A compiler model for a relational data base management system

One of the chief difficulties which needs to be overcome during the early design stages of a system is that of establishing a satisfactory design for that system. From the time it was first conceived it was apparent that the Relational Data Base Management System is like a compiler in so far as it takes a succession of user requests for information formulated in an applied predicate calculus and translates each one into a series of calls which access an underlying data base and transform data from that data base into the form the user wishes to see. This paper compares the architecture of the Relational Data Base Management System with that of a compiler, and then demonstrates the use of the architecture when processing a language based on an applied predicate calculus. Finally, the paper describes a number of extensions to that architecture which are required to solve the particular problems raised by the data base system.     

The architecture of the PLAIN data base handler

The programming language PLAIN has been designed to support conversational access to a data base, and incorporates relations as a built-in data type. This paper describes the architecture of the data base handler for PLAIN, emphasizing the separation of the data base handler from other aspects of the language processor, and the modularization of the data base architecture to support modifications to the language and its implementation with minimal difficulty. The data base architecture is layered in order to provide the greatest possible degree of information hiding and separation of functionality. The paper shows the structure of the data base handler and the functions of the various modules of the system.     

Data mappings again

Extracting data from a relational data base in order to respond to a request for information requires the use of a large number of algorithms. Some of these algorithms are responsible for validating data values, others support the relational operators while others still support the basic data structures used at the lowest levels of the system. This paper recognizes that the successful operation of a relational data base management system is dependent on the organization of these algorithms and emphasizes this point by describing a coherent architecture to embrace them.     

A portable implementation of a modular multiprocessing database programming language

This paper introduces the database programming language RAPP, which is an integration of the data type relation and relational algebraic operations with the modular multiprocessing language Pascal Plus. A portable version of the RAPP compiler has been implemented and is described.     

Graphical normal forms based on root dependencies in relational data base systems

Normal forms and dependencies are an area of great current interest in the design of relational data bases. Only a subclass, namely, root dependencies and the normal forms based on them, are of direct interest to the data base designer. Dependencies outside this subclass do not have clear cut semantics and may in the long run prove to be of theoretical interest only. We have proposed the fifth normal form (5NF) to control the pattern of codependancy, the highest known root dependency. We have also shown a strong parallel between root dependencies and their normal forms and a family of hypergraphs calledS-diagrams. Graphical normal forms, based onS-diagrams have been proposed and their equivalence to conventional normal forms proved.This work was supported in part by the Science and Engineering Research Board Grant Number 214–7248.     

A knowledge-based system for performing reverse engineering of relational databases

A knowledge-based system, called the Knowledge Extraction System (KES), is presented which performs the process of reverse engineering of relational databases. KES generates an extended entity-relationship (EER) model from a relational database. Within its extraction procedure, domain semantics are obtained by analyzing the data schema and data instances of an existing database, by using heuristics, or asking the user. Relations and attributes are classified into several categories and then converted into the corresponding modelling structures of the EER model. KES demonstrates how knowledge-based system technology can be applied to ease the work of database reverse engineering. It also illustrates that the reverse engineering process can be implemented at a high level of automation. To do so, KES is integrated with the target database management system so that data can be analyzed directly through dynamic SQL queries.     

The design of a Bills of Material Processor using a relational data base

This paper describes the development of a Bills of Material Processor (BOM) and shows how a relational data base system could greatly simplify the design and implementation of the processor on a computer. It describes the steps leading to the structuring of the data files based on data obtained from a manufacturing industry. Examples used in the discussion are real in that they refer to the actual development of a BOM processor using the RAPPORT relational data management system.     

Evolutionary fuzzy clustering of relational data

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be automatically estimated from such data. A fuzzy variant of an evolutionary algorithm for relational clustering is derived and compared against two systematic (pseudo-exhaustive) approaches that can also be used to automatically estimate the number of fuzzy clusters in relational data. An extensive collection of experiments involving 18 artificial and two real data sets is reported and analyzed.     

Ensembles of relational classifiers

Relational classification aims at including relations among entities into the classification process, for example taking relations among documents such as common authors or citations into account. However, considering more than one relation can further improve classification accuracy. Here we introduce a new approach to make use of several relations as well as both, relations and local attributes for classification using ensemble methods. To accomplish this, we present a generic relational ensemble model that can use different relational and local classifiers as components. Furthermore, we discuss solutions for several problems concerning relational data such as heterogeneity, sparsity, and multiple relations. Especially the sparsity problem will be discussed in more detail. We introduce a new method called PRNMultiHop that tries to handle this problem. Furthermore we categorize relational methods in a systematic way. Finally, we provide empirical evidence, that our relational ensemble methods outperform existing relational classification methods, even rather complex models such as relational probability trees (RPTs), relational dependency networks (RDNs) and relational Bayesian classifiers (RBCs).     

