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IEEE/ACM 2nd International Workshop on Software Architecture and Metrics (SAM)

作者： McBurney, Paul W. Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781479919345

Programmers need software documentation. However, documentation is expensive to produce and maintain, and often becomes outdated over time. Programmers often lack the time and resources to write documentation. Therefore, automated solutions are desirable. Designers of automatic documentation tools are limited because there is not yet a clear understanding of what characteristics are important to generating high quality summaries. I propose three specific research objectives to improving automatic documentation generation. I propose to study the similarity between source code and summary. Second, I propose studying whether or not including contextual information about source code improves summary quality. Finally, I propose to study the problem of similarity in source code structure and source code documentation. This paper discusses my work on these three objectives towards my Ph.D. dissertation, including my preliminary and proposed work.

关键词： automatic documentation Software engineering Source code summarization

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automatic documentation of professional health interactions: A systematic review

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ARTIFICIAL INTELLIGENCE IN MEDICINE 2023年第1期137卷 102487-102487页

作者： Falcetta, Frederico Soares de Almeida, Fernando Kude Lemos, Janaina Conceicao Sutil Goldim, Jose Roberto da Costa, Cristiano Andre Univ Vale Rio Sinos Unisinos Software Innovat Lab Softwarelab Ave Unisinos 950 BR-93022750 Sao Leopoldo RS Brazil Hosp Femina Rua Mostardeiro 17 BR-90430001 Porto Alegre RS Brazil Hosp Clin Porto Alegre Rua Ramiro Barcelos 2350 BR-90035903 Porto Alegre RS Brazil

Electronic systems are increasingly present in the healthcare system and are often related to improved medical care. However, the widespread use of these technologies ended up building a relationship of dependence that can disrupt the doctor-patient relationship. In this context, digital scribes are automated clinical documentation systems that capture the physician-patient conversation and then generate the documentation for the appointment, enabling the physician to engage with the patient entirely. We have performed a systematic literature review on intelligent solutions for automatic speech recognition (ASR) with automatic documentation during a medical interview. The scope included only original research on systems that could detect speech and transcribe it in a natural and structured fashion simultaneously with the doctor-patient interaction, excluding speech-to-text-only technologies. The search resulted in a total of 1995 titles, with eight articles remaining after filtering for the inclusion and exclusion criteria. The intelligent models mainly consisted of an ASR system with natural language processing capability, a medical lexicon, and structured text output. None of the articles had a commercially available product at the time of the publication and reported limited real-life experience. So far, none of the applications has been prospectively validated and tested in large-scale clinical studies. Nonetheless, these first reports suggest that automatic speech recognition may be a valuable tool in the future to facilitate medical registration in a faster and more reliable manner. Improving transparency, accuracy, and empathy could drastically change how patients and doctors experience a medical visit. Unfortunately, clinical data on the usability and benefits of such applications is almost non-existent. We believe that future work in this area is necessary and needed.

关键词： EHR automatic documentation Neural networks

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automatic Source Code Summarization of Context for Java Methods

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2016年第2期42卷 103-119页

作者： McBurney, Paul W. McMillan, Collin Univ Notre Dame Coll Comp Sci & Engn Notre Dame IN 46556 USA Univ Notre Dame Comp Sci South Bend VA USA

Source code summarization is the task of creating readable summaries that describe the functionality of software. Source code summarization is a critical component of documentation generation, for example as Javadocs formed from short paragraphs attached to each method in a Java program. At present, a majority of source code summarization is manual, in that the paragraphs are written by human experts. However, new automated technologies are becoming feasible. These automated techniques have been shown to be effective in select situations, though a key weakness is that they do not explain the source code's context. That is, they can describe the behavior of a Java method, but not why the method exists or what role it plays in the software. In this paper, we propose a source code summarization technique that writes English descriptions of Java methods by analyzing how those methods are invoked. We then performed two user studies to evaluate our approach. First, we compared our generated summaries to summaries written manually by experts. Then, we compared our summaries to summaries written by a state-of-the-art automatic summarization tool. We found that while our approach does not reach the quality of human-written summaries, we do improve over the state-of-the-art summarization tool in several dimensions by a statistically-significant margin.

