The Experts below are selected from a list of 67572 Experts worldwide ranked by ideXlab platform
T. L. Jefferson - One of the best experts on this subject based on the ideXlab platform.
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ICSM - An empirical study of software maintenance of a Web-based Java Application
21st IEEE International Conference on Software Maintenance (ICSM'05), 2005Co-Authors: M.-g. Lee, T. L. JeffersonAbstract:This paper presents empirical study detailing software maintenance for Web-based Java Applications to aid in understanding and predicting the software maintenance category and effort. The specific Application described is a Java Web-based administrative Application in the e-Government arena. The Application is based on the design of an open source model-view-controller framework. The domain factors, which also provide contextual references, are described based on Kitchenham et al.'s software maintenance ontology. This paper characterizes the number of fault reports and maintenance effort for each maintenance category. This study finds that the distribution of software maintenance effort in this observed Web-based Java Application is similar to the distribution in previous software maintenance studies, which analyzed non object-oriented and non Web-based Applications.
C. Nicaud - One of the best experts on this subject based on the ideXlab platform.
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Seed: An Easy-to-Use Random Generator of Recursive Data Structures for Testing
2011 Fourth IEEE International Conference on Software Testing, Verification and Validation, 2011Co-Authors: Pierre-Cyrille Héam, C. NicaudAbstract:Random testing represents a simple and tractable way for software assessment. This paper presents the Seed tool that can be used for the uniform random generation of recursive data structures such as labelled trees and logical formulas. We show how Seed can be used in several testing contexts, from model based testing to performance testing. Generated data structures are defined by grammar-like rules, given in an XML format, multiplying Seed possible Applications. Seed is based on combinatorial techniques, and can generate uniformly at random k structures of size n with an efficient time complexity. Finally, Seed is available as a free Java Application and a great effort has been made to make it easy-to-use.
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Seed: an easy to use random generator of recursive data structures for testing
2009Co-Authors: Pierre-Cyrille Héam, C. NicaudAbstract:Random testing represents a simple and tractable way for software assessment. This paper presents the \seed tool that can be used for the uniform random generation of recursive data structures such as labelled trees and logical formulas. We show how \seed can be used in several testing contexts, from model based testing to performance testing. Generated data structures are defined by grammar-like rules, given in an XML format, multiplying \seed possible Applications. Seed is based on combinatorial techniques, and can generate uniformly at random k structures of size $n$ with a time complexity in O(n^2+ kn\log n). Finally, \seed is available as a free Java Application and a great effort has been made to make it easy-to-use.
Shudong Zhang - One of the best experts on this subject based on the ideXlab platform.
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sscmap an extensible Java Application for connecting small molecule drugs using gene expression signatures
arXiv: Quantitative Methods, 2009Co-Authors: Shudong Zhang, Timothy W GantAbstract:Background: Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. Results: This paper introduces sscMap (statistically significant connections' map), a Java Application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the Application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. Conclusions: The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from this http URL
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sscmap an extensible Java Application for connecting small molecule drugs using gene expression signatures
BMC Bioinformatics, 2009Co-Authors: Shudong Zhang, Timothy W GantAbstract:Background Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.
Timothy W Gant - One of the best experts on this subject based on the ideXlab platform.
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sscmap an extensible Java Application for connecting small molecule drugs using gene expression signatures
arXiv: Quantitative Methods, 2009Co-Authors: Shudong Zhang, Timothy W GantAbstract:Background: Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. Results: This paper introduces sscMap (statistically significant connections' map), a Java Application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the Application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. Conclusions: The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from this http URL
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sscmap an extensible Java Application for connecting small molecule drugs using gene expression signatures
BMC Bioinformatics, 2009Co-Authors: Shudong Zhang, Timothy W GantAbstract:Background Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.
M.-g. Lee - One of the best experts on this subject based on the ideXlab platform.
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ICSM - An empirical study of software maintenance of a Web-based Java Application
21st IEEE International Conference on Software Maintenance (ICSM'05), 2005Co-Authors: M.-g. Lee, T. L. JeffersonAbstract:This paper presents empirical study detailing software maintenance for Web-based Java Applications to aid in understanding and predicting the software maintenance category and effort. The specific Application described is a Java Web-based administrative Application in the e-Government arena. The Application is based on the design of an open source model-view-controller framework. The domain factors, which also provide contextual references, are described based on Kitchenham et al.'s software maintenance ontology. This paper characterizes the number of fault reports and maintenance effort for each maintenance category. This study finds that the distribution of software maintenance effort in this observed Web-based Java Application is similar to the distribution in previous software maintenance studies, which analyzed non object-oriented and non Web-based Applications.
