國立虎尾科技大學 |

Automatic code generation using artificial intelligence.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Automatic code generation using artificial intelligence./
Author:	Danilchenko, Yuri B.
Description:	1 online resource (124 pages)
Notes:	Source: Masters Abstracts International, Volume: 73-03.
Contained By:	Masters Abstracts International73-03.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9781124804354

Automatic code generation using artificial intelligence.
Danilchenko, Yuri B.

Automatic code generation using artificial intelligence. - 1 online resource (124 pages)

Source: Masters Abstracts International, Volume: 73-03.

Thesis (M.S.)--Northern Kentucky University, 2011.

Includes bibliographical references

Automatic Code Generation (ACG) allows software engineers to create more concise, maintainable, and reusable solutions, ultimately improving their productivity. Despite the significant benefits and the profound economic impact of ACG in the software development field, it still often requires substantial input and interaction from humans. The presented Automatic Coder using Artificial Intelligence (ACAI) system uses a novel approach to solve fully automated code generation in routine programming domains. Given high level user goals and preferences, a library of abstract programs, and a library of generic code components, ACAI uses a combination of Case-Based Reasoning, Routine Design, and Template-Based Programming approaches to generate complete Java programs that satisfy user requirements.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9781124804354Subjects--Topical Terms:

573171
Computer science.
Subjects--Index Terms:

Artificial intelligenceIndex Terms--Genre/Form:

554714
Electronic books.

Automatic code generation using artificial intelligence.
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502 $a Thesis (M.S.)--Northern Kentucky University, 2011.
504 $a Includes bibliographical references
520 $a Automatic Code Generation (ACG) allows software engineers to create more concise, maintainable, and reusable solutions, ultimately improving their productivity. Despite the significant benefits and the profound economic impact of ACG in the software development field, it still often requires substantial input and interaction from humans. The presented Automatic Coder using Artificial Intelligence (ACAI) system uses a novel approach to solve fully automated code generation in routine programming domains. Given high level user goals and preferences, a library of abstract programs, and a library of generic code components, ACAI uses a combination of Case-Based Reasoning, Routine Design, and Template-Based Programming approaches to generate complete Java programs that satisfy user requirements.
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653 $a Case-based reasoning
653 $a Routine design
653 $a Software engineering
653 $a Template-based programming
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