关键词： Source code summarization automatic documentation program comprehension

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SEMIautomatic PROGRAM CONSTRUCTION FROM SPECIFICATIONS USING LIBRARY MODULES

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1991年第9期17卷 853-871页

作者： NISHIDA, F TAKAMATSU, S FUJITA, Y TANI, T OITA UNIV FAC ENGNDEPT COMP SCI & INTELLIGENT SYSTOITAJAPAN UNIV OSAKA PREFECTURE FAC ENGNDEPT ELECT ENGNSAKAIOSAKA 591JAPAN

This paper describes a method of semi-automatic specification refinement and program generation using library modules. Users write their specifications, modify and rearrange them so that the specifications can be refined with the aid of the library modules. When a specification is given, a refinement system called MAPS searches for library modules applicable to the given specification, replaces the specification with a more detailed description written in the operation part of the modules, and converts the refined specification into a program written in a programming language designated by the user. Case-like expressions or pseudo-natural language expressions are used for describing user's specifications and specifications for library modules.

关键词： automatic documentation MULTILINGUAL TRANSLATION, NATURAL LANGUAGE REUSABLE MODULE SEMIautomatic LINKING SEMIautomatic REFINEMENT UNIFICATION

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Self-instructive spreadsheets: an environment for automatic knowledge acquisition and tutor generation

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INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES 2000年第5期52卷 775-803页

作者： Lentini, M Nardi, D Simonetta, A Univ Roma La Sapienza Dipartimento Informat & Sistemist I-00198 Rome Italy

Typically, spreadsheet applications are difficult to use for casual users (different from developers), mainly because of lack of support. In fact, building a tutoring facility for such applications is a time-consuming task. Our aim is the realization of a tool for the automatic generation of Intelligent Tutors for conventional spreadsheet applications. We have developed a system that works in two steps. In the first one, it extracts an explicit representation of the problem-solving pattern coded in a programmed spreadsheet. In the second step, it generates a hypertextual guide and an interactive tutor that can effectively support, in the native environment, the casual user of the spreadsheet with the specific application it is designed for. We have successfully tested our system on a class of students using an application for budget analysis. (C) 2000 Academic Press.

关键词： knowledge acquisition hypertext intelligent spreadsheets knowledge-based tutoring systems automatic documentation

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On the application of 3-D scanning technology for the documentation and typology of lithic artifacts

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JOURNAL OF ARCHAEOLOGICAL SCIENCE 2008年第12期35卷 3101-3110页

作者： Grosman, Leore Smikt, Oded Smilansky, Uzy Weizmann Inst Sci Dept Phys Complex Syst IL-76100 Rehovot Israel Hebrew Univ Jerusalem Inst Archaeol IL-91904 Jerusalem Israel Weizmann Inst Sci Dept Comp Sci & Appl Math IL-76100 Rehovot Israel Cardiff Univ Cardiff Sch Math Cardiff CF24 4AG S Glam Wales Cardiff Univ WIMCS Cardiff CF24 4AG S Glam Wales

A 3-D optical scanner was used to obtain precise and complete representations of lithic artifacts. A computer algorithm, which was specially developed for the purpose, was used to position the artifacts in a way which enables the extraction of the standard metric parameters (length, width, width at 1/2 length, etc.). In this way, the ambiguities which affect the traditional manual measurements were eliminated. This new methodology creates accurate and objective databases. Several other parameters (center of mass position, volume, surface area) were also computed. The advantages of our method are illustrated by the analysis of 90 scanned Lower Paleolithic handaxes. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Lithics 3-D images automatic documentation Metric parameters Handaxes

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Reduce maintenance costs with smart field devices

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HYDROCARBON PROCESSING 1999年第1期78卷 65-67页

作者： Masterson, JS Fisher Rosemount Burnsville MN USA

Ongoing annual savings of nearly $1,000 per device are possibleIntelligent microprocessor-based field devices rapidly replacing older types of instrumentation in refineries and petrochemical plants generate vast amounts of information that can be useful far beyond the control room. While the advent of smart instrumentation and condition monitoring sensors has increased the volume of available information, getting this complex data to the maintenance shop in a useful form has evolved slowly.

