7^th International Conference on Data Mining and Software Engineering (DMSE 2026)

July 16 ~ 17, 2026, London, United Kingdom

https://cmla2026.org/dmse/index

Scope & Topics

The 7^th International Conference on Data Mining and Software Engineering (DMSE 2026) aims to provide a premier international forum for researchers, practitioners, and industry experts to share their knowledge, insights, and results in the theory, methodology, and applications of Data Mining and Software Engineering. As these fields continue to evolve rapidly, driven by advances in artificial intelligence, large-scale data analytics, and modern software development practices, DMSE 2026 seeks to foster deeper understanding, spark innovation, and promote meaningful collaboration across disciplines.

The goal of the conference is to bring together leading minds from academia and industry to explore emerging trends, address contemporary challenges, and establish new partnerships in Data Mining and Software Engineering. By bridging foundational research with real world applications, DMSE 2026 provides a platform for exchanging ideas that shape the future of intelligent systems, data driven engineering, and next generation software technologies.

Authors are invited to contribute high quality research papers, case studies, survey articles, and industrial experiences that demonstrate significant advances in the following areas, but are not limited to::

Topics of interest include, but are not limited to, the following:

Foundations of Data Mining and Software Engineering

Algorithms, Models, and Theory for Data Mining Foundations of Software Engineering

Formal Methods, Verification, and Model Checking Programming Languages, Type Systems, and Semantics Neuro Symbolic AI and Logic Guided Learning

Machine Learning, AI and Knowledge Discovery

Large Scale Machine Learning and Deep Learning Generative AI, LLMs, and Autonomous AI Agents

Retrieval Augmented Generation (RAG) Systems and Evaluation Multimodal, Self-Supervised, and Transfer Learning Explainable, Trustworthy, and Responsible AI

Knowledge Graphs, Knowledge Based Systems, and Reasoning Privacy Preserving ML (Federated Learning, Differential Privacy) Causal Machine Learning and Causal Discovery

AI for Software Engineering (AI4SE)

AI Driven Code Generation, Completion, and Synthesis Automated Software Testing, Debugging, and Repair

AI Assisted Refactoring, Optimization, and Maintenance Prompt Engineering and Prompt Based SE Workflows Benchmarking and Evaluation of AI Models for SE

Autonomous SE Agents for Planning, Coding, Testing, and Deployment Human AI Collaboration in Software Development

Software Engineering for AI Systems (SE4AI)

Engineering LLM Based Applications and AI Native Systems Guardrails, Hallucination Mitigation, and Safety Layers

Data Centric AI and Data Quality Engineering

MLOps, DataOps, and Continuous Delivery for ML Systems

ML System Observability, Drift Detection, and AI Incident Response AI Governance, Risk, and Compliance Engineering

Data Driven Software Engineering

Mining Software Repositories (MSR)

Empirical Software Engineering and Evidence Based Methods Developer Productivity, Behavior, and Cognitive Analytics Socio Technical Systems and Collaboration Analytics Software Analytics and Data Driven Decision Making Technical Debt Detection, Prediction, and Management

Continuous Experimentation, A/B Testing, and Causal Inference in SE

Software Architecture, Systems and Platforms

Cloud Native Software Engineering and Distributed Systems Microservices, Serverless Computing, and Containerization Edge, IoT, and Embedded Software Systems

Cyber Physical and Real Time Systems Observability, Telemetry, and Runtime Analytics Performance Engineering and Optimization

Quantum Software Engineering and Quantum Programming Tools

Software Quality, Testing and Reliability

Automated Test Generation, Fuzzing, and Mutation Testing Software Reliability, Resilience, and Dependability Software Maintenance, Evolution, and Reengineering Quality Assurance, Metrics, and Continuous Improvement Performance, Scalability, and Stress Testing

Security, Privacy and Trust

Software Security and Vulnerability Detection Secure Software Supply Chains and DevSecOps

Threat Modeling, Attack Simulation, and Security Testing Adversarial ML, Robustness, and AI Safety

Trustworthy Software Systems and Compliance

Web, Search, Mobile and Emerging Platforms

Web Scale Systems and Web Engineering

Search Engines, Information Retrieval, and Recommendation Systems

Mobile, Ubiquitous, and Context Aware Computing AR/VR, Immersive Systems, and Interactive Software

Blockchain, Smart Contracts, and Decentralized Applications

Applications, Domains and Interdisciplinary Areas

Data Mining Applications in Healthcare, Finance, Education, and Smart Cities Learning Analytics, Educational Data Mining, and AI in Education Sustainable and Green Software Engineering

Multimedia Systems, Vision Driven Applications, and Multimodal Analytics Social Computing, Digital Ecosystems, and Human Centered AI

Paper Submission

Authors are invited to submit papers through the conference Submission System by June 20, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings (H index 46) in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from DMSE 2026, after further revisions, will be published in the special issue of the following journal.