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Programming Languages and Compilers Commons™
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- Software Engineering (3)
- Programming languages (2)
- Analogical modeling (1)
- Artificial intelligence tools (1)
- Automated ontology generation (1)
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- Bioinformatics (1)
- Call Graphs (1)
- Cantonese tone recognition (1)
- Cognitive robotics (1)
- Computer code (1)
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- Conceptual ontologies (1)
- Exemplar-based approach (1)
- Feature selection and extraction (1)
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- Lexical and terminological resources (1)
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- Memory-based learning (1)
- Natural language (1)
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- Neural networks (1)
- Ontology engineering (1)
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- Static Analysis (1)
Articles 1 - 9 of 9
Full-Text Articles in Programming Languages and Compilers
Evaluating A Large Language Model’S Ability To Solve Programming Exercises From An Introductory Bioinformatics Course, Stephen R. Piccolo, Paul Denny, Andrew Luxton-Reilly, Samuel H. Payne, Perry G. Ridge
Evaluating A Large Language Model’S Ability To Solve Programming Exercises From An Introductory Bioinformatics Course, Stephen R. Piccolo, Paul Denny, Andrew Luxton-Reilly, Samuel H. Payne, Perry G. Ridge
Faculty Publications
Life scientists frequently write computer code when doing research. Computer programming can aid researchers in performing tasks that are not supported by existing tools. Programming can also help researchers to implement analytical logic in a way that documents their steps and thus enables others to repeat those steps. Many educational resources are available to teach computer programming, but this skill remains challenging for many researchers and students to master. Artificial-intelligence tools like OpenAI’s ChatGPT are able to interpret human-language requests to generate code. Accordingly, we evaluated the extent to which this technology might be used to perform programming tasks described …
Lightweight Call-Graph Construction For Multilingual Software Analysis, Anne-Marie Bogar, Damian Lyons, David Baird
Lightweight Call-Graph Construction For Multilingual Software Analysis, Anne-Marie Bogar, Damian Lyons, David Baird
Faculty Publications
Analysis of multilingual codebases is a topic of increasing importance. In prior work, we have proposed the MLSA (MultiLingual Software Analysis) architecture, an approach to the lightweight analysis of multilingual codebases, and have shown how it can be used to address the challenge of constructing a single call graph from multilingual software with mutual calls. This paper addresses the challenge of constructing monolingual call graphs in a lightweight manner (consistent with the objective of MLSA) which nonetheless yields sufficient information for resolving language interoperability calls. A novel approach is proposed which leverages information from …
Lightweight Multilingual Software Analysis, Damian Lyons, Anne Marie Bogar, David Baird
Lightweight Multilingual Software Analysis, Damian Lyons, Anne Marie Bogar, David Baird
Faculty Publications
Large software systems can often be multilingual – that is, software systems are written in more than one language. However, many popular software engineering tools are monolingual by nature. Nonetheless, companies are faced with the need to manage their large, multilingual codebases to address issues with security, efficiency, and quality metrics. This paper presents a novel lightweight approach to multilingual software analysis – MLSA. The approach is modular and focused on efficient static analysis computation for large codebases. One topic is addressed in detail – the generation of multilingual call graphs to identify language boundary problems in multilingual code. The …
Lightweight Multilingual Software Analysis, Damian Lyons, Anne Marie Bogar, David Baird
Lightweight Multilingual Software Analysis, Damian Lyons, Anne Marie Bogar, David Baird
Faculty Publications
Developer preferences, language capabilities and the persistence of older languages contribute to the trend that large software codebases are often multilingual – that is, written in more than one computer language. While developers can leverage monolingual software development tools to build software components, companies are faced with the problem of managing the resultant large, multilingual codebases to address issues with security, efficiency, and quality metrics. The key challenge is to address the opaque nature of the language interoperability interface: one language calling procedures in a second (which may call a third, or even back to the first), resulting in a …
A Cognitive Robotics Approach To Comprehending Human Language And Behaviors, Deryle W. Lonsdale, D. Paul Benjamin, Damian Lyons
A Cognitive Robotics Approach To Comprehending Human Language And Behaviors, Deryle W. Lonsdale, D. Paul Benjamin, Damian Lyons
Faculty Publications
The ADAPT project is a collaboration of researchers in linguistics, robotics and artificial intelligence at three universities. We are building a complete robotic cognitive architecture for a mobile robot designed to interact with humans in a range of environments, and which uses natural language and models human behavior. This paper concentrates on the HRI aspects of ADAPT, and especially on how ADAPT models and interacts with humans.
Generating Ontologies Via Language Components And Ontology Reuse, Deryle W. Lonsdale, Yihong Ding, David W. Embley, Martin Hepp, Li Xu
Generating Ontologies Via Language Components And Ontology Reuse, Deryle W. Lonsdale, Yihong Ding, David W. Embley, Martin Hepp, Li Xu
Faculty Publications
Realizing the Semantic Web involves creating ontologies, a tedious and costly challenge. Reuse can reduce the cost of ontology engineering. Semantic Web ontologies can provide useful input for ontology reuse. However, the automated reuse of such ontologies remains underexplored. This paper presents a generic architecture for automated ontology reuse. With our implementation of this architecture, we show the practicality of automating ontology generation through ontology reuse. We experimented with a large generic ontology as a basis for automatically generating domain ontologies that fit the scope of sample natural-language web pages. The results were encouraging, resulting in five lessons pertinent to …
Analogical Modeling: An Update, Deryle W. Lonsdale, David Eddington
Analogical Modeling: An Update, Deryle W. Lonsdale, David Eddington
Faculty Publications
Analogical modeling is a supervised exemplar-based approach that has been widely applied to predict linguistic behavior. The paradigm has been well documented in the linguistics and cognition literature, but is less well known to the machine learning community. This paper sets out some of the basics of the approach, including a simplified example of the fundamental algorithm’s operation. It then surveys some of the recent analogical modeling language applications, and sketches how the computational system has been enhanced lately to offer users increased flexibility and processing power. Some comparisons and contrasts are drawn between analogical modeling and other language modeling …
A Memory-Based Approach To Cantonese Tone Recognition, Deryle W. Lonsdale, Michael Emonts
A Memory-Based Approach To Cantonese Tone Recognition, Deryle W. Lonsdale, Michael Emonts
Faculty Publications
This paper introduces memory-based learning as a viable approach for Cantonese tone recognition. The memorybased learning algorithm employed here outperforms other documented current approaches for this problem, which is based on neural networks. Various numbers of tones and features are modeled to find the best method for feature selection and extraction. To further optimize this approach, experiments are performed to isolate the best feature weighting method, the best class voting weights method, and the best number of k-values to implement. Results and possible future work are discussed.
Peppering Knowledge Sources With Salt: Boosting Conceptual Content For Ontology Generation, Deryle W. Lonsdale, Yihong Ding, David W. Embley, Alan Melby
Peppering Knowledge Sources With Salt: Boosting Conceptual Content For Ontology Generation, Deryle W. Lonsdale, Yihong Ding, David W. Embley, Alan Melby
Faculty Publications
This paper describes work done to explore the common ground between two different ongoing research projects: the standardization of lexical and terminological resources, and the use of conceptual ontologies for information extraction and data integration. Specifically, this paper explores improving the generation of extraction ontologies through use of a comprehensive terminology database that has been represented in a standardized format for easy tool-based implementation. We show how, via the successful integration of these two distinct efforts, it is possible to leverage large-scale terminological and conceptual information having relationship-rich semantic resources in order to reformulate, match, and merge retrieved information of …