
• ‘01 v1, ‘04 v2, ‘05 ISO adoption, ‘14 v3, ’24 v4 released!
H. Washizaki, eds., “Guide to the Software Engineering Body of Knowledge (SWEBOK Guide), Version 4.0,” IEEE Computer Society, 2024
9

10. Mainframe
70’s –
Early 80’s
Late 80’s -
Early 90’s
Late 90’s -
Early 00’s
Late 00’s -
Early 10’s
PC,
Client &
server
Internet
Ubiquitous
computing
Late 10’s -
Early 20’s
IoT,
Big data,
AI
Structured
programming
Waterfall
Formalization
Design
Program
generation
Maturity
Management
Object-oriented
Req. eng.
Modeling
Verification
Reuse
Model-driven
Product-line
Global & open
Value-based
Systems eng.
Agile
Iterative &
incremental
DevOps
Empirical
Data-driven
Continuous
SE and IoT
SE and AI
SWEBOK V1
SWEBOK V2
SWEBOK V3
SWEBOK V4
1
10

11. SWEBOK Guide evolution from V3 to V4
• Modern engineering, practice update, BOK grows and recently developed areas
Requirements
Design
Construction
Testing
Maintenance
Configuration Management
Engineering Management
Process
Models and Methods
Quality
Professional Practice
Economics
Computing Foundations
Mathematical Foundations
Engineering Foundations
Requirements
Architecture
Design
Construction
Testing
Operations
Maintenance
Configuration Management
Engineering Management
Process
Models and Methods
Quality
Security
Professional Practice
Economics
Computing Foundations
Mathematical Foundations
Engineering Foundations
V3 V4
Agile,
DevOps
AI for
SE, SE
for AI
H. Washizaki, eds., “Guide to the Software Engineering Body of Knowledge (SWEBOK Guide), Version 4.0,” IEEE Computer Society, 2024
Editor:
H. Washizaki
KA editors:
A. Ihara,
S. Ogata,
N. Yoshioka,
S. Munetoh,
K. Shintani,
E. Hayashiguchi
and 15+ experts
11

12. IEEE CS Technology Prediction Team (Chair: Dejan Milojicic) https://www.computer.org/resources/2025-top-technology-predictions
IEEE CS Technology Prediction
Team (Chair: Dejan Milojicic)

13. Mainframe
70’s –
Early 80’s
Late 80’s -
Early 90’s
Late 90’s -
Early 00’s
Late 00’s -
Early 10’s
PC,
Client &
server
Internet
Ubiquitous
computing
Late 10’s -
Early 20’s
IoT,
Big data,
AI
GenAI, FM,
Autonomous,
Quantum,
Continuum
Late 20’s – 30’s
Structured
programming
Waterfall
Formalization
Design
Program
generation
Maturity
Management
Object-oriented
Req. eng.
Modeling
Verification
Reuse
Model-driven
Product-line
Global & open
Value-based
Systems eng.
Agile
Iterative &
incremental
DevOps
Empirical
Data-driven
Continuous
SE and IoT
SE and AI
SE and GenAI,
Quantum,
Sustainability
Autonomous
and Continuum
AI-assisted
DevOps/OpsDev
SWEBOK V1
SWEBOK V2
SWEBOK V3
SWEBOK V4
13
Partially adopted from “The Trailer of the ACM 2030 Roadmap for Software Engineering”

14. Agenda
• SWEBOK Guide evolution
• Emerging areas/topics and educational implication
• BOK comparison: SWEBOK and Software Services Engineering BOKs
14

15. New KA:
Software Architecture
15
15

16. Architecture: Educational implication and services
• Impact on higher education
• Things formerly taught abstractly can now be taught
practically
• Deal with larger systems than ever before and need exposure
to the underlying fundamental principles and practices of the
discipline
• Impact on professional training
• Importance as today’s cyber-physical systems are pervasive
• Demands for agile, just in-time solutions accelerate the need
to “get things right” early and often
• Practitioners depend upon knowledge of fundamental
principles to survive
• SSE education
• Service-oriented architecture (SOA) has been well
addressed.
• Learning contents can be updated to cover all areas, incl.
fundamentals, description, process, and evaluation.
• “Challenges in creating environments for SOA learning” incl.
understanding business conditions, using infrastructure,
integrating real-world applications [Lopez+07]
16
16
N. López, et al., “Challenges in creating environments for SOA learning,” International
Workshop on Systems Development in SOA Environments (SDSOA’07)

17. New KA:
Software Security
17

18. Software security: Educational implication and services
• Higher education
• Security fundamentals
• Basic security engineering techniques
aligned with the development life
cycle
• Professional training
• Available practical security solutions,
including security tools and patterns
• Domain-specific security techniques
• Security management
• SSE education
• Security in software services needs to
be addressed.
• Other domain specific security would
be related: container, cloud, IoT, and
AI/machine-learning.
User
id
name
ProtectionObject
id
name
* *
Authorization_rule
Right
access_type
predicate
copy_flag
checkRights
Role
id
name
*
*
MemberOf
Name: Role-Based Access Control (RBAC)
Problem: How do we assign rights to people based on
their functions or tasks?
Solution: Assign users to roles and give rights to these
roles so they can perform their tasks.
Related pattern: Authorization, ...
18
18
Li-Chiou Chen, et al. “Teaching Web Security Using Portable Virtual Labs,”
2011 IEEE 11th International Conference on Advanced Learning Technologies

19. New KA:
Operations
19
19

20. Operations: Educational implication and services
• Higher education
• Importance of operations in the era of
continuous software engineering
• Fundamentals and practice operation basics
and tools, particularly DevOps practices,
through exercise and project-based learning
• Professional training
• Entire picture of operations as an integral part
of system and software life cycle processes
• Modern infrastructure practices such as Agile
Infrastructure and Infrastructure as Code (IaC),
as well as practical considerations, related
standards, and tools such as containers and
virtualization
• SSE education
• DevOps with “continuous engineering”
automation tools for software services
engineering needs to be addressed.
20
20

21. Enhanced concerns: Agile and DevOps
• Higher education
• Impact on all KAs
• Fit the current scenario: fast-moving and
changing times, full of uncertainty.
• Paradigm shifts rather than just a new set of
practices
• Together with other approaches to develop
critical thinking and decision-making
• Professional training
• DevOps affects decision-making at all levels of the
software engineering process and KAs
• Agile impacts both the engineering and the
management level.
• SSE education
• Agile/DevOps are vital for software services
engineering.
21
To Do Doing Done
Securing …
Product
Technical Debt …
Development Deploy & operation
Test & verification Monitoring
Dev Ops

22. Additional topic: AI and software engineering
• Limitations and challenges
• Uncertain and stochastic behavior
• Necessity of sufficiently labeled, structured datasets
• AI for SE
• Building high-quality software systems by replicating human
developers’ behavior
• Ranging over almost all development stages
• SE for AI
• Different from traditional software since the rules and
system behavior of AI systems are inferred from data
• Need for particular support of SE for AI
• Documenting practices as patterns
22
Software
engineering
AI
AI for SE SE for AI
Hironori Washizaki, Foutse Khomh, Yann-Gael Gueheneuc, Hironori Takeuchi, Naotake Natori, Takuo Doi, Satoshi Okuda,
“Software Engineering Design Patterns for Machine Learning Applications,” IEEE Computer, Vol. 55, No. 3, pp. 30-39, 2022. (Best Paper Award)

23. AI for SE: From AI-assisted dev to Human/AI co-creation (ref: AI-SEAL [Feldt18])
23
Robert Feldt, et al., Ways of Applying Artificial Intelligence in Software Engineering, RAISE 2018, CoRR abs/1802.02033
Agentic
actions
Process
Automation level
Target
Product
Runtime
Low risk
High risk
Middle risk
Completion Exploration
& chat
Tool Partner Agent
Developers Customers
End users
AI agents
Reasoning &
implementation

24. AI for SE: Automated repair and maintenance
Defect detection Validation
Report Fixing
Attachment
Severity
Resolution
time
Summary: Backspace and
navigation keys no longer working
for recipient input fields
Priority: P1 , Severity: Critical,
Attachments: 1633287-input-field.diff
Seen on 77.0a1 (2020-04-26) (64-bit), Win10
Weird and nasty, if someone is able to reproduce this, please
confirm!
STR ###Steps to Reproduce###
1. compose, start recipient input for "john“
2. …
Summary: Backspace and
navigation keys no longer working
for recipient input fields
Priority: P1 , Severity: Critical,
Attachments: 1633287-input-field.diff
Seen on 77.0a1 (2020-04-26) (64-bit), Win10
Weird and nasty, if someone is able to reproduce this, please
confirm!
STR ###Steps to Reproduce###
1. compose, start recipient input for "john“
2. …
Causal
discovery
S.R. Peralta, H. Washizaki, et al., “Unraveling the Influences on Bug Fixing Time: A Comparative Analysis of Causal Inference Model,”
17th International Conference on Evaluation and Assessment in Software Engineering (EASE 2024)

25. SE for AI: Techniques useful for AI/ML systems quality
Training
data
Trained
model
Prediction,
inference
Infrastructure
software system
New data
ML model repair Monitoring, goal-oriented
modeling
Testing oracle problem,
balanced dataset and coverage
Performance, robustness
and explainability
Architecture validity and
quality assurance
Suitability with objective,
handling unexpected situations
N. Uchihira, AI and Software Engineering, JUSE SQiP 2017
Eric Breck et al., The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction, IEEE Big Data 2017
Metamorphic testing
Search-based testing
Practices and patterns
Quality measurement
25

26. SE for AI: System modeling and MLOps integration [ICEBE’23][FGCS’24][SQJ’24]
“Integrated Multi-view Modeling for Reliable Machine Learning-Intensive Software Engineering,” Software Quality Journal, Vol. 32, Springer, 2024.
“Enterprise Architecture-based Metamodel for a Holistic Business – IT Alignment View on Machine Learning Projects,” IEEE ICEBE 2023, Best Paper Award
“Enterprise Architecture-based Metamodel for Machine Learning Projects and its Management,” Future Generation Computer Systems, 161, 2024 26

27. AI and SE: Educational impact and services
• Higher education
• Emerging endeavors on AI for SE and SE for AI
• Future SWEBOK versions will address how to engineer AI-based systems
• Professional training
• Emerging automated techniques and tools by referring to the general
introduction of AI and ML, as well as AI for SE.
• Ranging from resolving ambiguous requirements to predicting maintainability.
• Emerging methods, patterns and practices
• SSE education
• AI for SSE: AI-assisted service refactoring, agent-based SOA, …
• SSE for AI: LLM/AI as a service (LLaaS, AIaaS),
SE
AI
27

28. Teaching methods [Washizaki+23]
Requ
irem
ent
Arc
hite
ctur
e
Desig
n
Con
stru
ctio
n
Testi
ng
Oper
atio
n
Mai
nten
ance
Confi
gurati
on
Mana
geme
nt
Proce
ss
Mode
l &
meth
od
Qual
ity
Secu
rity
Prof
essi
ona
l
Eco
no
mic
s
Project-based X X X X X X X X
Problem-based X X X X
By reflection X X X X X
Active X X X
Flipped X X
Just-in-time X X
Community
participation
X X
Experimental/resear
ch-based
X
Global development X
Collaborative X
Agile X
H. Washizaki, Maria-Isabel Sanchez-Segura, et al., “Envisioning software engineer training needs in the digital era through the
SWEBOK V4 prism,” 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023)
28

29. Agenda
• SWEBOK Guide evolution
• Emerging areas/topics and educational implication
• BOK comparison: SWEBOK and Software Services Engineering BOKs
29

30. BOKs in (software) services engineering [Xu+24]
• Knowledge Body of Service Computing [Zhang08]
• Software Service Engineering Body of Knowledge (SSEBOK) [Xu14]
• Chinese Software Engineering Body of Knowledge (CSWEBOK)
[MoE19]
[Xu+24] Xiaofei Xu and Zhiying Tu, « Insights and Practice Experiences of Service Science and Engineering Education,” IEEE
International Conference on Software Services Engineering (SSE), 2024
[Zhang08] Liang-Jie Zhang, “Introduction to the Body of Knowledge Areas of Services Computing and Services and Services
System,” IEEE Transactions on Services Computing, 1(2), 2008
[Xu14] Xiaofei Xu, “Education and Knowledge-Body of Service Science and Engineering Program,” Computer Education, 1, 2014
[MoE19] China MoE, “University Teaching Steering Committee on Software Engineering. C-SWEBOK: The Chinese Software
Engineering Body of Knowledge,” Higher Education Press, 2019
30