XDOODB：一种支持关系模型和数据库方法的OODBMS

本文所述的研究工作，是在ＯＯＤＢＭＳ中同时支持面向对象数据模型和关系数据模型，实现包括对象操作（即数据库方法）在内的同一体化对象管理，并研制了一个相应的原型系统ＸＤＯＯＤＢ。在ＸＤＯＯＤＢ中，我们设计和实现了一种基于ＳＱＬ的数据库语言ＯＳＱＬ，提出了虚拟方法的概念，实现了一种Ｃ＋＋预编译器，使之可自动产生虚拟方法体，所提供的方法服务器以对用户透明的方式可进行数据库方法的存储、动态加载和运行，并采用     

A systematic review of software architecture visualization techniques

ContextGiven the increased interest in using visualization techniques (VTs) to help communicate and understand software architecture (SA) of large scale complex systems, several VTs and tools have been reported to represent architectural elements (such as architecture design, architectural patterns, and architectural design decisions). However, there is no attempt to systematically review and classify the VTs and associated tools reported for SA, and how they have been assessed and applied.ObjectiveThis work aimed at systematically reviewing the literature on software architecture visualization to develop a classification of VTs in SA, analyze the level of reported evidence and the use of different VTs for representing SA in different application domains, and identify the gaps for future research in the area.MethodWe used systematic literature review (SLR) method of the evidence-based software engineering (EBSE) for reviewing the literature on VTs for SA. We used both manual and automatic search strategies for searching the relevant papers published between 1 February 1999 and 1 July 2011.ResultsWe selected 53 papers from the initially retrieved 23,056 articles for data extraction, analysis, and synthesis based on pre-defined inclusion and exclusion criteria. The results from the data analysis enabled us to classify the identified VTs into four types based on the usage popularity: graph-based, notation-based, matrix-based, and metaphor-based VTs. The VTs in SA are mostly used for architecture recovery and architectural evolution activities. We have also identified ten purposes of using VTs in SA. Our results also revealed that VTs in SA have been applied to a wide range of application domains, among which “graphics software” and “distributed system” have received the most attention.ConclusionSA visualization has gained significant importance in understanding and evolving software-intensive systems. However, only a few VTs have been employed in industrial practice. This review has enabled us to identify the following areas for further research and improvement: (i) it is necessary to perform more research on applying visualization techniques in architectural analysis, architectural synthesis, architectural implementation, and architecture reuse activities; (ii) it is essential to pay more attention to use more objective evaluation methods (e.g., controlled experiment) for providing more convincing evidence to support the promised benefits of using VTs in SA; (iii) it is important to conduct industrial surveys for investigating how software architecture practitioners actually employ VTs in architecting process and what are the issues that hinder and prevent them from adopting VTs in SA.     

Exploring the benefits of the combination of a software architecture analysis and a usability evaluation of a mobile application

Designing easy to use mobile applications is a difficult task. In order to optimize the development of a usable mobile application, it is necessary to consider the mobile usage context for the design and the evaluation of the user-system interaction of a mobile application. In our research we designed a method that aligns the inspection method “Software ArchitecTure analysis of Usability Requirements realizatioN” SATURN and a mobile usability evaluation in the form of a user test. We propose to use mobile context factors and thus requirements as a common basis for both inspection and user test. After conducting both analysis and user test, the results described as usability problems are mapped and discussed. The mobile context factors identified define and describe the usage context of a mobile application. We exemplify and apply our approach in a case study. This allows us to show how our method can be used to identify more usability problems than with each method separately. Additionally, we could confirm the validity and identified the severity of usability problems found by both methods. Our work presents how a combination of both methods allows to address usability issues in a more holistic way. We argue that the increased quantity and quality of results can lead to a reduction of the number of iterations required in early stages of an iterative software development process.     

粗糙关系数据库的数学基础

在引入粗糙关系数据库（Rough Relational Database,RRDB）的基本概念基础上,分析得出粗糙关系数据库中使用的几个主要数学理论包括等价关系、分解、位模式、粗糙熵及粗糙集理论,并进一步深入研究了这些理论在RRDB中的相关性质,对它们在粗糙关系数据库中的应用进行了探讨。     

Enhanced ER to relational mapping and interrelational normalization

This paper develops a method that maps an enhanced Entity-Relationship (ER+) schema into a relational schema and normalizes the latter into an inclusion normal form (IN-NF). Unlike classical normalization that concerns individual relations only, IN-NF takes interrelational redundancies into account and characterizes a relational database schema as a whole. The paper formalizes the sources of such interrelational redundancies in ER+ schemas and specifies the method to detect them. Also, we describe briefly a Prolog implementation of the method, developed in the context of a Computed-Aided Software Engineering shell and present a case study.     

Fuzzy XML data modeling with the UML and relational data models

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data modeling has been extensively investigated in various data models. Currently, huge amounts of electronic data are available on the Internet, and XML has been the de facto standard of information representation and exchange over the Web. This paper focuses on fuzzy XML data modeling, which is mainly involved in the representation model of the fuzzy XML, its conceptual design, and its storage in databases. Based on “possibility distribution theory”, we developed this fuzzy XML data model. We developed this fuzzy UML data model to design the fuzzy XML model conceptually. We investigated the formal conversions from the fuzzy UML model to the fuzzy XML model and the formal mapping from the fuzzy XML model to the fuzzy relational databases.