Información de la conferencia

ESEM 2026: International Symposium on Empirical Software Engineering and Measurement

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Día de Entrega:
2026-04-22 Cerrado
Fecha de Notificación:
2026-06-30
Fecha de conferencia:
2026-10-04
Ubicación:
Munchen, Germany
Ediciones:
20
CCF: B   ICORE: A   QUALIS: A2   Vistas: 154667   Seguidores: 64   Asistentes: 5
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ESEM
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72,7 / 100
Puesto n.º 292 de 5.705 congresos · 6% superior

N.º 8 de 512 en Ingeniería eléctrica y electrónica N.º 37 de 247 en Ingeniería de software

Reconocimiento académico (35%)
92
Selectividad en la revisión (20%) Sin datos: se puntúa con la línea base neutra de 50 —
Ediciones celebradas (20%)
82
Atención de la comunidad (10%)
66
Integridad del registro público (15%)
50

Datos utilizados: Categorías: CCF B, ICORE A, QUALIS A2 · Ediciones documentadas: 20 · Investigadores que lo siguen aquí: 64 · Investigadores que abrieron esta página en los últimos 24 meses: 29

Falta en el registro público: Tasas de aceptación históricas (+4,5) · Ediciones anteriores (+3,0)
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Solicitud de Artículos

ESEM 2026 (International Symposium on Empirical Software Engineering and Measurement) is a CCF B / ICORE A / QUALIS A2 conference held in Munchen, Germany on 2026-10-04. The paper submission deadline is 2026-04-22. Acceptance notifications are sent on 2026-06-30.

The International Symposium on Empirical Software Engineering and Measurement (ESEM) technical papers (main) track features submissions that describe original, unpublished work in software engineering and software measurement, with a strong empirical foundation. Papers in this track should communicate fully developed research and results. Strong emphasis should be given to the methodological aspects of the research and the assessment of the validity of the contributions. Please note: Open Science policy: ESEM is open by default. Submissions must comply with the Open Science Policy and provide the artifacts needed to understand and reproduce the analysis, unless legal/ethical barriers exist (see details on Data Availability below). Double-anonymous review format: ESEM 2026 uses double blind reviewing. Submissions must not reveal authors’ identities. General scope of submissions Submissions must not be under consideration for publication or presentation elsewhere. In addition to the specific scope of this track, submissions may address any aspect of software engineering but must tackle the problem from an empirical perspective and using a rigorous empirical method, including (but not limited to): Empirical studies using qualitative, quantitative, and mixed methods Cross- and multi-disciplinary methods and studies Controlled experiments and quasi-experiments Case studies, action research, ethnography, and field studies Survey research Simulation studies Artifact studies Data mining using statistical, machine learning, and AI-based approaches Meta-studies and evidence syntheses, including: Systematic literature reviews and rapid reviews with a strong synthesis component and a clear contribution beyond overview summarization Meta-analyses, and qualitative, quantitative, or structured syntheses of prior studies that generate clear new insights Replication studies Papers should be positioned in terms of research methodology and contribution in relation to established frameworks for empirical software engineering and measurement. Negative results are also welcome as long as the research is based on well-motivated hypotheses in line with the state-of-the-art, relevant scientific knowledge that is then well-documented, analysed in depth, and provides clear value to the community. Topics of interest (illustrative, not exhaustive) Topics in scope for ESEM 2026 and commonly addressed using an empirical approach include, but are not limited to: Evaluation and comparison of software models, tools, techniques, and practices Modeling, measuring, and assessing product or process quality and productivity Continuous software engineering Software verification and validation, including analysis and testing Engineering of software systems that include machine learning components and data dependencies Applications of software engineering to different types of systems and domains (e.g., IoT, cyber-physical systems, Industry 4.0) Human factors, teamwork, and behavioral aspects of software engineering We also welcome submissions that relate to meta-topics around empirical software engineering research, including for example: Development, evaluation, and comparison of empirical approaches and methods Infrastructure, techniques, and tools for conducting and supporting empirical studies
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Los Mejores Artículos

AñoLos Mejores Artículos
2018A Longitudinal Cohort Study on the Retainment of Test-driven Development
2018Relationship Between Geographical Location and Evaluation of Developer Contributions in Github
2018What if a Bug has a Different Origin? Making Sense of Bugs Without an Explicit Bug Introducing Change
2018Automatic Topic Classification of Test Cases Using Text Mining at an Android Smartphone Vendor
2018Prediction of relatedness in stack overflow: deep learning vs. SVM: a reproducibility study
2018Comparing Techniques for Aggregating Interrelated Replications in Software Engineering
2017Quantifying the Transition from Python 2 to 3: An Empirical Study of Python Applications
2017An empirical analysis of FLOSS repositories to compare One-Time Contributors to Core and Periphery Developers
2017REACT: An Approach for Capturing Rationale in Chat Messages
2017Early Phase Cost Models for Agile Software Processes in the US DoD
2016Experiences from Measuring Learning Potential and Performance in Large-Scale Distributed Software Development
2016Using Forward Snowballing to update Systematic Reviews in Software Engineering
2016An External Replication on the Effects of Test-driven Development Using Blind Analysis
2015An Exploratory Study on the Evolution of C Programming in the Unix Operating System
2015How to Make Best Use of Cross-Company Data for Web Effort Estimation?
2015Don't Call Us, We'll Call You: Characterizing Callbacks in JavaScript
2014Evaluating strategies for study selection in systematic literature studies
2014Networking in a Large-Scale Distributed Agile Project
2014Towards a Framework to Support Large Scale Sampling in Software Engineering Surveys
2014Discovering Buffer Overflow Vulnerabilities In The Wild: An Empirical Study
2013Towards a Metric Suite Proposal to Quantify Confirmation Biases of Developers
2013Evaluating software product metrics with synthetic defect data
2013Benchmarking Usability and Performance of Multicore Languages
2012Handling Categorical Variables in Effort Estimation
2012Experimental Assessment of Software Metrics using Automated Refactoring
2011One Technique is Not Enough: A Comparison of Vulnerability Discovery Techniques
2011An Empirical Investigation of Systematic Reviews in Software Engineering
2011End-User Programmers and their Communities: An Artifact-Based Analysis
2011Design of an Empirical Study for Comparing the Usability of Concurrent Programming Languages
2011An Empirical Study on the Use of Team Building Criteria in Software Projects
2011Scrum + Engineering Practices: Experiences of Three Microsoft Teams
2010Transition from a plan-driven process to Scrum: a longitudinal case study on software quality
2010Trust dynamics in global software engineering
2010Are developers complying with the process: an XP study
2009Using differences among replications of software engineering experiments to gain knowledge
2008Socio-technical congruence: a framework for assessing the impact of technical and work dependencies on software development productivity
2007The Effects of Over and Under Sampling on Fault-prone Module Detection
2007Toward Reducing Fault Fix Time: Understanding Developer Behavior for the Design of Automated Fault Detection Tools

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