Academic literature on the topic 'DBMS Testing'

Abstract The work examines the effectiveness of the replication mechanism of the X production company database. In order to extend the functionality of the computer database of the enterprise, a model of its resource flow was created and an intensional and extensional part was created for a test database based on real enterprise resources. The model has been simplified to 3-rd normal form. The implementation was done in the MySQL database system. Two different operating systems were selected for testing: Windows and Linux. The database management system (DBMS) is working under the GPL license. MySQL DBMS offers many security mechanisms, and to secure the database, system of users permissions to objects have been selected and also an encryption of access passwords for users and connections to servers was used. A replication engine based on the binary log and the model “main server and backup server” was used to create a copy of the enterprise data.

This paper is projecting website system built on top of PHP Framework Laravel 5.2 and MySQL DBMS which contains 6 modules of scientific conference management needs, Master Conference, User Management, Submission, Website Management, Schedule, and Post Conference. From the development and testing system with Black Box method concluded that the system is running well and feasible to be applied to the management of the conference in Electrical Engineering Program Faculty of Engineering Udayana University.

NVMe SSD hugely boosts the I/O speed, with up to GB/s throughput and microsecond-level latency. Unfortunately, DBMS users can often find their high-performanced storage devices tend to deliver less-than-expected or even worse performance when compared to their traditional peers. While many works focus on proposing new DBMS designs to fully exploit NVMe SSDs, few systematically study the symptoms, root causes and possible detection methods of such performance mismatches on existing databases. In this paper, we start with an empirical study where we systematically expose and analyze the performance mismatches on six popular databases via controlled configuration tuning. From the study, we find that all six databases can suffer from performance mismatches. Moreover, we conclude that the root causes can be categorized as databases' unawareness of new storage devices characteristics in I/O size, I/O parallelism and I/O sequentiality. We report 17 mismatches to developers and 15 are confirmed. Additionally, we realize testing all configuration knobs yields low efficiency. Therefore, we propose a fast performance mismatch detection framework and evaluation shows that our framework brings two orders of magnitude speedup than baseline without sacrificing effectiveness.

Information retrieval system is a system that is widely used to retrieve information. This research will discuss how the system finds back the information stored in database tables. Tables in the database are arranged to store all forms of data entered by database users so that later the stored data can be used again. Re-accessing the database's information must go through a mechanism known as a database management system (DBMS). One of the most widely used DBMS is MySQL. By using a DBMS, information and data can be manipulated according to user needs. Data manipulation in the database is done in a special language, namely SQL (Structure Query Language). Mastery of SQL commands is an obligation for database users so that the manipulated data can produce the required information. However, many database users still do not understand how the actual SQL command syntax manages and manipulates data into information. This is, of course, very risky if the solution is not immediately sought because it will hinder the process of retrieving information from the data stored in the database. For this problem to be resolved, it is necessary to design a system that can help database users translate their wishes into SQL command syntax. This paper will discuss how a command in Indonesian can be translated into SQL command syntax. The method used to solve this research problem is rule-based. There are two stages in the main process: the pre-processing stage, which consists of a word tokenization process, and a translation stage, including a keyword grouping process. This keyword grouping process consists of the keyword group analysis phase, table and column analysis, identification of SQL commands, and mapping of SQL commands. From all stages that have been passed and testing of 7 scenarios with ten (10) commands for each scenario, the accuracy is 81.42%. The inaccuracy in the testing process is more a problem of displaying data from two or more tables, for example, using the join table command. This problem can be addressed by adding new rules for the use of table joins.