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  1. International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE).
  2. 2015 IEEE/ACM 4th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering
  3. Text Understanding for Programming in Natural Language: Control Structures
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2015 IEEE/ACM 4th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering
Title Page i
Title Page iii
Copyright Page
Table of Contents
Message from the Chairs
Committees and Reviewers
Sponsors and Supporters
Mining Enterprise Models for Knowledgeable Decision Making
Text Understanding for Programming in Natural Language: Control Structures
Clustering Source Code Elements by Semantic Similarity Using Wikipedia
Black-Box Test Generation from Inferred Models
Recommending Features and Feature Relationships from Requirements Documents for Software Product Lines
Towards Interpretable Defect-Prone Component Analysis Using Genetic Fuzzy Systems
Author Index
Publisher's Information
2013 2nd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE)
2012 First International Workshop on Realizing AI Synergies in Software Engineering (RAISE)

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Text understanding for programming in natural language: control structures

Article

Text Understanding for Programming in Natural Language: Control Structures

Content Provider IEEE Xplore Digital Library
Author Landhaeusser, M. Hug, R.
Copyright Year 2015
Description Author affiliation: Karlsruhe Inst. of Technol., Karlsruhe, Germany (Landhaeusser, M.; Hug, R.)
Abstract We investigate how natural languages such as English can be used as programming languages. Often, in natural language (as well as in programming) different actions happen at the same time or are repeated. In natural language we just say what is going to happen -- in programming we use control structures. Story lines without equivalent language/phrase structures are unnatural and programs without control structures are hard to read. An empirical study showed how users express control structures in natural language. We propose a new and automatic text analysis. It leverages Stanford's typed dependencies to detect sentence structures that imply strictly sequential control flows, repetition, and parallelism. The technique is analyzed in the context of Alice, a 3D programming environment, and Alice NLP, a system for programming Alice in ordinary English. We evaluate our approach with 52 texts with 795 control-flow-affected elements in total and show that 82% of these elements can be detected successfully. We performed a second evaluation with manually corrected input and find that our approach successfully detects the control structures 97% of the time in the absence of parser errors.
Starting Page 7
Ending Page 12
File Size 135829
Page Count 6
File Format PDF
ISBN 9781467370646
DOI 10.1109/RAISE.2015.9
Language English
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date 2015-05-17
Publisher Place Italy
Access Restriction Subscribed
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword Control structures Computer languages Gold Natural languages Alice Programming Ontologies Programming with natural language Animation Natural language processing End-user programming Periodic structures
Content Type Text
Resource Type Article
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