Using SQL Queries to Evaluate the Design of SQL Databases

Software engineers often need to identify and correct design defects, i.e., recurring design problems that hinder development and maintenance by making programs harder to comprehend and/or evolve. While detection of design defects is an actively researched area, their correction — mainly a manual and time-consuming activity — is yet to be extensively investigated for automation. In this paper, we propose an automated approach for suggesting defect-correcting refactorings using relational concept analysis (rca). The added value of rca consists in exploiting the links between formal objects which abound in a software re-engineering context. We validated our approach on instances of the Blob design defect taken from four different open-source programs.KeywordsDesign DefectsRefactoringRelational Concept Analysis

Extending classical functional dependencies for physical database design

Design defects come from poor design choices and have the effect of degrading the quality of object-oriented designs.Therefore, they present opportunities for improvements.However, design defects have not been precisely specified and there are few appropriate tools that allow their detection as well as their correction. Our goal is to provide a systematic method to specify systematically design defects precisely and to generate automatically detection and correction algorithms from their specifications. The detection algorithms are based not only on metrics but also on semantical and structural properties whereas the correction algorithms are based on refactorings. We apply and validate these algorithms on open-source object-oriented programs to show that our method allows a systematic specification, a precise detection, and a suitable correction of design defects.

Design defects are one of the main reasons for the decline of software design quality. Effective detection of design defects plays an important role in improving software maintainability and scalability. On the basis of defining software design defects, according to C&K design metrics and heuristics, this paper extracts the relevant features of design defects. Based on classical machine learning methods, classifiers are trained for design defect, and candidate designs are classified by classifiers, so as to identify whether there is a design defect in the design. Experiments show that the method has high accuracy and recall rate in identifying design defects.

В статье рассматривается эффективность проектных решений BIM. В работе представлены результаты исследований в области использования инновационных технологий при проектировании зданий. Рассмотрены современные технологии информационного моделирования, в частности BIM, которые позволяют представить здание не только в трехмерном пространстве, но и позволяют проектировать его в динамической системе «проектирование – строительство – эксплуатация». Опыт использования BIM-технологий основан на выявлении ошибок на начальном этапе проектирования и возможности их устранения на этом же этапе. Анализ механизмов обнаружения проектных ошибок и дефектов лег в основу поставленной в работе задачи. Проанализирована модель об обнаружении дефектов. The paper discusses the effectiveness of BIM design solutions. The paper presents the results of research in the field of using innovative technologies in building design. Modern information modeling technologies, in particular BIM, which allow to represent a building not only in three-dimensional space, but also allow to design it in a dynamic system "design - construction - operation" are considered. The experience of using BIM-technologies is based on the detection of errors at the initial stage of design and the possibility of their elimination at the same stage. The analysis of mechanisms of detection of design errors and defects formed the basis of the task set in the paper. The model about defect detection is analyzed.

<div class="htmlview paragraph">Thermal testing of spacecraft electronic units prior to flight provides effective detection of design, process and workmanship defects. Thermal testing subjects units to cold and hot thermal environments beyond those expected in flight. The strength of screening effectiveness depends upon the number of cycles, the temperature range, and the temperature transition rate. MIL-HDBK-344 provides insight into the incurred stresses and quantitative value (precipitation efficiency) of the screening environment using these three test parameters.</div> <div class="htmlview paragraph">In this paper, MIL-HDBK-344 topics applicable to thermal testing of space hardware are summarized and comparisons are made between test environment strengths computed from MIL-HDBK-344 and MIL-STD-1540E. The weighting of these aforementioned test parameters in the precipitation efficiency equation are discussed and assessed. It was found that the fatigue equivalency equations in MIL-STD-1540E specify a significantly larger number of required cycles for various test temperature ranges as compared to cycles computed from MIL-HDBK-344 equations.</div>

The main goal of the paper is to give a formalization of the relational database schema integration process, as a part of a database schema design. We briefly describe the form type concept and the module schema design, which are related to the integration process. Database schema of the information system is obtained by progressive pairwise integration of so called database module schemes, that are usually built by different designers. An integration process is preceded by checking of database module schemes onto mutual consistency.

System catalog, which is a part of each SQL database, is a repository where the data in its base tables describes the SQL-schemas (schemas) in the database. The SQL standard specifies the Information Schema, which must contain virtual tables (views) that are created based on the base tables of the system catalog. In this paper, we investigate to what extent one can find information about possible design flaws of a SQL database by querying the tables in its Information Schema and possibly tables in its other schemas. We do this based on a set of SQL database design antipatterns, each of which presents a particular type of database design flaw.

Database schemas evolve over time to satisfy changing application requirements. If this evolution is not performed correctly, some quality attributes are at risk such as data integrity, functional correctness, or maintainability. To help developer teams in the design of database schemas, several design methodologies for NoSQL databases have proposed to use conceptual models during this process. The use of an explicit conceptual model can also help developers in the tasks of schema evolution. In this work-in-progress paper, we propose a framework that, given a change in the conceptual model, identifies what must be modified in a NoSQL database schema and the underlying data. We researched several open source projects that use Apache Cassandra to study the benefits of using a conceptual model during the schema evolution process as well as to understand how these models evolve. In this first work, we have focused on studying seven types of conceptual model changes identified in these projects. For each change we describe the transformation required in the database schema to maintain the consistency between the schema and the model as well as the migration of data required to the new schema version.

A design flaw is indicative of a potential shortcoming in the construction of a software system and can result in a reduction in the quality of the software. This study offers a means of detecting design flaws through the use of ontology-assisted flaw description and declarative meta programming. Ontology flaw structures are used to describe the flaw domains, while the use of a declarative-based method allows the design flaws which arise within an object-oriented system to be altered into these structures, thereby permitting their detection at the metalevel when declarative meta programming is employed. This research uses the method described in order to detect a number of design flaws which are already well-documented. The findings demonstrate that the method is successful in detecting those flaws, and that structural design flaw detection is particularly effective.

We describe the conceptual model of SORAC, a data modeling system developed at the University of Rhode Island. SORAC supports both semantic objects and relationships, and provides a tool for modeling databases needed for complex design domains. SORAC's set of built-in semantic relationships permits the schema designer to specify enforcement rules that maintain constraints on the object and relationship types. SORAC then automatically generates C++ code to maintain the specified enforcement rules, producing a schema that is compatible with Ontos. This facilitates the task of the schema designer, who no longer has to ensure that all methods on object classes correctly maintain necessary constraints. In addition, explicit specification of enforcement rules permits automated analysis of enforcement propagations. We compare the interpretations of relationships within the semantic and object-oriented models as an introduction to the mixed model that SORAC supports. Next, the set of built-in SORAC relationship types is presented in terms of the enforcement rules permitted on each relationship type. We then use the modeling requirements of an architectural design support system, called Arch Objects, to demonstrate the capabilities of SORAC. The implementation of the current SORAC prototype is also briefly discussed.

Software metrics are of great importance in object-oriented design assessment. They quantify various aspects of design entities and play an important role in predicting design quality. Despite the fact that software metrics have become increasingly useful, they raise several issues. Among them, relevant to our research are the issue of setting threshold values and the problem of measurement results interpretation. Fuzzy clustering analysis is used to overcome the limitations of the existing approaches that are using threshold values for metrics and to provide a better interpretation of the obtained measurement results. This paper focuses on metrics-based design flaw detection in object-oriented design. A new metric, Design Flaw Entropy which measures the distribution of design flaws into the analyzed system is introduced. To validate the proposed approach, a case study was also proposed.

The authors have proposed using category-theoretic sketches to enhance database design and integration methodologies. The algebraic context is called the Sketch Data Model (SkDM) and mathematically describes databases, views and their updates, and other database concepts. The system described here is a freely available graphical Java environment with a module that compiles a design incorporating algebraically specified constraints into database schemas that interface directly with modern database management systems. It therefore supports, inter alia, rapid prototyping.KeywordsSemantic data modelcategory theorygraphical database design

According to database theory, a database designer can specify any set of data dependencies, no matter how complex, to constrain a database scheme. This paper investigates how much complexity is actually needed in real-world situations. It is shown that every natural set of mvd's must belong to a class of mvd's called conflict-free. Conflict-free sets of mvd's have the desirable property that they allow a unique 4NF dependency preserving database scheme; moreover, non conflict-free sets have no such normalization. If a set of mvd's is not conflict-free, then the dependencies are inadequately specified; there are semantic concepts that are unrepresented in the scheme. These concepts are isolated, and it is shown that adding these concepts amounts to making the set of mvd's conflict-free.

Database system reengineering technique has been used to resolve the problem of converting from existing out-of-data database systems to new technique database systems in order to reduce the new system implementation cost. The technique consists of three parts: schema translation, data conversion, and program translation. The schema translation requires the transferring of existing database schema into the new database schema with better semantics. Recapturing the semantics is a complicated and difficult work. During the database design phase, the semantics has been lost from the conceptual data model to the logical data model. It is difficult to recapture it. After recapturing the semantics from the original conceptual database schema, we also need to have a sophisticated knowledge base to store the knowledge. The paper describes a new schema translation system, which can recapture the missing/hidden semantics of a database. The kernel of the system is an extended entity relationship (EER) data dictionary system (DDS), which can store all the semantics of the new database schema.