Research Track

The goal of the CoSEDS 2022 is to provide a platform for all stakeholders in these fields from both academia and industry to present their work and explore the latest developments in the area of Software Engineering, the interdisciplinary field of Data Sciences and other allied fields. CoSEDS 2022 seeks contributions of different types, including theoretical foundations, practical techniques, new ideas, empirical studies, experience, and lessons learned. Submissions will be evaluated based on their scientific merit, importance, novelty, presentation, quality and relevance to Software Engineering and Data Sciences. We invite submissions under three categories: Regular papers, Short papers and Work in Progress/ Position Papers.

Regular papers should not exceed 11 pages, 10 pages for the main text (including figures, appendix etc.) and 1 page for references. 

 • Short papers should not exceed 6 pages, including references.

 • Work in Progress or Position papers should not exceed 2 pages, including references.

Regular papers are expected to contain in-depth descriptions of the work along with detailed evaluation and/or representing a self-contained theoretical contribution. Short papers may contain preliminary results, brief accounts of original ideas, and other relevant work of potentially high scientific interest; for example, new interesting ideas, which may not be evaluated extensively, tool descriptions or case studies. Work in progress or Position papers are expected to describe ideas and proposals that the author(s) would like to present at the conference.


 1. Regular papers will be assigned a long time slot for presentation than short and WIP/position papers.

 2. The papers will be accepted or rejected in the category in which they were submitted; there will be no "demotions" from a Regular to a Short paper or WIP/ Position Paper.

All submissions will be reviewed by at-least three members of Program Committee on the basis of technical quality, relevance to conference topics of interest, originality, significance, and clarity.

Submission site:


CoSEDS 2022 seeks contributions of different types, including theoretical foundations, practical techniques, new ideas, empirical studies, experience, and lessons learned in the areas of Software Engineering, interdisciplinary field of Data Sciences and intersection of Software engineering and Data Sciences. We welcome submissions addressing potential and relevant topics across the full spectrum of software engineering and Data Sciences, including, but not limited to:


Agile software development Middleware, frameworks, and APIs Security, privacy and trust
Autonomic and self-adaptive systems Mining software engineering repositories Software architecture
Cloud computing Mobile applications Software economics and metrics
Component-based software engineering Model-driven engineering Software evolution and maintenance
Configuration management and deployment Parallel, distributed, and concurrent systems Software modeling and design
Cooperative, distributed, and collaborative
software engineering
Performance Software process
Cyber physical systems Probabilistic systems Software product lines
Debugging, fault localization, and repair Program analysis Software reuse
Dependability, safety, and reliability Program comprehension Software services
Embedded software Program synthesis Software testing
Empirical software engineering Programming languages Software visualization
End-user software engineering Recommendation systems Specification and modeling languages
Formal methods Refactoring Tools and environments
Green and sustainable technologies Requirements engineering Traceability
Human factors and social aspects of software engineering Reverse engineering Ubiquitous/pervasive software systems
Human-computer interaction Search-based software engineering Validation and verification


Algorithms For Large Data Sets Data, Text, Web Mining,
and Visualization
Big Data Databases and Data Security  
Business Intelligence Deep learning and deep analytics.  
Cluster, Cloud, And Grid Computing Distributed computing and parallel processing  
Complexity Science Feature selection, transformation and construction.  
Data Analytics High performance computing for data analytics  
Data Architecture Infrastructure and storage  
Data Centric Programming Large scale optimization.  
Data Management Latent semantics and insight learning
Data Mining And Knowledge Discovery Machine learning
Data Science And Social Science. Machine learning theories, models and systems.
Data Warehouses And Large-Scale Databases. Management, storage, retrieval and search
Mathematical, probabilistic and statistical models Web/online/social/network mining and learning
Network science Relation, coupling, link and graph mining.
Security, privacy and ethics Security, trust and risk in big data.


Software Engineering for Data Science: Software Engineering challenges imposed by Data Science.
Data Science for Software Engineering: Opportunities that Data Science offers to software engineering, both in research and practice.
Data Science for improved Quality Assurance.
Engineering Better Quality Data Intensive Systems.



A number of rejections are done due to plagiarism in papers submitted to journals and Conferences. This is against professional ethics and we have no options, but to desk reject the paper. Hence authors are requested to take extreme care in avoiding any forms of plagiarism. If a paper is found to be plagiarized at any point of time, the organizers have right to withdraw the papers and disqualify the authors without any further notice.