Application of Recursive Query on Structured Query Language Server

The advantage of recursive programming is that it is very easy to write and it only requires very few lines of code if done correctly.Structured query language(SQL)is a database language and is used to manipulate data.In Microsoft SQL Server 2000,recursive queries are implemented to retrieve data which is presented in a hierarchical format,but this way has its disadvantages.Common table expression(CTE)construction introduced in Microsoft SQL Server 2005 provides the significant advantage of being able to reference itself to create a recursive CTE.Hierarchical data structures,organizational charts and other parent-child table relationship reports can easily benefit from the use of recursive CTEs.The recursive query is illustrated and implemented on some simple hierarchical data.In addition,one business case study is brought forward and the solution using recursive query based on CTE is shown.At the same time,stored procedures are programmed to do the recursion in SQL.Test results show that recursive queries based on CTEs bring us the chance to create much more complex queries while retaining a much simpler syntax.

Structured Query Language Injection Penetration Test Case Generation Based on Formal Description

Aiming to improve the Structured Query Language( SQL) injection penetration test accuracy through the formalismguided test case generation,an attack purpose based attack tree model of SQL injection is proposed,and then under the guidance of this model, the formal descriptions for the SQL injection vulnerability feature and SQL injection attack inputs are established. Moreover,according to new coverage criteria,these models are instantiated and the executable test cases are generated.Experiments show that compared with the random enumerated test case used in other works,the test case generated by our method can detect the SQL injection vulnerability more effectively. Therefore,the false negative is reduced and the test accuracy is improved.

A Type of Language Field Integrated Algorithm Used for Analysis and Control of Complicated System

A new concept of language field and its value structure are presented in this paper for the first time and a describing framework is set forth for researching computational model of reasoning. On this basis we have established a model of qualitative reasoning of causal relations and fuzzy integrated algorithm. Furthermore we have found a lot of its applications.

Evaluation Method of Web Site Structure Based on Web Structure Mining

The structure of Web site became more complex than before. During the design period of a Web site, the lack of model and method results in improper Web structure, which depend on the designer's experience. From the point of view of software engineering, every period in the software life must be evaluated before starting the next period's work. It is very important and essential to search relevant methods for evaluating Web structure before the site is completed. In this work, after studying the related work about the Web structure mining and analyzing the major structure mining methods (Page\|rank and Hub/Authority), a method based on the Page\|rank for Web structure evaluation in design stage is proposed. A Web structure modeling language WSML is designed, and the implement strategies for evaluating system of the Web site structure are given out. Web structure mining has being used mainly in search engines before. It is the first time to employ the Web structure mining technology to evaluate a Web structure in the design period of a Web site. It contributes to the formalization of the design documents for Web site and the improving of software engineering for large scale Web site, and the evaluating system is a practical tool for Web site construction.

A BRIEF SURVEY OF STRUCTURAL APPROACH TO LANGUAGE ACQUISITION

1.The Theory Underlying the Structural Approach to Language AcquisitionGrammar-translation approach had dominated the realm of language teach-ing and learning for centuries.However,in the 30s and 40s of this centuryAmerican linguists,using the foundings of behavioristic psychology as

A New Database Intrusion Detection Approach Based on Hybrid Meta-Heuristics

A new secured database management system architecture using intrusion detection systems(IDS)is proposed in this paper for organizations with no previous role mapping for users.A simple representation of Structured Query Language queries is proposed to easily permit the use of the worked clustering algorithm.A new clustering algorithm that uses a tube search with adaptive memory is applied to database log files to create users’profiles.Then,queries issued for each user are checked against the related user profile using a classifier to determine whether or not each query is malicious.The IDS will stop query execution or report the threat to the responsible person if the query is malicious.A simple classifier based on the Euclidean distance is used and the issued query is transformed to the proposed simple representation using a classifier,where the Euclidean distance between the centers and the profile’s issued query is calculated.A synthetic data set is used for our experimental evaluations.Normal user access behavior in relation to the database is modelled using the data set.The false negative(FN)and false positive(FP)rates are used to compare our proposed algorithm with other methods.The experimental results indicate that our proposed method results in very small FN and FP rates.

