2019 - IEEE Fellow For contributions to ubiquitous and immersive programming
Her primary areas of study are Source code, Java, Programming language, Code and Wireless. Her research in Source code intersects with topics in KPI-driven code analysis, Source lines of code, Database and Code generation. The study incorporates disciplines such as AspectJ, Application software, Software engineering, Implementation and Exception handling in addition to Java.
Her Software engineering research is multidisciplinary, incorporating elements of Functional programming, Software system and Aspect-oriented software development. Her study in the field of Software development is also linked to topics like Information theory. Her Software development research incorporates elements of Aspect-oriented programming, Join point, Pointcut, Metaprogramming and Algorithm.
Her scientific interests lie mostly in Source code, Java, Programming language, Software and Code. Her study on Java also encompasses disciplines like
Cristina V. Lopes focuses mostly in the field of Software development, narrowing it down to topics relating to Software engineering and, in certain cases, Separation of concerns. Her work in Code covers topics such as Information retrieval which are related to areas like World Wide Web. The study of Aspect-oriented programming is intertwined with the study of Object-oriented programming in a number of ways.
Cristina V. Lopes mainly investigates Java, Source code, Code, Programming language and Software. The concepts of her Java study are interwoven with issues in Python, Database, Software quality, Software metric and Code refactoring. Her Source code research focuses on subjects like Data mining, which are linked to Component.
Cristina V. Lopes has researched Code in several fields, including Block, Scalability and Information retrieval. Cristina V. Lopes combines subjects such as Software development, Heuristics and Benchmark with her study of Block. Her work deals with themes such as Machine learning, Resource and Scripting language, which intersect with Software.
Cristina V. Lopes mostly deals with Source code, Java, Code, Information retrieval and Software. Her Source code research is multidisciplinary, relying on both Software quality, Database and Static program analysis. Her study with Java involves better knowledge in Programming language.
In Code, Cristina V. Lopes works on issues like KPI-driven code analysis, which are connected to Index, Resource and Static analysis. The various areas that Cristina V. Lopes examines in her Information retrieval study include Adaptation, Process and Taxonomy. Her study involves Software system and Software development, a branch of Software.
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Lodewijk Bergmans;Cristina Videira Lopes.
workshop on object oriented technology (1999)
C. Lopes;G. Kiczales.
technology of object oriented languages and systems (2000)
Making sense of sensing systems: five questions for designers and researchers
Victoria Bellotti;Maribeth Back;W. Keith Edwards;Rebecca E. Grinter.
human factors in computing systems (2002)
D: A Language Framework for Distributed Programming
Cristina Videira Lopes;Gregor Kiczales.
A study on exception detection and handling using aspect-oriented programming
Martin Lippert;Cristina Videira Lopes.
international conference on software engineering (2000)
A survey, classification and comparative analysis of medium access control protocols for ad hoc networks
R. Jurdak;C.V. Lopes;P. Baldi.
IEEE Communications Surveys and Tutorials (2004)
SourcererCC: scaling code clone detection to big-code
Hitesh Sajnani;Vaibhav Saini;Jeffrey Svajlenko;Chanchal K. Roy.
international conference on software engineering (2016)
Sourcerer: a search engine for open source code supporting structure-based search
Sushil Bajracharya;Trung Ngo;Erik Linstead;Yimeng Dou.
conference on object-oriented programming systems, languages, and applications (2006)
Sourcerer: mining and searching internet-scale software repositories
Erik Linstead;Sushil Bajracharya;Trung Ngo;Paul Rigor.
Data Mining and Knowledge Discovery (2009)
Adaptive Low Power Listening for Wireless Sensor Networks
R. Jurdak;P. Baldi;C.V. Lopes.
IEEE Transactions on Mobile Computing (2007)
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