From requirements to acceptance tests

From user requirements definition to accepted software system, the software project management wants to be sure that the system will meet the requirements. For the development of a telecommunication satellites Control Centre, C.N.E.S. has used new rules to make the use of tracing matrix easier. From Requirements to Acceptance Tests, each item of a document must have an identifier. A unique matrix traces the system and allows the tracking of the consequences of a change in the requirements. A tool has been developed, to import documents into a relational data base. Each record of the data base corresponds to an item of a document, the access key is the item identifier. Tracing matrix is also processed, providing automatically links between the different documents. It enables the reading on the same screen of traced items. For example one can read simultaneously the User Requirements items, the corresponding Software Requirements items and the Acceptance Tests

Rules for mapping a conceptual model onto various data base management systems. Available in 2 volumes.

The design and implementation of data bases involve, firstly, the formulation of a conceptual data model by systematic analysis of the structure and information requirements of the organisation for which the system is being designed; secondly, the logical mapping of this conceptual model onto the data structure of the target data base management system (DBMS); and thirdly, the physical mapping of this structured model into storage structures of the target DBMS. The accuracy of both the logical and physical mapping determine the performance of the resulting systems. This thesis describes research which develops software tools to facilitate the implementation of data bases. A conceptual model describing the information structure of a hospital is derived using the Entity-Relationship (E-R) approach and this model forms the basis for mapping onto the logical model. Rules are derived for automatically mapping the conceptual model onto relational and CODASYL types of data structures. Further algorithms are developed for partly automating the implementation of these models onto INGRES, MIMER and VAX-11 DBMS

Stock Selection System: Building Long/Short Portfolios Using Intraday Patterns

AbstractWe present the architecture of a complete intraday trading management system using a stock selection algorithm for building long/short portfolios. Our approach for stock selection is based on knowledge discovery in large databases technologies; more specifically, we build techniques that allow one to discover hidden price patterns which are capable of predicting the direction of stock prices. The base of the whole system is a novel pattern mining algorithm from time-series data, which involves highly compute-intensive aggregation calculations as complex but efficient distributed SQL queries on the relational databases that store the time-series. This algorithm follows similar path to Association Rule Mining algorithms (such as the Apriori and FP-Growth algorithms) but with major differences. First, it has one step more at initialization which uses a rule-based generator algorithm that transforms relations and data structures in a binary string format. These patterns contain mixed information of small price patterns (3, 4 or 5 candlesticks) and trading signals/filters produced by technical indicators. As output, instead of generating association rules, it produces probabilities (varies between 60% and 95%) about the future stock price direction such as “within next 5 periods, price will increase (or decrease) more than 2%”. Then, the stock selection system exploits all this information and uses it to find those stocks that appear to form patterns which have the highest accuracy in predicting prices. Each time period (finest interval length being 10minutes), the stock selector system, having the support of trading systems, examines and decides which stocks should be replaced in current portfolio by other more profitable stocks. The system testing, which produced interested results, is made of portfolio of 10 stocks having open long position and 5 stocks having open short positions

Towards Intelligent Databases

This article is a presentation of the objectives and techniques of deductive databases. The deductive approach to databases aims at extending with intensional definitions other database paradigms that describe applications extensionaUy. We first show how constructive specifications can be expressed with deduction rules, and how normative conditions can be defined using integrity constraints. We outline the principles of bottom-up and top-down query answering procedures and present the techniques used for integrity checking. We then argue that it is often desirable to manage with a database system not only database applications, but also specifications of system components. We present such meta-level specifications and discuss their advantages over conventional approaches

Algebraic optimization of recursive queries

Over the past few years, much attention has been paid to deductive databases. They offer a logic-based interface, and allow formulation of complex recursive queries. However, they do not offer appropriate update facilities, and do not support existing applications. To overcome these problems an SQL-like interface is required besides a logic-based interface.\ud \ud In the PRISMA project we have developed a tightly-coupled distributed database, on a multiprocessor machine, with two user interfaces: SQL and PRISMAlog. Query optimization is localized in one component: the relational query optimizer. Therefore, we have defined an eXtended Relational Algebra that allows recursive query formulation and can also be used for expressing executable schedules, and we have developed algebraic optimization strategies for recursive queries. In this paper we describe an optimization strategy that rewrites regular (in the context of formal grammars) mutually recursive queries into standard Relational Algebra and transitive closure operations. We also describe how to push selections into the resulting transitive closure operations.\ud \ud The reason we focus on algebraic optimization is that, in our opinion, the new generation of advanced database systems will be built starting from existing state-of-the-art relational technology, instead of building a completely new class of systems

Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database

SoK: Cryptographically Protected Database Search

Protected database search systems cryptographically isolate the roles of reading from, writing to, and administering the database. This separation limits unnecessary administrator access and protects data in the case of system breaches. Since protected search was introduced in 2000, the area has grown rapidly; systems are offered by academia, start-ups, and established companies. However, there is no best protected search system or set of techniques. Design of such systems is a balancing act between security, functionality, performance, and usability. This challenge is made more difficult by ongoing database specialization, as some users will want the functionality of SQL, NoSQL, or NewSQL databases. This database evolution will continue, and the protected search community should be able to quickly provide functionality consistent with newly invented databases. At the same time, the community must accurately and clearly characterize the tradeoffs between different approaches. To address these challenges, we provide the following contributions: 1) An identification of the important primitive operations across database paradigms. We find there are a small number of base operations that can be used and combined to support a large number of database paradigms. 2) An evaluation of the current state of protected search systems in implementing these base operations. This evaluation describes the main approaches and tradeoffs for each base operation. Furthermore, it puts protected search in the context of unprotected search, identifying key gaps in functionality. 3) An analysis of attacks against protected search for different base queries. 4) A roadmap and tools for transforming a protected search system into a protected database, including an open-source performance evaluation platform and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac