本文選題：BPEL過程　切入點：數(shù)據(jù)流錯誤　出處：《南京理工大學》2017年碩士論文　論文類型：學位論文

【摘要】：隨著Web服務與云計算的飛速發(fā)展,服務組合已經(jīng)成為應用開發(fā)的主流模式之一。Web服務業(yè)務過程執(zhí)行語言(簡稱BPEL)已經(jīng)成為描述Web服務組合事實上的的標準。由于BPEL是類XML語言,BPEL服務組合(過程)具有天然的塊結(jié)構(gòu)的特性,因而不易發(fā)生控制流錯誤(如死鎖)。然而,由于Web服務通過消息進行數(shù)據(jù)交互,同時為保證數(shù)據(jù)的隱私性,BPEL服務組合往往需要對內(nèi)部、外部的數(shù)據(jù)進行大量的轉(zhuǎn)換處理,因而極易引入數(shù)據(jù)流錯誤,這嚴重影響了 BPEL服務組合的質(zhì)量�，F(xiàn)有BPEL過程的數(shù)據(jù)流錯誤檢測方法存在路徑爆炸和誤報(false positives)等問題,為克服上述不足,我們提出了兩種方法用于檢測BPEL過程中的數(shù)據(jù)流錯誤:基于可達定義的數(shù)據(jù)流分析方法和基于SMT(可滿足性模理論)約束求解器的符號編碼方法。我們將上述方法應用到178個工業(yè)界中的BPEL過程,對其中的數(shù)據(jù)流錯誤進行了實證分析,并提出了基于復雜性度量為特征進行數(shù)據(jù)流錯誤分類預測。本文的主要貢獻包括:1.提出了兩種檢測BPEL過程中的數(shù)據(jù)流錯誤的方法。第一種是基于可達定義的數(shù)據(jù)流分析方法,第二種是基于SMT求解器的符號編碼與約束求解方法。第二類方法首先對常見的三種數(shù)據(jù)流反模式進行符號編碼,然后采用SMT約束求解器對數(shù)據(jù)流錯誤進行檢測。第一類方法可以方便的定位錯誤發(fā)生的位置,但可能存在誤報(false positives),第二類方法可以確保路徑的可行性,但需要編碼并運行SMT工具,因此兩類方法優(yōu)缺點互補。2.以178個真實BPEL過程為研究對象,對它們的復雜性度量指標和數(shù)據(jù)流錯誤進行了實證分析。統(tǒng)計分析了現(xiàn)有度量指標在刻畫數(shù)據(jù)流復雜性方面尚有不足,提出了一組新的度量數(shù)據(jù)流復雜性的指標。并統(tǒng)計分析發(fā)現(xiàn)了數(shù)據(jù)流錯誤的嚴重性,共94個BPEL過程存在數(shù)據(jù)流錯誤,占比52.81%,其中輸出冗余錯誤最為嚴重;最后我們總結(jié)出了數(shù)據(jù)流錯誤的活動分布和發(fā)生原因。3.提出一種以復雜性度量指標作為特征對數(shù)據(jù)流錯誤進行分類預測的方法。首先針對常用的復雜性度量指標進行特征篩選,隨后基于各種數(shù)據(jù)挖掘分類算法,對BPEL過程中的各種數(shù)據(jù)流錯誤進行分類預測。分類預測均取得了超過90%的準確度且最終選擇的特征組合中特征均具有簡單、易計算的特點。
[Abstract]:With the rapid development of Web services and cloud computing, Web Services Business process execution language (BPELL) has become the de facto standard for describing Web service composition. Because BPEL is a XML language like BPEL service composition (process). Having the properties of a natural block structure, Therefore, control flow errors (such as deadlocks) are not easy to occur. However, because Web services interact with data through messages, and in order to ensure the privacy of data, Web service composition often requires a large number of internal and external data transformation processing. Therefore, it is easy to introduce data flow errors, which seriously affect the quality of BPEL service composition. The existing data flow error detection methods in BPEL process have some problems, such as path explosion and false positives. in order to overcome these problems, We propose two methods to detect data flow errors in BPEL process: data stream analysis method based on reachability definition and symbolic coding method based on SMT constraint solver. Applied to 178 BPEL processes in industry, The error of data flow is analyzed empirically. The main contributions of this paper include: 1. Two methods to detect data flow errors in BPEL process are proposed. The first method is based on the definition of reachability. The second is symbol coding and constraint solving method based on SMT solver. Then the SMT constraint solver is used to detect the error in the data stream. The first method can easily locate the location of the error, but there may be false positives. the second method can ensure the feasibility of the path. However, it is necessary to code and run SMT tools, so the advantages and disadvantages of the two methods complement each other .2. taking 178 real BPEL processes as research objects, An empirical analysis of their complexity metrics and data flow errors is made, and a statistical analysis is made on the shortcomings of the existing metrics in describing the complexity of data flows. A new set of indexes to measure the complexity of data flow is proposed, and the severity of data flow errors is found by statistical analysis. A total of 94 BPEL processes have data flow errors, accounting for 52.81%, among which the output redundancy errors are the most serious. Finally, we summarize the activity distribution of data flow errors and the causes of data flow errors. 3. A method of classifying and predicting data flow errors based on complexity metrics is proposed. Then, based on various data mining classification algorithms, various data flow errors in the BPEL process are classified and forecasted. The classification prediction achieves accuracy of more than 90% and the features of the final selected feature combinations have the characteristics of simple and easy to calculate.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP393.09

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