Journal Stats

  • Research Direction: Computer
  • Sci Category: SCIE

Empirical Software Engineering

Journal ISSN: 1573-7616,1382-3256

JCR: Q1

Impact Factor: 4.5

Articles

AI support for data scientists: An empirical study on workflow and alternative code recommendations

Dhivyabharathi Ramasamy, Cristina Sarasua & Abraham Bernstein
Published: 04 July 2025
Volume 30, article number 133, (2025)
DOI:https://doi.org/10.1007/s10664-025-10622-4
Keywords:AI support,Coding assistants,Prompt engineering,Alternative recommendations,User interfaces,Data science workflows,Computational notebooks

Understanding practitioners’ reasoning and requirements for efficient tool support in technical debt management

João Paulo Biazotto, Daniel Feitosa, Paris Avgeriou & Elisa Yumi Nakagawa
Published: 04 July 2025
Volume 30, article number 134, (2025)
DOI:https://doi.org/10.1007/s10664-025-10691-5
Keywords:Technical debt,Technical debt management,Tool support,Survey,Thematic synthesis

KBL: a golden keywords-based query reformulation approach for bug localization

Biyu Cai, Weiqin Zou, Qianshuang Meng, Hui Xu & Jingxuan Zhang
Published: 05 July 2025
Volume 30, article number 135, (2025)
DOI:https://doi.org/10.1007/s10664-025-10694-2
Keywords:Bug report,Query reformulation,Golden keywords,Bug localization

Enhanced SQL error messages facilitate faster error fixing

Toni Taipalus, Hilkka Grahn & Antti Knutas
Published: 07 July 2025
Volume 30, article number 136, (2025)
DOI:https://doi.org/10.1007/s10664-025-10695-1
Keywords:SQL,Compiler,Error message,Database management system,Software development,Error recovery

The effect of stereotypes on perceived competence of indigenous software practitioners: a study of dress style in professional photos

Mary Sánchez-Gordón, Ricardo Colomo-Palacios, Cathy Guevara-Vega, Antonio Quiña-Mera & Aliaksandr Hubin
Published: 08 July 2025
Volume 30, article number 137, (2025)
DOI:https://doi.org/10.1007/s10664-025-10675-5
Keywords:Software developer,Stereotypes,Perception of competence,Impression formation,Social cognition,Indigenous

Guiding principles for mixed methods research in software engineering

Margaret-Anne Storey, Rashina Hoda, Alessandra Maciel Paz Milani & Maria Teresa Baldassarre
Published: 09 July 2025
Volume 30, article number 138, (2025)
DOI:https://doi.org/10.1007/s10664-025-10629-x
Keywords:Mixed methods,Research methods,Methodology,Guiding principles

When code smells meet ML: on the lifecycle of ML-specific code smells in ML-enabled systems

Gilberto Recupito, Giammaria Giordano, Filomena Ferrucci, Dario Di Nucci & Fabio Palomba
Published: 12 July 2025
Volume 30, article number 139, (2025)
DOI:https://doi.org/10.1007/s10664-025-10676-4
Keywords:Software engineering for artificial intelligence,Software quality for artificial intelligence,Technical debt,Empirical software engineering

MPDA: a data augmentation approach to improve deep learning for software vulnerability detection

Feiqiao Mao, Yingxiang Yuan, Xingyang Du, Li Gao & Zhihua Du
Published: 14 July 2025
Volume 30, article number 140, (2025)
DOI:https://doi.org/10.1007/s10664-025-10698-y
Keywords:Deep learning,Data augmentation,Software vulnerability detection,Data imbalance

Introduction

Empirical Software Engineering serves as a vital forum for applied software engineering research with a strong empirical focus.

  • A platform for empirical results relevant to both researchers and practitioners.
  • Features industrial experience reports detailing the application of software technologies.
  • Addresses the gap between research and practice.
  • Promotes industry-relevant research.
  • Encourages studies that can be replicated or expanded upon.

Editorial Board

Editors-in-Chief

  • Robert Feldt, Chalmers University of Technology, Sweden
  • Thomas Zimmermann, University of California, Irvine, USA

Editors-in-Chief Emeritus

  • Victor R. Basili, Dept. of Computer Science, University of Maryland, College Park, USA
  • Lionel C. Briand, The Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg

Advisory Board

  • Daniel M. Berry, University of Waterloo, Canada
  • Daniela Damian, University of Victoria, Canada
  • Harald Gall, University of Zurich, Switzerland
  • Mark Harman, University College London, UK
  • Ahmed Hassan, Queen’s University, Canada
  • Natalia Juristo, Universidad Politecnico de Madrid, Spain
  • Sung Kim, Hong Kong University of Science and Technology, Hong Kong
  • Filippo Lanubile, University of Bari, Italy
  • Hong Mei, Peking University, China
  • Atif Memon, University of Maryland, USA
  • Tim Menzies, North Carolina State University, USA
  • Audris Mockus, Avaya Labs, USA
  • Jeff Offutt, George Mason University, USA
  • Dieter Rombach, University of Kaiserslautern & Fraunhofer IESE, Germany
  • Per Runeson, Lund University, Sweden
  • Martin Shepperd, Brunel University, UK
  • Arie van Deursen, Delft University of Technology, The Netherlands
  • Andreas Zeller, Saarland University, Germany
  • Laurie Williams, North Carolina State University, USA

Aims & Scope

  • Analysis and design

  • Model‑driven development

  • Requirements engineering

  • Verification and validation

  • Maintenance and evolution

  • Quality assurance

  • Dependability analysis

  • Project management

  • Organization models for software development

  • Predictive models for software dependability

  • Applications of artificial intelligence techniques to software engineering

  • Qualitative analysis

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