Fabio Calefato

Fabio Calefato

Associate Professor

Curriculum Vitae

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Contacts

Research Experience

University of Bari, Dept. of Computer Science, Associate Professor

PeoplewareAI s.r.l., Co-founder and CEO

University of Bari, Dept. of Computer Science, Tenure-track Assistant Professor

University of Bari, Jonian Dept., Untenured Assistant Professor

University of Bari, Dept. of Computer Science, Postdoctoral Research Fellow

University of Bari, Dept. of Computer Science, Postdoctoral Research Fellow

University of Bari, Dept. of Computer Science, Postdoctoral Research Fellow

Education

Inter-University Specialization School for Secondary Education in Physics, Computer Science, and Mathematics

PhD in Computer Science

MSc in Computer Science

Research Activity

My research primarily focuses on the intersection of Software Engineering and AI/ML, while also encompassing human factors in software development and globally distributed software engineering. Throughout my career, I have maintained a strong focus on empirical validation of research findings, conducting controlled experiments, case studies, and mining open-source software repositories. My work has consistently appeared in top-tier venues and has influenced both academic research and industry practices in software engineering. Below is a detailed description of some of my research activities, organized by recency and impact.

Generative AI for software engineering research and practices: In collaboration with leading international researchers, I am advancing three active workstreams that emerged from my participation in the 2023 and 2024 editions of the Copenhagen Symposium on Human-Centered Software Engineering AI. The first workstream comprises an observational study mining self-admitted mentions of LLMs usage in open-source projects. Together, we examined how developers integrate AI assistants into their workflows across development tasks, content types, and usage purposes. Our study analyzed over 250,000 open-source repositories, identifying patterns in AI tool adoption and their impact on project metrics. An article describing this collaborative work is currently under review at IEEE TSE. The second workstream aims to establish a comprehensive set of guidelines for conducting experiments with LLMs in software engineering research. Our joint initiative addresses the challenges of achieving reproducible results with LLMs by tackling their unique characteristics that affect study validity and reproducibility, providing researchers with concrete protocols for empirical evaluations. The third workstream investigates the integration of AI in software engineering research methodologies. Together, we examine how Generative AI tools can support various research tasks including qualitative analysis, systematic literature reviews, and human studies design. Our collaborative work explores both opportunities and risks of AI adoption in SE research, gathering perspectives from researchers about the changing landscape of empirical software engineering methods.

Software engineering for AI-enabled systems: One of my recent research interests is focused on improving the development workflows of AI/ML-based systems through empirical studies and tool development. I conducted a comprehensive review of industry-leading AutoML tools to analyze their benefits and limitations in software engineering contexts (IST 2025). I have contributed to understanding MLOps practices by analyzing adoption patterns in open-source projects on GitHub (ESEM 2022). This work revealed key challenges in transitioning ML models from experimentation to production, leading to the development of an MLOps solution framework applied in healthcare contexts (CAIN 2022). Finally, I have established best practices for collaborative development of AI systems using computational notebooks (CSCW 2021).

AI Safety and Regulatory Compliance in Healthcare Systems: One of my current research interests focuses on developing frameworks and methodologies for ensuring continuous compliance and safety of AI systems in regulated healthcare environments. This research addresses the challenge of maintaining regulatory adherence while enabling continuous learning in medical AI applications. Working with medical professionals and life science researchers, I am developing an extended MLOps framework that integrates automated compliance verification, monitoring, and ethical oversight throughout the AI system lifecycle. The framework introduces systematic approaches for bias detection, fairness assessment, and performance monitoring across demographic groups, bridging the gap between responsible AI principles and clinical implementation requirements. This work has fostered collaborations with healthcare institutions and secured funding through national initiatives, including the DARE project (€130.5M) for digital preventive healthcare solutions.

Industry-based research on the state of software engineering practices: I have participated in and continue to contribute to several industry-based global surveys to understand software engineering practices. The HELENA (Hybrid dEveLopmENt Approaches in software systems development) project has identified key characteristics of hybrid development approaches through analysis of 1,000+ developers across 50 countries since 2016. Our findings on agile process adoption patterns appeared in IEEE TSE (2021), significantly impacting our understanding of modern development methodologies. The NaPiRE project (Naming the Pain in Requirements Engineering) is a global survey initiative examining industrial practices and challenges in Requirements Engineering. Through biannual surveys, our large-scale academic collaboration develops a holistic theory of RE practices and problems, producing insights that guide problem-driven research. The Evolution of Post-Pandemic Work Policies project analyzes hybrid and remote work policies across companies worldwide through global surveys and academic collaboration. Our research provides evidence-based insights into emerging work patterns, revealing challenges and adaptations in post-pandemic work environments and helping organizations optimize their hybrid workplace policies.