关键词： Maintenance Costs Open systems Computer architecture Computer software Maintenance costs Smart field devices Asset management software Online maintenance software automatic documentation Predictive maintenance

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Constructural Software documentation 19

Constructural Software Documentation

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IEEE/ACM 41st International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP)

作者： Nassif, Mathieu Robillard, Martin P. McGill Univ Sch Comp Sci Montreal PQ Canada

ISBN: (纸本)9781728117645

Software projects capture information in artifacts that include production code, test suites, and documentation. Because different artifacts serve different purposes, some artifacts can include redundant information, encoded in different formats. To mitigate this redundancy, we propose an approach to explicitly encode in unit tests information that will be automatically extracted and added to the documentation of the software. We implemented this approach in the form of an Eclipse plug-in that binds unit tests written with JUnit to the header comments of the tested methods.

关键词： Constructural documentation Unit testing automatic documentation documentation extraction Javadoc

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Improved Code Summarization via a Graph Neural Network 28

Improved Code Summarization via a Graph Neural Network

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28th IEEE/ACM International Conference on Program Comprehension (ICPC)

作者： LeClair, Alexander Haque, Sakib Wu, Lingfei McMillan, Collin Univ Notre Dame South Bend IN 46556 USA IBM Res Yorktown Hts NY USA

ISBN: (纸本)9781450379588

automatic source code summarization is the task of generating natural language descriptions for source code. automatic code summarization is a rapidly expanding research area, especially as the community has taken greater advantage of advances in neural network and AI technologies. In general, source code summarization techniques use the source code as input and outputs a natural language description. Yet a strong consensus is developing that using structural information as input leads to improved performance. The first approaches to use structural information flattened the AST into a sequence. Recently, more complex approaches based on random AST paths or graph neural networks have improved on the models using flattened ASTs. However, the literature still does not describe the using a graph neural network together with source code sequence as separate inputs to a model. Therefore, in this paper, we present an approach that uses a graph-based neural architecture that better matches the default structure of the AST to generate these summaries. We evaluate our technique using a data set of 2.1 million Java method-comment pairs and show improvement over four baseline techniques, two from the software engineering literature, and two from machine learning literature.

关键词： automatic documentation neural networks deep learning artificial intelligence

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A Convolutional Neural Network for Language-Agnostic Source Code Summarization 14

A Convolutional Neural Network for Language-Agnostic Source ...

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14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE)

作者： Moore, Jessica Ben Gelman Slater, David Two Six Labs Machine Learning Grp Arlington VA 22203 USA

ISBN: (纸本)9789897583759

Descriptive comments play a crucial role in the software engineering process. They decrease development time, enable better bug detection, and facilitate the reuse of previously written code. However, comments are commonly the last of a software developer's priorities and are thus either insufficient or missing entirely. automatic source code summarization may therefore have the ability to significantly improve the software development process. We introduce a novel encoder-decoder model that summarizes source code, effectively writing a comment to describe the code's functionality. We make two primary innovations beyond current source code summarization models. First, our encoder is fully language-agnostic and requires no complex input preprocessing. Second, our decoder has an open vocabulary, enabling it to predict any word, even ones not seen in training. We demonstrate results comparable to state-of-the-art methods on a single-language data set and provide the first results on a data set consisting of multiple programming languages.

关键词： Natural Language Processing Deep Learning Source Code Crowdsourcing automatic documentation

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