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研究生:黃佳雄
研究生(外文):Chui-Hsiung Huang
論文名稱:建構包含四種模型之軟體可靠度評估系統
論文名稱(外文):SAS/IML Implementation of Four Selected Models for a Software Reliability Evaluation System
指導教授:王清正
指導教授(外文):Ching-Cheng Wang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:製造工程研究所碩博士班
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:51
中文關鍵詞:SAS/IML軟體可靠度
外文關鍵詞:Software ReliabilitySAS/IML
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軟體可靠度為在一特定時間,特定環境之內,軟體操作不發生失效的機率。大部分之軟體可靠度模型均使用錯碼計數(fault counts)、失效計數(failure counts)與失效時間間距(time between failures)為其失效行為之量測。本文以六十幾個軟體可靠度模型為來源,先由上述三種量測值進行簡單分類並縮小範圍,再依特定之目的,如預測能力、估算能力、假設條件之品質、適用性與簡單性,選定以下四種軟體可靠度模型作為研究對象:
1. Downs與Garrone所提的Random Paths Model。
2. Downs與Garrone所提的Piecewise Linear Hazard Rate Model。
3. Gaudoin、Lavergne與Soler所提的Lognormal Proportional Model。
4. Sofer與Miller所提的Non-Parametric Software Reliability Growth Model。

上述每個模型之選擇皆有其考量因素。其中,隨機路徑模型與片段線性失效率模型之考量為其預測能力;對數常態比例模型則考量其建構評估系統之簡單性;而無母數軟體可靠度成長模型因具有一完全單調性,使得此模型之適用範圍相當廣泛。此外,欲發展每個模型之評估系統有五個主要步驟。第一個步驟,先進行模型分析,其產出包含假設條件、數學方程式與輸入資料需求。第二個步驟,使用統計學之估計方法推導未知參數之估計式。第三個步驟,使用SAS/IML將所得之演算法進行程式實作。第四個步驟,使用模擬資料進行測試以估計未知參數。第五個步驟,以區間估計法確認估計結果的正確性。透過上述步驟之進行,本文已分別完成隨機路徑模型、片段線性失效率模型、對數常態比例模型與無母數軟體可靠度成長模型等四個軟體可靠度評估系統。此軟體可靠度量化評估能力,不僅可幫助軟體開發人員決定軟體之測試完成時間,亦可提供使用者購買軟體之決策依據。
Software reliability is defined as the probability of failure-free software operation for a specified period of time in a specified environment. Most of software reliability models apply three measurements including fault counts, failure counts and time between failures to measure their failure behavior. We have reviewed more than 60 software reliability models, and select the following four models by specific criteria of predictive validity, capability, quality of assumptions, applicability and simplicity:
1. Downs and Garrone's Random Paths (RP) Model.
2. Downs and Garrone's Piecewise Linear Hazard Rate (PLHR) Model.
3. Gaudoin, Lavergne and Soler's Lognormal Proportional Model (LPM).
4. Sofer and Miller's Non-Parametric Software Reliability Growth (NPSRG) Model.

There is a main considered factor to select each model of the above. The reason for Random Paths Model and Piecewise Linear Hazard Rate Model is their predictive ability. Lognormal Proportional Model is considered by its simplicity and rapidity to finish a constructed evaluation system. Non-Parametric Software Reliability Growth Model with a complete monotonicity is selected by its extensive applicability. Furthermore, there are five main steps to develop an evaluation system of each model. In the first step, we perform model analysis and its outputs including assumptions, mathematic equations and input data requirements. In the second step, the methods of estimation in Statistics are employed to derive the estimated formulas of unknown parameters. In the third step, the derived algorithms are implemented in SAS/IML. In the fourth step, the established system of each model is tested using simulation data to estimate unknown parameters. In the final step, we use the method of interval estimation to ensure the accuracy of estimated result. By the performance of above steps, we have finished four models of software reliability evaluation system including the RP, PLHR, LPM, and NPSRG models. The quantitative evaluation capacity of software reliability not only help the software developer to determine the finished time of software testing but also supply the decision making while purchasing to the user.
摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章、緒論 1
1.1研究動機 1
1.2研究背景 1
1.3研究方法 3
第二章、軟體可靠度模型 5
2.1簡介 5
2.2軟體可靠度模型之分類 5
2.3軟體可靠度模型之選擇 6
第三章、隨機路徑模型 9
3.1 前言 9
3.2 模型分析 10
3.3 參數估計式推導 12
3.4 程式實作 12
3.4.1模擬產生資料程式 13
3.4.2 SAS/IML程式編碼 13
3.4.3 模擬結果 14
第四章、片段線性失效率模型 17
4.1 模型分析 17
4.2 參數估計式推導 18
4.3程式實作 24
4.3.1模擬產生資料程式 25
4.3.2 SAS/IML程式編碼 27
4.3.3 模擬結果 28
第五章、對數常態比例模型 30
5.1 模型分析 30
5.2 參數估計式推導 31
5.3程式實作 33
5.3.1模擬產生資料程式 33
5.3.2 SAS/IML程式編碼 33
5.3.3 模擬結果 34
第六章、無母數軟體可靠度成長模型 36
6.1 模型分析 36
6.2 參數估計式推導 38
6.3程式實作 39
6.3.1模擬產生資料程式 39
6.3.2 SAS/IML程式編碼 40
6.3.3 模擬結果 41
第七章、結論與建議 45
7.1 結論 45
7.2 建議 46
參考文獻 48
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