ISCAS OpenIR
a generative approach to searching algorithmic programs development
Shi Haihe; Xue Jinyun
2011
Conference Name5th International Conference on Theoretical Aspects of Software Engineering, TASE 2011
SourceProceedings - 5th International Conference on Theoretical Aspects of Software Engineering, TASE 2011
Pages76-81
Conference DateAugust 29,
Conference PlaceXi'an, Shaanxi, China
Indexed TypeEI
ISBN9780769545066
Department(1) Institute of Software Chinese Academy of Sciences Beijing 100190 China; (2) Provincial Key Lab. for High-Performance Computing Technology Jiangxi Normal University Nanchang 330022 China; (3) Graduate University Chinese Academy of Sciences Beijing 100049 China
English AbstractUsing highly configurable semi-automatic approach to algorithmic programs development can improve correctness and productivity. This paper explores a way to use generative techniques to produce the algorithmic programs for searching problem. Based on PAR method and PAR platform, it is to formally develop generic type component and algorithm components, and to design a formal algorithm generative model that models an invariant behavior in terms of variant behaviors, and then to automatically generate a variety of specialized searching algorithmic programs through replacing the generic identifiers with a few concrete operations. Through the super framework and underlying components, the reliability and productivity of domain specific algorithms are dramatically improved. © 2011 IEEE.; Using highly configurable semi-automatic approach to algorithmic programs development can improve correctness and productivity. This paper explores a way to use generative techniques to produce the algorithmic programs for searching problem. Based on PAR method and PAR platform, it is to formally develop generic type component and algorithm components, and to design a formal algorithm generative model that models an invariant behavior in terms of variant behaviors, and then to automatically generate a variety of specialized searching algorithmic programs through replacing the generic identifiers with a few concrete operations. Through the super framework and underlying components, the reliability and productivity of domain specific algorithms are dramatically improved. © 2011 IEEE.
KeywordProductivity Software Engineering
SponsorshipIEEE CS; IFIP
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/16199
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Shi Haihe,Xue Jinyun. a generative approach to searching algorithmic programs development[C],2011:76-81.
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