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Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/27234
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| Title: | A Novel Approach to Modularization Programming of Legacy Systems |
| Other Titles: | 大型既有軟體系統程式模組化方法之研究 |
| Authors: | 黃俊哲;何習銓;楊建民
Huang, Chun-Che;Ho, Hsi-Chuan;Yang, Jiann-Min |
| Keywords: | 模組化程式,既有系統,模糊關聯記憶;Program modularization,legacy system,fuzzy associative memory |
| Date: | 2007-01 |
| Issue Date: | 2009-01-17 16:23:10 (UTC+8) |
| Abstract: | The modularization of large legacy software systems has attracted a great deal of attention in recent years. Such modularization improves the maintenance and reuse of smaller, more manageable pieces of program source codes, and also provides insight into the overall structure of the software system. This paper develops a methodology to determine the modularization programming of a legacy software system. This methodology breaks programs into modules, or groups of related functions based on the observation that a module can be defined as a group of functions having high cohesion and low coupling. Furthermore, the determination of good alternatives to perform the desired attributes, with some fuzzy constraints, is crucial in building software systems. With known modules, a rule-based fuzzy representation of the module development problem is presented, while the tradeoff of the attributes of performance among modules is analyzed, using a fuzzy neural network approach. The approach taken to reach this solution is illustrated with simulation software.
最近幾年，對於大型既有軟體系統的模組化已經引起相當大的關注。這些模組化，改善了原始碼的維護性及其再使用性，也對於軟體系統的整體架構提供更清晰的觀察。本篇論文發展了一個決定既有系統的模組化程式的方法論。此方法論將其相關功能分群，切割程式成數個模組，因為一個模組可以被定義為一群具有高凝聚力或低耦合度的功能性單位。此外，如何應用模糊限制來決定較好的解決方案來呈現所需的屬性，也是建構軟體系統的關鍵。對於已知的模組，使用規則導向的模糊表達方式，來表達模組建構的問題，同時應用模糊類神經的方法，分析模組之間效能相關屬性的取捨。此方法已成功解決模擬軟體所需模組化的問題並將解決的過程詳加描述。 |
| Relation: | 資訊管理學報,14(1),273-298 |
| Data Type: | article |
| Appears in Collections: | [資訊管理學系] 期刊論文
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