Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (10): 178-186.doi: 10.11896/jsjkx.230800191

• Computer Software • Previous Articles     Next Articles

Study on Building Business-oriented Resource On-demand Resolution Model

LIU Yao1, QIN Xun2, LIU Tianji2   

  1. 1 Engineering Center,Institute of Scientific and Technical Information of China,Beijing 100038,China
    2 School of Software and Microelectronics,Peking University,Beijing 102600,China
  • Received:2023-08-30 Revised:2024-01-22 Online:2024-10-15 Published:2024-10-11
  • About author:LIU Yao,born in 1972,Ph.D,resear-cher,is a distinguished member of CCF(No.17606D).His main research in-terests include natural language proces-sing,knowledge organization,and know-ledge engineering
  • Supported by:
    National Social Science Foundation of China(21BTQ011).

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Abstract: To address the issue of re-analyzing and repeating development of natural language processing tools and resource ana-lysis plugins when new requirements arise during project development,this paper proposes a business-oriented on-demand resource analysis solution.Firstly,a demand-driven resource analysis method from requirement to code is proposed,focusing on the construction of a demand concept indexing model for the requirement text itself.The constructed demand concept indexing model outperforms other classification models in terms of accuracy,recall,and F1 score.Secondly,this paper establishes a mapping mechanism from requirement text to code library categories based on the correlation between requirement text and code.For the mapping results,the precison@K is used as an evaluation metric,with an ultimate accuracy rate of 60%,demonstrating a certain practical value.In summary,this paper explores a set of key technologies for on-demand resource analysis with demand parsing capabilities and implements the correlation between requirements and code,covering the entire process from requirement text classification,code library classification,code library retrieval to plugin generation.The proposed method forms a complete business loop of “requirement-code-plugin-analysis” and experimentally verifies to be effective for on-demand resource analysis.Compared to existing large language models for business requirement analysis and code generation,this method focuses on the implementation of the full process of plugin code reuse within specific business domains,containing business characteristics.

Key words: Natural language processing, Requirements model, Code reuse, Text parsing, Code categorization, Code retrieval

CLC Number: 

  • TP391
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