Mika V. Mäntylä spends much of his time researching Software engineering, Software, Data science, Systematic review and Software development. The Software engineering study combines topics in areas such as Empirical research and Software quality, Code smell. His Code smell study deals with Artificial intelligence intersecting with Machine learning.
His Software research focuses on Maintainability and how it connects with Software metric. His Data science research incorporates themes from Topic model, Sentiment analysis, Subjectivity analysis and Computational linguistics. His work on Software development process as part of general Software development study is frequently linked to Research program, therefore connecting diverse disciplines of science.
Mika V. Mäntylä mainly investigates Software, Software engineering, Data science, Software development and Test. His Software study combines topics from a wide range of disciplines, such as Sentiment analysis, Root cause analysis and Source code. His biological study spans a wide range of topics, including Quality, Empirical research and Software quality, Code smell.
His Data science research integrates issues from Topic model and Software repository. His research investigates the link between Software development and topics such as Agile software development that cross with problems in Software development process. His Test research is multidisciplinary, incorporating elements of Exploratory testing, Manual testing and Knowledge management.
The scientist’s investigation covers issues in Software, Software engineering, Source code, Software development and Data science. His studies in Software integrate themes in fields like Sentiment analysis, World Wide Web and Engineering management. The concepts of his Software engineering study are interwoven with issues in Quality, Pipeline and Natural language.
His Quality research is multidisciplinary, relying on both Software quality and Process. While the research belongs to areas of Software development, Mika V. Mäntylä spends his time largely on the problem of Agile software development, intersecting his research to questions surrounding Lean manufacturing, Software development process and Software deployment. The various areas that Mika V. Mäntylä examines in his Data science study include Set, Unit of analysis and Software repository.
Mika V. Mäntylä mostly deals with Software engineering, Software, Software development, Empirical research and Quality. Mika V. Mäntylä undertakes interdisciplinary study in the fields of Software engineering and Grey literature through his works. Mika V. Mäntylä regularly ties together related areas like Sentiment analysis in his Software studies.
His study in Software development is interdisciplinary in nature, drawing from both Agile software development and DevOps. His Empirical research research includes themes of Data science and Software repository. His work on Quality assurance as part of general Quality study is frequently linked to Systematic review, bridging the gap between disciplines.
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The evolution of sentiment analysis—A review of research topics, venues, and top cited papers
Mika Viking Mäntylä;Daniel Graziotin;Miikka Kuutila.
Computer Science Review (2018)
Guidelines for including grey literature and conducting multivocal literature reviews in software engineering
Vahid Garousi;Michael Felderer;Michael Felderer;Mika V. Mäntylä.
Information & Software Technology (2019)
Comparing and experimenting machine learning techniques for code smell detection
Francesca Arcelli Fontana;Mika V. Mäntylä;Marco Zanoni;Alessandro Marino.
Empirical Software Engineering (2016)
Benefits and limitations of automated software testing: systematic literature review and practitioner survey
Dudekula Mohammad Rafi;Katam Reddy Kiran Moses;Kai Petersen;Mika V. Mantyla.
automation of software test (2012)
Using metrics in Agile and Lean Software Development - A systematic literature review of industrial studies
Eetu Kupiainen;Mika V. Mäntylä;Juha Itkonen.
Information & Software Technology (2015)
A taxonomy and an initial empirical study of bad smells in code
M. Mantyla;J. Vanhanen;C. Lassenius.
What Types of Defects Are Really Discovered in Code Reviews
M.V. Mantyla;C. Lassenius.
Perceived causes of software project failures - An analysis of their relationships
Timo O. A. Lehtinen;Mika V. Mäntylä;Jari Vanhanen;Juha Itkonen.
The Highways and Country Roads to Continuous Deployment
Marko Leppanen;Simo Makinen;Max Pagels;Veli-Pekka Eloranta.
IEEE Software (2015)
The need for multivocal literature reviews in software engineering: complementing systematic literature reviews with grey literature
Vahid Garousi;Michael Felderer;Mika V. Mäntylä.
evaluation and assessment in software engineering (2016)
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