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Mathematicians, Social Scientists,
or Engineers?
The Split Minds of Software
Engineering Researchers
Lionel Briand
http://www.lbriand.info
ICSE 2022
A Word of Thanks …
PhD advisor: Victor Basili
Collaborators and students: See the 2020 ACM SE Notes
interview on my web page
Family, for their patience and tolerance ;-)
2
Motivations
Happiness is not a function of what you achieve. It's a function
of how you spend your time. Success is a temporary thrill.
Happiness lies in doing daily activities that bring you joy.
There's always a new mountain to climb. You don't have to
anchor your emotions to the summit.
Adam Grant, Organizational Psychologist, Wharton, USA
3
What Kept Me in Academia
4
Who are we?
What is our purpose?
5
Traditional Engineering Fields
6
Software Systems
• No standard education
• No standard practices
• Human intensive
7
• Variability
• Frequent change
• No continuity property
A Tale of Three Communities
8
Formal Methods
and
Guarantees
Human & Social
Studies
Engineering
Automated
Solutions
A Tale of Three Communities
9
Formal Methods
and
Guarantees
Human & Social
Studies
Engineering
Automated
Solutions
• Combining solvers and
smart heuristics
• Probabilistic guarantees
• Trade-offs
• Scalability
• Applicability
A Tale of Three Communities
10
Formal Methods
and
Guarantees
Human & Social
Studies
Engineering
Automated
Solutions
In Vitro vs.
in Vivo
evaluation
• Assumptions
• Complexity
• Limitations
Reality
11
Formal Methods
and
Guarantees
Human & Social
Studies
Engineering
Automated
Solutions
Disconnect
Twitter
Stack Overflow
Diversity
Values
Leadership
Coordination
Sleep
Cannabis
…
Evolutionary computing
Machine learning
Natural Language Proc.
…
Solvers
Theorem provers
Symbolic execution
…
Representation
12
Formal Methods
and
Guarantees
Human & Social
Studies
Engineering
Automated
Solutions
Distinguished
papers ICSE 2022
(nominated)
7
10
2
Original
emphasis
A World Apart
• “HiTyper iteratively conducts static inference and DL-based
prediction until the TDG is fully inferred. Experiments on two
benchmark datasets show that HiTyper outperforms state-of-the-
art DL models …”
• “Leadership: (1) is dynamically shared among team members; (2)
engenders a sense of belonging to the team; and (3) involves
balancing competing organizational cultures …”
• “Diva proves 68% more theorems than TacTok and 77% more than
ASTactic. Complementary to CoqHammer, Diva proves 781
theorems (27% added value) that CoqHammer does not, and 364
theorems no existing tool has proved automatically.”
13
A World Apart
• “HiTyper iteratively conducts static inference and DL-based
prediction until the TDG is fully inferred. Experiments on two
benchmark datasets show that HiTyper outperforms state-of-the-
art DL models …”
• “Leadership: (1) is dynamically shared among team members; (2)
engenders a sense of belonging to the team; and (3) involves
balancing competing organizational cultures …”
• “Diva proves 68% more theorems than TacTok and 77% more than
ASTactic. Complementary to CoqHammer, Diva proves 781
theorems (27% added value) that CoqHammer does not, and 364
theorems no existing tool has proved automatically.”
14
Different backgrounds, language,
research methods …
Diversity is Good
• This is what a field like software engineering requires
• But …
• Those communities need to be (significantly) connected
• We need to be able to talk to each other and work together
• Only then we will be able to offer the novel solutions that
software engineering needs and maximize our impact
15
Would it change anything for
the three sub-communities if
we attended different
conferences and published
in different journals?
16
Social Studies and Football
• Regarding human and social science studies …
• Assuming you replace “software engineering” by “football” in
a paper …
• If the paper abstract still makes sense, is it software
engineering research?
• Does the software engineering context matter?
17
Biases in Engineering Research
• What is the impact of our heavy reliance on Open-Source systems
(OSS) and data for our engineering research?
• Type and size of systems, underlying technology
• Generalization of results?
• Context is everything is software engineering …
18
Formal Methods for Software
Engineering
• Software engineering research versus applied mathematics,
Computer Aided Verification
• Can it be so practically limited, so disconnected from
engineering reality, that it can only be seen as an intellectual
exercise?
• Is such research a necessary first step?
19
Impact
21
Dimensions of Impact
• Timeline: Short versus long term
• Mechanism: Publications, interactions, knowledge transfer,
organizational change, commercialization, …
• Evidence: Empirical results, industrial adoption, …
22
My Experience with Industry
• Scope the collaboration
• Define the problem(s) and prioritizing
• Read the research literature
• Identify the gaps
• Plan the research
• ….
23
Typical (abstract) Dialog
• Partner: What are the solutions available in the research literature?
• Me (Slightly embarrassed): Well, there are good ideas but nothing
that can fit your needs and scale to your systems. We have a great
deal to do, and it is going to take X years.
• Lack of operational, scalable, practical solutions
• Recent example: Regression testing, a topic that has been,
relatively speaking, extensively investigated
• No accurate, applicable and scalable (published) solutions in a CI
context, with frequent builds and large systems
24
Schneiderman’s Model
• Ben Schneiderman, “The New ABCs of Research: Achieving Breakthrough Collaborations”, 2016
• Linear model of research is ineffective
• A Collaborative Model of Research and Innovation
• Access to smart and motivated professionals
• Produce dual benefits: publishable research results and focused practical solutions that serve an
existing or foreseeable market
25
Basic Research
Applied
Research
Innovation & Development
Schneiderman’s Model
• Applied research feeds basic research
• Lower barriers to technology transfer
• Common practice in GAFAM
• Public-private partnerships
26
Basic Research
Applied
Research
Innovation & Development
Strategy for Software
Engineering
27
• Research driven by industry needs
• Realistic evaluations
• Combining research with technology transfer and innovation
Problem
Formulation
Problem
Identification
State of the
Art Review
Candidate
Solution(s)
Initial
Validation
Training
Realistic
Validation
Industry Partners
Research Groups
1
2
3
4
5
7
Solution
Release
8
6
Adapted from Gorschek et al., 2006
Making it Possible
• Institutions: Support partnerships (e.g., technology transfer
offices, enabling industrial leaves for faculty members)
• Funding Agencies: Finance partnerships through specific
programs
• Private companies: Long term commitments, open science
• Academics: Develop an appreciation for demand-driven
research in industrial contexts. Change publication model.
28
The goal is not to forbid
curiosity-driven research
but to encourage demand-
driven, collaborative
research
29
Mathematicians, Social Scientists,
or Engineers?
The Split Minds of Software
Engineering Researchers
Lionel Briand
http://www.lbriand.info
ICSE 2022

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Mathematicians, Social Scientists, or Engineers? The Split Minds of Software Engineering Researchers

  • 1. Mathematicians, Social Scientists, or Engineers? The Split Minds of Software Engineering Researchers Lionel Briand http://www.lbriand.info ICSE 2022
  • 2. A Word of Thanks … PhD advisor: Victor Basili Collaborators and students: See the 2020 ACM SE Notes interview on my web page Family, for their patience and tolerance ;-) 2
  • 3. Motivations Happiness is not a function of what you achieve. It's a function of how you spend your time. Success is a temporary thrill. Happiness lies in doing daily activities that bring you joy. There's always a new mountain to climb. You don't have to anchor your emotions to the summit. Adam Grant, Organizational Psychologist, Wharton, USA 3
  • 4. What Kept Me in Academia 4
  • 5. Who are we? What is our purpose? 5
  • 7. Software Systems • No standard education • No standard practices • Human intensive 7 • Variability • Frequent change • No continuity property
  • 8. A Tale of Three Communities 8 Formal Methods and Guarantees Human & Social Studies Engineering Automated Solutions
  • 9. A Tale of Three Communities 9 Formal Methods and Guarantees Human & Social Studies Engineering Automated Solutions • Combining solvers and smart heuristics • Probabilistic guarantees • Trade-offs • Scalability • Applicability
  • 10. A Tale of Three Communities 10 Formal Methods and Guarantees Human & Social Studies Engineering Automated Solutions In Vitro vs. in Vivo evaluation • Assumptions • Complexity • Limitations
  • 11. Reality 11 Formal Methods and Guarantees Human & Social Studies Engineering Automated Solutions Disconnect Twitter Stack Overflow Diversity Values Leadership Coordination Sleep Cannabis … Evolutionary computing Machine learning Natural Language Proc. … Solvers Theorem provers Symbolic execution …
  • 12. Representation 12 Formal Methods and Guarantees Human & Social Studies Engineering Automated Solutions Distinguished papers ICSE 2022 (nominated) 7 10 2 Original emphasis