Human factors in software engineering: In my research I have extensively investigated how human factors such, as personality traits, emotions, and social dynamics, influence software development processes, leveraging AI/ML techniques for analysis across various developer platforms and communication channels. In technical Q&A platforms like Stack Overflow, I have conducted comprehensive studies analyzing both technical aspects (such as community guidelines for effective questions) and social factors affecting answer success rates (MSR 2015, ESEM 2016, IST 2018, EMSE 2019). This work has led to the creation of gold standards for sentiment analysis (MSR 2018) and the development of ML-based methods to detect emotions and sentiment polarity in technical communication (IEEE Software 2020). Additionally, I have conducted cross-platform evaluations of sentiment analysis tools (MSR 2020) and performed extended replications to assess how the choice of sentiment analysis tools influences the validity of empirical studies (EMSE 2021). Beyond sentiment analysis, I have investigated how developer personalities influence collaboration in large software ecosystems like Apache (ICGSE 2018, IST 2019), with particular attention to how traits like agreeableness impact code review activities and pull request acceptance (ICGSE 2017). My work has shed light on the need for developing specialized tools for automatic personality detection from text in technical contexts (TOSEM 2021). With this line of research, I have demonstrated the critical importance of domain-specific approaches when analyzing developer communications, showing the limitations of general-purpose personality and sentiment analysis tools in software engineering contexts. Finally, I have also studied retention and disengagement factors of Open Source Software community participants, defining and validating a theoretical model of the activity rhythm of open-source project developers (SOHEAL 2019, EMSE 2022).

Global software engineering: My research has addressed the challenges of software development distributed on a global scale. Key contributions include theoretical and empirical work on trust-building mechanisms and social awareness in virtual teams (CSCW 2013, CHASE 2012, IEEE Software 2013). I pioneered SocialCDE, a social awareness tool for fostering trust in distributed teams (ESEC/FSE 2013), which was awarded the 2011 Microsoft Software Engineering Innovation Award; this work demonstrated how social awareness tools can increase trust and improve coordination in global teams. I also made significant advances in communication barriers, developing and evaluating eConference, a real-time ML-based translation tool (ICGSE 2010-11, ESEM 2012, ESEM 2014, ESE 2016) that showed promising efficiency gains while identifying important trade-offs in distributed development activities; the tool was awarded the 2006 Eclipse Innovation Award by IBM. Additional contributions include an industrial action research study on communication tools in distributed agile teams (ICGSE 2020). My expertise in this domain is reflected in my service as General Chair for ICGSE 2019 and my role as Guest Editor for JSS special issue on Global Software Engineering (JSS 2021).

Awards

Self-Admitted GenAI Usage: A Mixed Methods Study of Software Projects on GitHub (2025 - under review)

A multivocal literature review on the benefits and limitations of industry-leading AutoML tools (2025)

A lot of talk and a badge: An exploratory analysis of personal achievements in GitHub (2024)

Generative AI in Software Engineering Must Be Human-Centered: The Copenhagen Manifesto (2024)

Assessing the Use of AutoML for Data-Driven Software Engineering (2023)

Eliciting Best Practices for Collaboration with Computational Notebooks (2022)

Using Personality Detection Tools for Software Engineering Research: How Far Can We Go? (2022)

What Makes Agile Software Development Agile? (2022)

Will you come back to contribute? Investigating the inactivity of OSS core developers in GitHub (2022)

A Preliminary Investigation of MLOps Practices in GitHub (2022)

Pynblint: a static analyzer for Python Jupyter notebooks (2022)

An In-Depth Analysis of Occasional and Recurring Collaborations in Online Music Co-creation (2021)

Assessment of off-the-shelf SE-specific sentiment analysis tools: An extended replication study (2021)

Towards Productizing AI/ML Models: An Industry Perspective from Data Scientists (2021)

Love, Joy, Anger, Sadness, Fear, and Surprise: SE Needs Special Kinds of AI: A Case Study on Text Mining and SE (2020)

Can We Use SE-specific Sentiment Analysis Tools in a Cross-Platform Setting? (2020)

A large-scale, in-depth analysis of developers’ personalities in the Apache ecosystem (2019)

RECODE: revision control for digital images (2019)

An empirical assessment of best-answer prediction models in technical Q&A sites (2019)

Agile Collaboration for Distributed Teams [Software Technology] (2019)

How to ask for technical help? Evidence-based guidelines for writing questions on Stack Overflow (2018)

Investigating Crowd Creativity in Online Music Communities (2018)