31. Software Service Engineering Body of Knowledge (SSEBOK)
[Xu14] Xiaofei Xu, “Education and Knowledge-Body of Service Science and Engineering Program,”
Computer Education, 1, 2014 31

32. Chinese Software Engineering Body of Knowledge (CSWEBOK)
[MoE19] China MoE, “University Teaching Steering Committee on Software Engineering. C-SWEBOK:
The Chinese Software Engineering Body of Knowledge,” Higher Education Press, 2019 32

33. Preliminary comparison
SWEBOK Guide V4
Chinese Software Engineering Body
of Knowledge (CSWEBOK)
(Service)
business analysis
Agile and DevOps
SE for AI
AI for SE
Security (of
service systems)
Software Service Engineering Body
of Knowledge (SSEBOK)
Safety (of software
services)
Social and life
(services)
33

34. Possible implication
SWEBOK Guide evolution
• Potential extension
• Business analysis
• Software systems safety
• SSE Knowledge Area as a
SWEBOK Guide supplement?
SSE and its education
• Potential enhanced treatment
• Agile/DevOps
• SSE for AI & AI for SSE
• Security in SSE
• BOK-based learning courses
and certifications?
• Suitable teaching methods?
34

35. SWEBOK Guide evolution from V3 to V4
• Modern engineering, practice update, BOK grows and recently developed areas
Requirements
Design
Construction
Testing
Maintenance
Configuration Management
Engineering Management
Process
Models and Methods
Quality
Professional Practice
Economics
Computing Foundations
Mathematical Foundations
Engineering Foundations
Requirements
Architecture
Design
Construction
Testing
Operations
Maintenance
Configuration Management
Engineering Management
Process
Models and Methods
Quality
Security
Professional Practice
Economics
Computing Foundations
Mathematical Foundations
Engineering Foundations
V3 V4
Agile,
DevOps
AI for
SE, SE
for AI
H. Washizaki, eds., “Guide to the Software Engineering Body of Knowledge (SWEBOK Guide), Version 4.0,” IEEE Computer Society, 2024
Editor:
H. Washizaki
KA editors:
A. Ihara,
S. Ogata,
N. Yoshioka,
S. Munetoh,
K. Shintani,
E. Hayashiguchi
and 15+ experts
Preliminary comparison
SWEBOK Guide V4
Chinese Software Engineering Body
of Knowledge (CSWEBOK)
(Service)
business analysis
Agile and DevOps?
SE for AI?
AI for SE?
Security (of
service systems) ?
Software Service Engineering Body
of Knowledge (SSEBOK)
Safety (of software
services)
Social and life
(services)
AI for SE: From AI-assisted dev to Human/AI co-creation (ref: AI-SEAL [Feldt18])
23
Robert Feldt, et al., Ways of Applying Artificial Intelligence in Software Engineering, RAISE 2018, CoRR abs/1802.02033
Agentic
actions
Process
Automation level
Target
Product
Runtime
Low risk
High risk
Middle risk
Completion Exploration
& chat
Tool Partner Agent
Developers Customers
End users
AI agents
Reasoning &
implementation
Teaching methods [Washizaki+23]
Eco
no
mic
s
Prof
essi
ona
l
Secu
rity
Qual
ity
Mode
l &
meth
od
Proce
ss
Mana
geme
nt
Confi
gurati
on
Mai
nten
ance
Oper
atio
n
Testi
ng
Con
stru
ctio
n
Desig
n
Arc
hite
ctur
e
Requ
irem
ent
X
X
X
X
X
X
X
X
Project-based
X
X
X
X
Problem-based
X
X
X
X
X
By reflection
X
X
X
Active
X
X
Flipped
X
X
Just-in-time
X
X
Community
participation
X
Experimental/resear
ch-based
X
Global development
X
Collaborative
X
Agile
H. Washizaki, Maria-Isabel Sanchez-Segura, et al., “Envisioning software engineer training needs in the digital era through the
SWEBOK V4 prism,” 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023)
35