Alexander Serebrenik mainly investigates Software, Software development, World Wide Web, Data mining and Knowledge management. His work deals with themes such as Sentiment analysis, Process mining, Soft skills and Software engineering, which intersect with Software. His work in Software development addresses issues such as Social media, which are connected to fields such as Development team and Knowledge-based systems.
His World Wide Web research is multidisciplinary, incorporating elements of Scalability, Open source development, Open source, Social coding and Popularity. His studies deal with areas such as Software maintenance, Software metric, Anger, Collaborative software development and Collaborative software as well as Data mining. The concepts of his Knowledge management study are interwoven with issues in Regression analysis, Open source software and Software development process.
His primary areas of study are Software engineering, Programming language, Software, Software development and Theoretical computer science. His Software engineering study deals with Software quality intersecting with Quality. The Software study combines topics in areas such as Sentiment analysis, Maintainability and Data science.
His study in Software development is interdisciplinary in nature, drawing from both World Wide Web and Knowledge management. He combines subjects such as Algorithm, Correctness and Petri net with his study of Theoretical computer science. His Software evolution study, which is part of a larger body of work in Software system, is frequently linked to Automotive industry, bridging the gap between disciplines.
His primary scientific interests are in Software, Software engineering, Software development, Data science and Empirical research. His Software study incorporates themes from Personal wellbeing and Source code. His Source code study improves the overall literature in Programming language.
His research in the fields of Domain overlaps with other disciplines such as Interview study. His Data science research is multidisciplinary, relying on both Sentiment analysis and Software quality. His Java research includes elements of Actuarial science and Theoretical computer science.
Software, Software development, Data science, Software engineering and Open source are his primary areas of study. The various areas that Alexander Serebrenik examines in his Software study include Group dynamic and Root cause. His research integrates issues of Software bug and Internet privacy in his study of Software development.
His Data science study combines topics in areas such as Agile software development, Code smell and Software evolution. His Software engineering research is multidisciplinary, incorporating perspectives in Sentiment analysis, Computational linguistics and Leverage. His work carried out in the field of Open source brings together such families of science as Maintenance engineering and Process management.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Process Discovery using Integer Linear Programming
J. M. E. M. van derWerf;B. F. van Dongen;C. A. J. Hurkens;A. Serebrenik.
applications and theory of petri nets (2009)
StackOverflow and GitHub: Associations between Software Development and Crowdsourced Knowledge
Bogdan Vasilescu;Vladimir Filkov;Alexander Serebrenik.
international conference on social computing (2013)
Gender and Tenure Diversity in GitHub Teams
Bogdan Vasilescu;Daryl Posnett;Baishakhi Ray;Mark G.J. van den Brand.
human factors in computing systems (2015)
How social Q&A sites are changing knowledge sharing in open source software communities
Bogdan Vasilescu;Alexander Serebrenik;Prem Devanbu;Vladimir Filkov.
conference on computer supported cooperative work (2014)
Rewriting aggregate queries using views
Sara Cohen;Werner Nutt;Alexander Serebrenik.
symposium on principles of database systems (1999)
Process discovery using integer linear programming
J.M.E.M. van der Werf;B.F. van Dongen;K.M. van Hee;C.A.J. Hurkens.
Computer science reports (2008)
Lean GHTorrent: GitHub data on demand
Georgios Gousios;Bogdan Vasilescu;Alexander Serebrenik;Andy Zaidman.
mining software repositories (2014)
Process Mining Software Repositories
Wouter Poncin;Alexander Serebrenik;Mark van den Brand.
conference on software maintenance and reengineering (2011)
Security and emotion: sentiment analysis of security discussions on GitHub
Daniel Pletea;Bogdan Vasilescu;Alexander Serebrenik.
mining software repositories (2014)
EnTagRec ++: An enhanced tag recommendation system for software information sites
Shaowei Wang;David Lo;Bogdan Vasilescu;Alexander Serebrenik.
Empirical Software Engineering (2018)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: