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1.8 Maintenance

Databases are one of the more enduring software engineering artefacts; it is not uncommon to find database implementations whose use can be traced back for 15 years or more. Consequently, maintenance of the database is a key issue.

Maintenance can take three main forms:

  • Operational maintenance, where the performance of the database is monitored. If it falls below some acceptable standard, then reorganisation of the database, usuall
    Author(s): The Open University

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1.7 Testing

The aim of testing is to uncover errors in the design and implementation of the database, its structure, constraints and associated user and management support. Testing is usually considered to involve two main tasks – validation and verification. Without adequate testing users will have little confidence in their data processing.

Validation answers the question: has the right database been developed to meet the requirements? It attempts to confirm that the right database has been co
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1.6.4 Supporting data management strategies

Most of the development we've covered so far in this course has focused on meeting specific user requirements – that is, ensuring the right data are constrained correctly and made available to the right user processes. However, other questions must also be addressed in order to support a data management strategy: How frequently should data be backed-up? What auditing mechanisms are required? Which users will be permitted to perform which functions? Which database tools and user processes w
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1.6.3 Supporting users and user processes

Use of a database involves user processes (either application programs or database tools) which must be developed outside of the database development. In terms of the three-schema architecture we now need to address the development of the external schema. This will define the data accessible to each user process or group of user processes. In reality, most DBMSs, and SQL itself, do not have many facilities to support the explicit definition of the external schema. However, by using built-in q
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1.6.2 Populating the database

After a database has been created, there are two ways of populating the tables – either from existing data, or through the use of the user applications developed for the database.

For some tables, there may be existing data from another database or data files. For example, in establishing a database for a hospital you would expect that there are already some records of all the staff that have to be included in the database. Data might also be bought in from an outside agency (address
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1.6.1 Realising the design

So far we have been concerned only with the specification of a logical schema. We now need our database to be created according to the definitions we have produced. For an implementation with a relational DBMS, this will involve the use of SQL to create tables and constraints that satisfy the logical schema description and the choice of appropriate storage schema (if the DBMS permits that level of control).

One way to achieve this is to write the appropriate SQL DDL statements into a f
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1.6 Implementation

Implementation involves the construction of a database according to the specification of a logical schema. This will include the specification of an appropriate storage schema, security enforcement, external schema, and so on. Implementation is heavily influenced by the choice of available DBMS, database tools and operating environment. There are additional tasks beyond simply creating a database schema and implementing the constraints – data must be entered into the tables, issues relating
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1.5 Design

Database design starts with a conceptual data model and produces a specification of a logical schema; this will usually determine the specific type of database system (network, relational, object-oriented) that is required, but not the detailed implementation of that design (which will depend on the operating environment for the database such as the specific DBMS available). The relational representation is still independent of any specific DBMS; it is another conceptual data model.

Our
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1.4 Analysis

Data analysis begins with the statement of data requirements and then produces a conceptual data model. The aim of analysis is to obtain a detailed description of the data that will suit user requirements so that both high and low level properties of data and their use are dealt with. These include properties such as the possible range of values that can be permitted for attributes such as, in the Open University example for instance, the course code, course title and credit points.
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1.3 Requirements gathering

Here we are concerned only with the requirements that relate specifically to the data. Establishing requirements involves consultation with, and agreement among, all the users as to what persistent data they want to store along with an agreement as to the meaning and interpretation of the data elements. The data administrator plays a key role in this process as they overview the business, legal and ethical issues within the organisation that impact on the data requirements.

The data req
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1.2 A development life cycle

Database development is just one part of the much wider field of software engineering, the process of developing and maintaining software. A core aspect of software engineering is the subdivision of the development process into a series of phases, or steps, each of which focuses on one aspect of the development. The collection of these steps is sometimes referred to as a development life cycle. The software product moves through this life cycle (sometimes repeatedly as i
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