A Two-folded Impact Analysis of Schema Changes on Database Applications

Database applications are becoming increasingly popular, mainly due to the advanced data management facilities that the underlying database management system offers compared against traditional legacy software applications. The interaction, however, of such applications with the database system introduces a number of issues, among which, this paper addresses the impact analysis of the changes performed at the database schema level. Our motivation is to provide the software engineers of database applications with automated methods that facilitate major maintenance tasks, such as source code corrections and regression testing, which should be triggered by the occurrence of such changes. The presented impact analysis is thus two-folded： the impact is analysed in terms of both the affected source code statements and the affected test suites concerning the testing of these applications. To achieve the former objective, a program slicing technique is employed, which is based on an extended version of the program dependency graph. The latter objective requires the analysis of test suites generated for database applications, which is accomplished by employing testing techniques tailored for this type of applications. Utilising both the slicing and the testing techniques enhances program comprehension of database applications, while also supporting the development of a number of practical metrics regarding their maintainability against schema changes. To evaluate the feasibility and effectiveness of the presented techniques and metrics, a software tool, called DATA, has been implemented. The experimental results from its usage on the TPC-C case study are reported and analysed.

Structure design and establishment of database application system for alien species in Shandong Province,China

This paper presents a case study on structure design and establishment of database application system for alien species in Shandong Province, integrating with Geographic Information System, computer network, and database technology to the research of alien species. The modules of alien species database, including classified data input, statistics and analysis, species pictures and distribution maps, and out date input, were approached by Visual Studio.net 2003 and Microsoft SQL server 2000. The alien species information contains the information of classification, species distinction characteristics, biological characteristics, original area, distribution area, the entering fashion and route, invasion time, invasion reason, interaction with the endemic species, growth state, danger state and spatial information, i.e. distribution map. Based on the above bases, several models including application, checking, modifying, printing, adding and returning models were developed. Furthermore, through the establishment of index tables and index maps, we can also spatially query the data like picture, text and GIS map data. This research established the technological platform of sharing information about scientific resource of alien species in Shandong Province, offering the basis for the dynamic inquiry of alien species, the warning technology of prevention and the fast reaction system. The database application system possessed the principles of good practicability, friendly user interface and convenient usage. It can supply full and accurate information inquiry services of alien species for the users and provide functions of dynamically managing the database for the administrator.

Combinatorial Design of Some Database Application Technologies Based on B/S

Evolving From principal-subordinate structure of C /S to flexible multileveled distributed structure, i.e. B/S architecture so as to form a wide, distributed and orderly Internet/Intranet integrated management inf ormation system, is the trend of development of application software of the whol e world. Advantages and disadvantages of the two modes: C/S and B/S are compared . It is pointed out that at present onefold B/S mode cannot yet fully fullfil th e demands of some complicated data processing, information statistics and analys is, etc, therefore it still awaits further development of technology to achieve 100% Internet. In this paper, a mode of B/S-C/S-blended multileveled architect ure is discussed; the logical levels of B/S mode is studied; Furthermore, combin ing some up-to-date software developing technology, combinatorial design of di fferent database application technology based on B/S is discussed. The expatiati on is made with following points: (1) Organic combination of the network distrib uted object technology of CORBA and the computation technology among different n etwork operating system ─ Java; (2) Organic combination of two modes of ASP and Plug_in; (3) JDBC Server and JDBC Client; (4) An expanded B/S model, i.e. the c lient application of browser communicates directly with Web server, and the serv er application communicates directly with database server through middle ware.

Clustering Text Data Streams

Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organization and topic detection and tracing etc. However, most methods are similarity-based approaches and only use the TF,IDF scheme to represent the semantics of text data and often lead to poor clustering quality. Recently, researchers argue that semantic smoothing model is more efficient than the existing TF,IDF scheme for improving text clustering quality. However, the existing semantic smoothing model is not suitable for dynamic text data context. In this paper, we extend the semantic smoothing model into text data streams context firstly. Based on the extended model, we then present two online clustering algorithms OCTS and OCTSM for the clustering of massive text data streams. In both algorithms, we also present a new cluster statistics structure named cluster profile which can capture the semantics of text data streams dynamically and at the same time speed up the clustering process. Some efficient implementations for our algorithms are also given. Finally, we present a series of experimental results illustrating the effectiveness of our technique.