D-Index & Metrics Best Publications

Andrian Marcus

The University of Texas at Dallas
United States

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 58 Citations 12,335 139 World Ranking 2415 National Ranking 1297

Research.com Recognitions

Awards & Achievements

2011 - ACM Senior Member

Overview

What is he best known for?

The fields of study Andrian Marcus is best known for:

Gene
Enzyme
Amino acid

Andrian Marcus merges Programming language with Theoretical computer science in his research. Andrian Marcus performs integrative Theoretical computer science and Programming language research in his work. Andrian Marcus regularly ties together related areas like Object (grammar) in his Artificial intelligence studies. His Object (grammar) study frequently draws connections to adjacent fields such as Artificial intelligence. As part of his studies on Gene, Andrian Marcus often connects relevant areas like clone (Java method). In his works, Andrian Marcus performs multidisciplinary study on Data mining and Natural language processing. He combines Natural language processing and Data mining in his research. He regularly ties together related areas like Germ in his Cell biology studies. His studies link Cell biology with Germ.

His most cited work include:

Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval (416 citations)
Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems (277 citations)
Local versus Global Lessons for Defect Prediction and Effort Estimation (221 citations)

What are the main themes of his work throughout his whole career to date

His study on Biochemistry is mostly dedicated to connecting different topics, such as Wheat germ. In his work, Andrian Marcus performs multidisciplinary research in Gene and Molecular biology. Andrian Marcus undertakes multidisciplinary investigations into Molecular biology and Gene in his work. His work on RNA is being expanded to include thematically relevant topics such as Genetics. His study ties his expertise on Messenger RNA together with the subject of Genetics. Andrian Marcus merges Messenger RNA with Ribosome in his study. He conducted interdisciplinary study in his works that combined Ribosome and Enzyme. He undertakes multidisciplinary studies into Enzyme and RNA in his work. His research brings together the fields of Embryo and Cell biology.

Andrian Marcus most often published in these fields:

Biochemistry (48.89%)
Gene (46.67%)
RNA (37.78%)

What were the highlights of his more recent work (between 2006-2013)?

Artificial intelligence (60.00%)
Data mining (60.00%)
Machine learning (40.00%)

In recent works Andrian Marcus was focusing on the following fields of study:

His Artificial intelligence study frequently links to related topics such as Adversarial information retrieval. Adversarial information retrieval is frequently linked to Cognitive models of information retrieval in his study. Many of his studies on Cognitive models of information retrieval involve topics that are commonly interrelated, such as Machine learning. Many of his studies involve connections with topics such as Ranking (information retrieval) and Machine learning. Andrian Marcus performs multidisciplinary study on Ranking (information retrieval) and Information retrieval in his works. Andrian Marcus performs multidisciplinary study in the fields of Information retrieval and Human–computer information retrieval via his papers. His work on Artificial intelligence expands to the thematically related Human–computer information retrieval. Andrian Marcus integrates many fields in his works, including Data mining and Natural language processing. He integrates Natural language processing with Data mining in his research.

Between 2006 and 2013, his most popular works were:

Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval (416 citations)
Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems (277 citations)
Local versus Global Lessons for Defect Prediction and Effort Estimation (221 citations)

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.

Best Publications

Recovering documentation-to-source-code traceability links using latent semantic indexing

Andrian Marcus;Jonathan I. Maletic.
international conference on software engineering (2003)

977 Citations

An information retrieval approach to concept location in source code

A. Marcus;A. Sergeyev;V. Rajlich;J.I. Maletic.
working conference on reverse engineering (2004)

645 Citations

Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

D. Poshyvanyk;Y.-G. Gueheneuc;A. Marcus;G. Antoniol.
IEEE Transactions on Software Engineering (2007)

603 Citations

Identification of high-level concept clones in source code

A. Marcus;J.I. Maletic.
automated software engineering (2001)

395 Citations

Automated severity assessment of software defect reports

T. Menzies;A. Marcus.
international conference on software maintenance (2008)

374 Citations

Data Cleansing: Beyond Integrity Analysis 1

Jonathan I. Maletic;Andrian Marcus.
IQ (2000)

368 Citations

Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems

A. Marcus;D. Poshyvanyk;R. Ferenc.
IEEE Transactions on Software Engineering (2008)

358 Citations

Combining Formal Concept Analysis with Information Retrieval for Concept Location in Source Code

D. Poshyvanyk;A. Marcus.
international conference on program comprehension (2007)

328 Citations

Supporting program comprehension using semantic and structural information

Jonathan I. Maletic;Andrian Marcus.
international conference on software engineering (2001)

319 Citations

On the Use of Automated Text Summarization Techniques for Summarizing Source Code

Sonia Haiduc;Jairo Aponte;Laura Moreno;Andrian Marcus.
working conference on reverse engineering (2010)

306 Citations

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