Causal association rule mining methods based on fuzzy state description

Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space, through constructing its state （abnormality） relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validiw is proved through case.

A Structured Temporal Logic Language:XYZ/SE

In order to enhance the readability and to simplify the verification of temporal logic programs in the XYZ system,we propose a structured temporal logic language called XYZ/SE,based on XYZ/BE which is the basis language of the XYZ system.A set of proof rules are given and proved to be sound and adequate for proving the partial correctness of XYZ/SE programs in a compositional way.Moreover,we show that every XYZ/BE program can be transformed into an equivalent XYZ/SE program.So we have developed a general compositional verification method in the XYZ system concerning the sequential case.

The Skills of Practical Writing for TourGuide(Ⅱ) ——Points for Attention

This thesis is about the skills of practical writing for Tour Guide.This article dissertates several points--the interpretation of the source language,structure of the target language and choice of the right word,that should be given more attention in translation.As a Tour Guide,one needs to have these skills and the ability of describing sceneries beautifully and accurately by writing.

A visual analytics workflow for probabilistic modeling

Probabilistic programming is a powerful means for formally specifying machine learning models.The inference engine of a probabilistic programming environment can be used for serving complex queries on these models.Most of the current research in probabilistic programming is dedicated to the design and implementation of highly efficient inference engines.Much less research aims at making the power of these inference engines accessible to non-expert users.Probabilistic programming means writing code.Yet many potential users from promising application areas such as the social sciences lack programming skills.This prompted recent efforts in synthesizing probabilistic programs directly from data.However,working with synthesized programs still requires the user to read,understand,and write some code,for instance,when invoking the inference engine for answering queries.Here,we present an interactive visual approach to synthesizing and querying probabilistic programs that does not require the user to read or write code.

LotusSQL:SQL Engine for High-Performance Big Data Systems

In recent years,Apache Spark has become the de facto standard for big data processing.SparkSQL is a module offering support for relational analysis on Spark with Structured Query Language(SQL).SparkSQL provides convenient data processing interfaces.Despite its efficient optimizer,SparkSQL still suffers from the inefficiency of Spark resulting from Java virtual machine and the unnecessary data serialization and deserialization.Adopting native languages such as C++could help to avoid such bottlenecks.Benefiting from a bare-metal runtime environment and template usage,systems with C++interfaces usually achieve superior performance.However,the complexity of native languages also increases the required programming and debugging efforts.In this work,we present LotusSQL,an engine to provide SQL support for dataset abstraction on a native backend Lotus.We employ a convenient SQL processing framework to deal with frontend jobs.Advanced query optimization technologies are added to improve the quality of execution plans.Above the storage design and user interface of the compute engine,LotusSQL implements a set of structured dataset operations with high efficiency and integrates them with the frontend.Evaluation results show that LotusSQL achieves a speedup of up to 9 in certain queries and outperforms Spark SQL in a standard query benchmark by more than 2 on average.

Lom： Discovering Logic Flaws Within MongoDB-based Web Applications

Logic flaws within web applications will allow malicious operations to be triggered towards back-end database. Existing approaches to identifying logic flaws of database accesses are strongly tied to structured query language （SQL） statement construction and cannot be applied to the new generation of web applications that use not only structured query language （NoSQL） databases as the storage tier. In this paper, we present Lom, a black-box approach for discovering many categories of logic flaws within MongoDB- based web applications. Our approach introduces a MongoDB operation model to support new features of MongoDB and models the application logic as a mealy finite state machine. During the testing phase, test inputs which emulate state violation attacks are constructed for identifying logic flaws at each application state. We apply Lom to several MongoDB-based web applications and demonstrate its effectiveness.