本文選題：軟件行為軌跡 + 動態(tài)測評��； 參考：《蘇州大學》2012年碩士論文

【摘要】：隨著蘇州市地鐵土建工程的逐步推進，人們對城市軌道交通運營軟件的可靠性、可用性以及安全性等可信性質(zhì)寄予了很高的期望與要求。為了解決城市軌道交通運營軟件日益突出的可信性問題，僅對軟件系統(tǒng)做出傳統(tǒng)質(zhì)量保證(如測試、驗證)是不夠的，更需要對系統(tǒng)交互行為進行有效的分析與態(tài)勢預測。 軌道交通運營軟件有別于傳統(tǒng)分布式軟件，它呈現(xiàn)出松散聚合、規(guī)模龐大、行為復雜等特點。本文將軟件行為作為切入點，對軌道交通運營軟件行為的軌跡分析以及意圖預測逐步展開了研究，建立一種以軟件行為可信為核心的軟件行為動態(tài)測評方法。 本文將系統(tǒng)監(jiān)測到的狀態(tài)變化映射為帶有語義的事件序列，利用最精簡主要序列提取算法對行為序列進行提煉精簡，從被消減掉的重復子序列挖掘有用信息，產(chǎn)生能體現(xiàn)軟件行為特征的行為序列，通過序列對比分析行為的可信性，用HMM對交互行為狀態(tài)進行預測，此為大粒度行為可信性動態(tài)測評研究；同時以交互事件為切入點，關(guān)注事件的參數(shù)值以及經(jīng)驗知識等詳細信息，用MEBN工具建立具體事態(tài)的貝葉斯網(wǎng)(SSBN)來分析交互行為的復雜過程及效應(yīng)，此為小粒度行為可信性動態(tài)測評研究。本文采用小粒度動態(tài)測評分析方法處理復雜情形下群體交互行為可信性分析，采用大粒度行為動態(tài)測評分析通用情形。 本文的主要工作包括： (1)研究軌道交通運營軟件行為的基本特點。明確各智能子系統(tǒng)的信息需求以及它們之間的關(guān)系，為打破子系統(tǒng)各自為營的封閉狀態(tài)，發(fā)揮整體優(yōu)勢，實現(xiàn)一個高效運營的分布式集成化的城市軌道交通運營系統(tǒng)提供理論支持。 (2)研究一套軟件行為描述方法，將監(jiān)測系統(tǒng)捕獲到的可信相關(guān)數(shù)據(jù)生成能表征軟件行為的信息，針對軟件實體交互產(chǎn)生的重復子序列的問題，提出最精簡主要序列提取算法，從被消除的重復子蹤跡中挖掘有用序列，以最簡潔而有廣泛代表性的格式存儲軟件行為信息。 (3)給出一種復雜的有標記的大粒度軟件行為動態(tài)測評方法。使用序列兩兩比較算法分析行為的可信性�；贓M的數(shù)據(jù)重構(gòu)方法訓練樣本數(shù)據(jù)，，用HMM預測軟件行為安全類別。給出仿真實驗，驗證此方法具有一定的優(yōu)勢。 (4)針對多實體貝葉斯網(wǎng)MEBN在表示不確定性關(guān)系上的優(yōu)勢，本文給出一種復雜情形小粒度行為動態(tài)測評方法。此方法有效利用MEBN的一階邏輯語義化表示能力和概率推理能力，采用片斷集有效地描述和分析多個軟件實體交互產(chǎn)生的復雜行為，通過仿真實驗，驗證了小粒度行為軌跡動態(tài)測評的可行性和有效性。 基于軟件行為可信性展開軟件行為動態(tài)測評方法的研究，不僅能推動動態(tài)可信評測理論的發(fā)展，對技術(shù)實踐也有很好的指導意義。
[Abstract]:With the gradual development of subway civil engineering in Suzhou City, people have high expectations and requirements for the reliability, usability and security of urban rail transit operation software. In order to solve the increasingly prominent credibility problem of urban rail transit operation software, it is not enough to make traditional quality assurance (such as testing and verification) for the software system. It is also necessary to effectively analyze and predict the interaction behavior of the system. The rail transit operation software is different from the traditional distributed software. It has the characteristics of loose aggregation, large scale and complex behavior. In this paper, the software behavior is taken as the breakthrough point, the trajectory analysis and intention prediction of the software behavior of rail transit are studied step by step, and a dynamic evaluation method of software behavior based on software behavior trustworthiness is established. In this paper, the state changes monitored by the system are mapped to the event sequences with semantics, and the behavior sequences are refined by the most simplified main sequence extraction algorithms, and useful information is extracted from the subsequences of the subsequences that have been reduced. The behavior sequence which can reflect the behavior characteristic of software is produced, and the credibility of the behavior is analyzed by comparing the sequence, and the interactive behavior state is predicted by HMM, which is the dynamic evaluation research of the large granularity behavior credibility, and the interactive event is taken as the breakthrough point at the same time. Based on the detailed information of event parameters and empirical knowledge, the Bayesian Network (MEBN) is used to analyze the complex process and effect of interaction behavior, which is a dynamic evaluation study of small-grained behavior credibility. In this paper, the small granularity dynamic evaluation and analysis method is used to deal with the credibility analysis of group interaction behavior in complex situations, and the large granularity behavior dynamic evaluation method is used to analyze the general situation. The main work of this paper includes: 1) the basic characteristics of the software behavior of rail transit are studied. To clarify the information needs of each intelligent subsystem and the relationship between them, in order to break the closed state of each subsystem, give play to the overall advantage, To implement a distributed integrated urban rail transit operation system with high efficiency provides theoretical support. (2) A set of software behavior description method is studied. The credible and relevant data captured by the monitoring system are used to generate information that can represent the software behavior. Aiming at the problem of repetitive sub-sequences generated by software entity interaction, the most simplified main sequence extraction algorithm is proposed. Useful sequences are mined from erased repeats to store software behavior information in the most concise and widely representative format. In this paper, a new method of dynamic evaluation of large granularity software behavior is presented. The sequence pairwise comparison algorithm is used to analyze the credibility of behavior. The data reconstruction method based on EM is used to train the sample data, and the HMM is used to predict the behavior security category of software. The simulation results show that this method has some advantages. 4) in view of the advantage of multi-entity Bayesian network (MEBN) in representing uncertain relations, this paper presents a method for dynamic evaluation of small-grained behavior in complex cases. In this method, the first-order logical semantic representation and probabilistic reasoning ability of MEBN are effectively utilized, and the complex behaviors generated by the interaction of multiple software entities are described and analyzed effectively by using the fragment set, and the simulation experiments are carried out. The feasibility and effectiveness of dynamic evaluation of small particle behavior trajectory are verified. The research of software behavior dynamic evaluation method based on software behavior credibility can not only promote the development of dynamic credible evaluation theory, but also have a good guiding significance to technical practice.
【學位授予單位】：蘇州大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP311.53;F572

【引證文獻】

相關(guān)博士學位論文 前3條

1 黃辰林;動態(tài)信任關(guān)系建模和管理技術(shù)研究[D];國防科學技術(shù)大學;2005年

2 楊曉暉;軟件行為動態(tài)可信理論模型研究[D];中國科學技術(shù)大學;2010年

3 滿君豐;開放網(wǎng)絡(luò)環(huán)境下軟件行為監(jiān)測與分析研究[D];中南大學;2010年

本文編號：1950260