  • 13. A World Apart • “HiTyper iteratively conducts static inference and DL-based prediction until the TDG is fully inferred. Experiments on two benchmark datasets show that HiTyper outperforms state-of-the- art DL models …” • “Leadership: (1) is dynamically shared among team members; (2) engenders a sense of belonging to the team; and (3) involves balancing competing organizational cultures …” • “Diva proves 68% more theorems than TacTok and 77% more than ASTactic. Complementary to CoqHammer, Diva proves 781 theorems (27% added value) that CoqHammer does not, and 364 theorems no existing tool has proved automatically.” 13
  • 14. A World Apart • “HiTyper iteratively conducts static inference and DL-based prediction until the TDG is fully inferred. Experiments on two benchmark datasets show that HiTyper outperforms state-of-the- art DL models …” • “Leadership: (1) is dynamically shared among team members; (2) engenders a sense of belonging to the team; and (3) involves balancing competing organizational cultures …” • “Diva proves 68% more theorems than TacTok and 77% more than ASTactic. Complementary to CoqHammer, Diva proves 781 theorems (27% added value) that CoqHammer does not, and 364 theorems no existing tool has proved automatically.” 14 Different backgrounds, language, research methods …
  • 15. Diversity is Good • This is what a field like software engineering requires • But … • Those communities need to be (significantly) connected • We need to be able to talk to each other and work together • Only then we will be able to offer the novel solutions that software engineering needs and maximize our impact 15
  • 16. Would it change anything for the three sub-communities if we attended different conferences and published in different journals? 16
  • 17. Social Studies and Football • Regarding human and social science studies … • Assuming you replace “software engineering” by “football” in a paper … • If the paper abstract still makes sense, is it software engineering research? • Does the software engineering context matter? 17
  • 18. Biases in Engineering Research • What is the impact of our heavy reliance on Open-Source systems (OSS) and data for our engineering research? • Type and size of systems, underlying technology • Generalization of results? • Context is everything is software engineering … 18
  • 19. Formal Methods for Software Engineering • Software engineering research versus applied mathematics, Computer Aided Verification • Can it be so practically limited, so disconnected from engineering reality, that it can only be seen as an intellectual exercise? • Is such research a necessary first step? 19
  • 21. Dimensions of Impact • Timeline: Short versus long term • Mechanism: Publications, interactions, knowledge transfer, organizational change, commercialization, … • Evidence: Empirical results, industrial adoption, … 22
  • 22. My Experience with Industry • Scope the collaboration • Define the problem(s) and prioritizing • Read the research literature • Identify the gaps • Plan the research • …. 23
  • 23. Typical (abstract) Dialog • Partner: What are the solutions available in the research literature? • Me (Slightly embarrassed): Well, there are good ideas but nothing that can fit your needs and scale to your systems. We have a great deal to do, and it is going to take X years. • Lack of operational, scalable, practical solutions • Recent example: Regression testing, a topic that has been, relatively speaking, extensively investigated • No accurate, applicable and scalable (published) solutions in a CI context, with frequent builds and large systems 24
  • 24. Schneiderman’s Model • Ben Schneiderman, “The New ABCs of Research: Achieving Breakthrough Collaborations”, 2016 • Linear model of research is ineffective • A Collaborative Model of Research and Innovation • Access to smart and motivated professionals • Produce dual benefits: publishable research results and focused practical solutions that serve an existing or foreseeable market 25 Basic Research Applied Research Innovation & Development
  • 25. Schneiderman’s Model • Applied research feeds basic research • Lower barriers to technology transfer • Common practice in GAFAM • Public-private partnerships 26 Basic Research Applied Research Innovation & Development
  • 26. Strategy for Software Engineering 27 • Research driven by industry needs • Realistic evaluations • Combining research with technology transfer and innovation Problem Formulation Problem Identification State of the Art Review Candidate Solution(s) Initial Validation Training Realistic Validation Industry Partners Research Groups 1 2 3 4 5 7 Solution Release 8 6 Adapted from Gorschek et al., 2006
  • 27. Making it Possible • Institutions: Support partnerships (e.g., technology transfer offices, enabling industrial leaves for faculty members) • Funding Agencies: Finance partnerships through specific programs • Private companies: Long term commitments, open science • Academics: Develop an appreciation for demand-driven research in industrial contexts. Change publication model. 28
  • 28. The goal is not to forbid curiosity-driven research but to encourage demand- driven, collaborative research 29
  • 29. Mathematicians, Social Scientists, or Engineers? The Split Minds of Software Engineering Researchers Lionel Briand http://www.lbriand.info ICSE 2022