Assessing the impact of real-time machine translation on multilingual meetings in global software projects (2016)

Moving to Stack Overflow: Best-Answer Prediction in Legacy Developer Forums (2016)

The role of social media in affective trust building in customer-supplier relationships (2015)

Cost Savings in Global Software Engineering: Where’s the Evidence? (2015)

Mining Successful Answers in Stack Overflow (2015)

Speech Recognition for Voice-Based Machine Translation (2014)

An empirical simulation-based study of real-time speech translation for multilingual global project teams (2014)

Group Awareness in Global Software Engineering (2013)

Computer-mediated communication to support distributed requirements elicitations and negotiations tasks (2012)

Assessing the impact of real-time machine translation on requirements meetings: a replicated experiment (2012)

Investigating the use of tags in collaborative development environments: a replicated study (2010)

Using frameworks to develop a distributed conferencing system: an experience report (2009)

A Controlled Experiment on the Effects of Synchronicity in Remote Inspection Meetings (2007)

Ph.D. Students Supervision

Dept. of Computer Science

Dept. of Computer Science, Ph.D. program cycle XXXV

Dept. of Computer Science, Ph.D. program cycle XXXII

Teaching

BSc in Computer Science and Software Production Technologies (ITPS), 2nd year, University of Bari, Dept. of Computer Science in

MSc in Computer Science, 1st year, University of Bari, Dept. of Computer Science in

Ph.D. program in Computer Science and Mathematics (XXXVIII cycle), University of Bari, Dept. of Computer Science in

MSc in Computer Science and Engineering, University of Oulu in

BSc in Computer Science, 3rd year in University of Bari, Dept. of Computer Science

BSc in Computer Science and Software Production Technologies (ITPS), 2nd year, University of Bari, Dept. of Computer Science in

BSc in Computer Science, 3rd year in University of Bari, Dept. of Computer Science

Ph.D. program in Computer Science and Mathematics (XXXIII cycle), University of Bari, Dept. of Computer Science in

Ph.D. program in Rights, Economies, and Cultures of the Mediterranean (XXXIII cycle), University of Bari, Jonian Dept. (Law and Business School) in

Ph.D. program in Computer Science, University of Oulu in

Ph.D. program in Computer Science and Mathematics (XXXII cycle), University of Bari, Dept. of Computer Science in

Ph.D. program in Rights, Economies, and Cultures of the Mediterranean (XXXII cycle), University of Bari, Jonian Dept. (Law and Business School) in

BSc in Maritime Sciences and Management (SGAM), 2nd year in

Bachelor of Law, 1st year, University of Bari, Jonian Dept. (Law and Business School) in

BSc in Computer Science and Software Production Technologies (ITPS), 1st year, University of Bari, Dept. of Computer Science in

BSc in Computer Science, 1st year, University of Bari, Dept. of Computer Science in

BSc in Computer Science, 1st year, University of Bari, Dept. of Computer Science in

Funded Research Projects

DARE - Digital Lifelong Prevention

SERICS - SEcurity and RIghts In the CyberSpace / Spoke 9: SuReCare

C3 - Creative Cultural Collaboration

OpEn - Open up Entrepreneurship

VINCENTE - A Virtual Collective Intelligence Environment to Develop Sustainable Technology Entrepreneurship Ecosystems

PRONEM - Natural Language Processing for Global Software Development

INTERSOCIAL - Unleashing the Power of Social Networking for Enhancing Regional Systems

LOGIN - LOgistica INtegrata

Funding Acquisition Proposals

DisTrac: A tool for tracking disengagement in open-source software projects

ARIANNA: ARtIficiAl iNtelligeNce for virtuAl meetings

Academic Service

Rector’s Delegate for the GARR Network

CS Dept. Director’s Delegate for Internship Programs

Associate Editor

Guest Editor

Review Board Member

Peer Reviews (partial list)

External Reviewer (Opponent) in Doctoral Defenses

Events Organization

Program Co-Chair

General Chair

Steering Board Member

Track Co-Chair

Workshops & Tutorials Co-Chair

Workshops Co-Chair

Open-science Co-Chair

Publicity & Social Media Chair

Keynote Presentations

The Potential and Challenges of Personality Detection in Software Engineering Research

Facing Communication Challenges in Distributed Software Development

Membership in Program Committees

Dept. of Computer Science

Dept. of Computer Science

Dept. of Computer Science

Dept. of Electrical and Information Engineering

Dept. of Electrical and Information Engineering

Research Visits

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Invited Seminars

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Software

BehaViz®

xMLOps Pipeline

EMTk (Emotion-Mining Toolkit)

References