The Experts below are selected from a list of 10263 Experts worldwide ranked by ideXlab platform
Marc Alexander - One of the best experts on this subject based on the ideXlab platform.
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Programming Language Feature agglomeration
Proceedings of the 1st Workshop on Programming Language Evolution, 2014Co-Authors: Jeremy Singer, Callum Cameron, Marc AlexanderAbstract:Feature-creep is a well-known phenomenon in software systems. In this paper, we argue that Feature-creep also occurs in the domain of Programming Languages. Recent Languages are more expressive than earlier Languages. However recent Languages generally extend rather than replace the syntax (sometimes) and semantics (almost always) of earlier Languages. We demonstrate this trend of agglomeration in a sequence of Languages comprising Pascal, C, Java, and Scala. These are all block-structured Algol-derived Languages, with earlier Languages providing explicit inspiration for later ones. We present empirical evidence from several Language-specific sources, including grammar definitions and canonical manuals. The evidence suggests that there is a trend of increasing complexity in modern Languages that have evolved from earlier Languages.
Hoan Anh Nguyen - One of the best experts on this subject based on the ideXlab platform.
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demonstrating Programming Language Feature mining using boa
International Conference on Systems, 2015Co-Authors: Robert Dyer, Hridesh Rajan, Tien N Nguyen, Hoan Anh NguyenAbstract:Programming Language researchers often study real-world projects to see how Language Features have been adopted and are being used. Typically researchers choose a small number of projects to study, due to the immense challenges associated with finding, downloading, storing, processing, and querying large amounts of data. The Boa Programming Language and infrastructure was designed to solve these challenges and allow researchers to focus on simply asking the right questions. Boa provides a domain-specific Language to abstract details of how to mine hundreds of thousands of projects and also abstracts how to efficiently query that data. We have previously used this platform to perform a large study of the adoption of Java's Language Features over time. In this demonstration, we will show you how we used Boa to quickly analyze billions of AST nodes and study the adoption of Java's Language Features.
Renchu Guan - One of the best experts on this subject based on the ideXlab platform.
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A comparative study for biomedical named entity recognition
International Journal of Machine Learning and Cybernetics, 2015Co-Authors: Xu Wang, Chen Yang, Renchu GuanAbstract:With high-throughput technologies applied in biomedical research, the quantity of biomedical literatures grows exponentially. It becomes more and more important to quickly as well as accurately extract knowledge from manuscripts, especially in the era of big data. Named entity recognition (NER), aiming at identifying chunks of text that refers to specific entities, is essentially the initial step for information extraction. In this paper, we will review the three models of biomedical NER and two famous machine learning methods, Hidden Markov Model and Conditional Random Fields, which have been widely applied in bioinformatics. Based on these two methods, six excellent biomedical NER tools are compared in terms of Programming Language, Feature sets, underlying mathematical methods, post-processing techniques and flowcharts. Experimental results of these tools against two widely used corpora, GENETAG and JNLPBA, are conducted. The comparison varies from different entity types to the overall performance. Furthermore, we put forward suggestions about the selection of Bio-NER tools for different applications.
Jeremy Singer - One of the best experts on this subject based on the ideXlab platform.
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Programming Language Feature agglomeration
Proceedings of the 1st Workshop on Programming Language Evolution, 2014Co-Authors: Jeremy Singer, Callum Cameron, Marc AlexanderAbstract:Feature-creep is a well-known phenomenon in software systems. In this paper, we argue that Feature-creep also occurs in the domain of Programming Languages. Recent Languages are more expressive than earlier Languages. However recent Languages generally extend rather than replace the syntax (sometimes) and semantics (almost always) of earlier Languages. We demonstrate this trend of agglomeration in a sequence of Languages comprising Pascal, C, Java, and Scala. These are all block-structured Algol-derived Languages, with earlier Languages providing explicit inspiration for later ones. We present empirical evidence from several Language-specific sources, including grammar definitions and canonical manuals. The evidence suggests that there is a trend of increasing complexity in modern Languages that have evolved from earlier Languages.
Rem W Collier - One of the best experts on this subject based on the ideXlab platform.
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a Feature model of actor agent functional object and procedural Programming Languages
Science of Computer Programming, 2015Co-Authors: Howell Jordan, Goetz Botterweck, John Noll, Andrew Butterfield, Rem W CollierAbstract:Abstract The number of Programming Languages is large and steadily increasing. However, little structured information and empirical evidence is available to help software engineers assess the suitability of a Language for a particular development project or software architecture. We argue that these shortages are partly due to a lack of high-level, objective Programming Language Feature assessment criteria: existing advice to practitioners is often based on ill-defined notions of ‘paradigms’ [3, p. xiii] and ‘orientation’, while researchers lack a shared common basis for generalisation and synthesis of empirical results. This paper presents a Feature model constructed from the programmer's perspective, which can be used to precisely compare general-purpose Programming Languages in the actor-oriented, agent-oriented, functional, object-oriented, and procedural categories. The Feature model is derived from the existing literature on general concepts of Programming, and validated with concrete mappings of well-known Languages in each of these categories. The model is intended to act as a tool for both practitioners and researchers, to facilitate both further high-level comparative studies of Programming Languages, and detailed investigations of Feature usage and efficacy in specific development contexts.
