Data mining, Software engineering, Estimation, Cost estimate and Pair programming are her primary areas of study. Her studies in Data mining integrate themes in fields like Software metric, Stepwise regression, Regression analysis, Data set and Case-based reasoning. The study incorporates disciplines such as Agile usability engineering and Body of knowledge in addition to Software engineering.
The various areas that she examines in her Estimation study include Statistics, Tabu search, Support vector machine and Software development effort estimation. Her work carried out in the field of Cost estimate brings together such families of science as Empirical process, Cost estimation models, Web development and Web engineering. Her biological study spans a wide range of topics, including Big Five personality traits, Empirical research, Software design and Openness to experience.
Emilia Mendes mainly focuses on Data mining, Estimation, Software engineering, Context and Software. Emilia Mendes has researched Data mining in several fields, including Machine learning, Stepwise regression, Artificial intelligence, Case-based reasoning and Web development. Emilia Mendes combines subjects such as Knowledge management, Cost estimate, Bayesian network, Project management and Data science with her study of Estimation.
The Cost estimate study combines topics in areas such as Web application, Cost estimation models and Web engineering. Emilia Mendes interconnects Software verification and validation, Software development, Software construction and Empirical research in the investigation of issues within Software engineering. Her Software research incorporates themes from Predictive modelling and Set.
Context, Software engineering, Software, Systematic review and Value are her primary areas of study. Her research in Software engineering intersects with topics in Empirical research and Decision support system. Her Software study incorporates themes from Agile software development, Replication, Project management and Process management.
As a part of the same scientific family, Emilia Mendes mostly works in the field of Field, focusing on Data science and, on occasion, Web application. Visualization is a subfield of Data mining that Emilia Mendes investigates. Her work is dedicated to discovering how Data mining, Training set are connected with Machine learning and other disciplines.
Her main research concerns Context, Software engineering, Systematic review, Software and Systematic mapping. Her study of Context brings together topics like Quality and Software development. Her Software development research integrates issues from Management science, Service, Personality, Personality psychology and Set.
Many of her research projects under Software engineering are closely connected to Mechanism with Mechanism, tying the diverse disciplines of science together. She has included themes like Machine learning, Bayesian network, Data mining and Training set in her Software study. Her Bayesian network research incorporates elements of Critical success factor, Estimation, Project management, Product and Operations research.
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.
Cross versus Within-Company Cost Estimation Studies: A Systematic Review
B.A. Kitchenham;E. Mendes;G.H. Travassos.
Empirical Studies of Pair Programming for CS/SE Teaching in Higher Education: A Systematic Literature Review
N. Salleh;E. Mendes;J. Grundy.
IEEE Transactions on Software Engineering (2011)
A systematic review of software maintainability prediction and metrics
Mehwish Riaz;Emilia Mendes;Ewan Tempero.
empirical software engineering and measurement (2009)
A Comparative Study of Cost Estimation Models for Web Hypermedia Applications
Emilia Mendes;Ian Watson;Chris Triggs;Nile Mosley.
Empirical Software Engineering (2003)
Effort estimation in agile software development: a systematic literature review
Muhammad Usman;Emilia Mendes;Francila Weidt;Ricardo Britto.
predictive models in software engineering (2014)
Why comparative effort prediction studies may be invalid
Barbara Kitchenham;Emilia Mendes.
Web metrics - estimating design and authoring effort
E. Mendes;N. Mosley;S. Counsell.
IEEE MultiMedia (2001)
Further comparison of cross-company and within-company effort estimation models for Web applications
E. Mendes;B. Kitchenham.
Software productivity measurement using multiple size measures
B. Kitchenham;E. Mendes.
Nile Mosley;Emilia Mendes.
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