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Detecting C o m m o n Design Errors
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A s indicated in 5, y o u should u s e the diagram rules to ensure that there are n o obvious errors in your ERD You also should u s e the guidelines in this section to check for design errors D e s i g n errors are more difficult to detect and resolve than diagram errors because design errors involve the meaning o f elements on a diagram, not just a diagram's structure The following subsections explain c o m m o n design problems, while Table 64 summarizes them
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In a large ERD, it is easy to connect the wrong entity types or omit a necessary relationship You can connect the wrong entity types if y o u do not consider all o f the queries that a data base should support For example in Figure 6 1 2 , i f Customer is connected directly to Reading instead o f being connected to Meter, the control o f a meter cannot be established unless the meter has b e e n read for the customer Queries that involve meter control cannot be answered except through consideration o f meter readings If the requirements do not directly indicate a relationship, y o u should consider indirect implications to detect whether a relationship is required For example, the requirements for the water utility database do not directly indicate the n e e d for a relationship from Bill to Reading However, careful consideration o f the consumption calculation reveals the need for a relationship The Includes relationship connects a bill to its most recent meter read ings, thus supporting the consumption calculation
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The typical error involves the usage o f a 1-M relationship instead o f an M - N relationship This error can be caused by an omission in the requirements For example, if the requirements just indicate that work assignments involve a collection o f employees, y o u should not assume that an employee can be related to just one work assignment You should gather additional requirements to determine if an employee can be associated with multiple work assignments Other incorrect cardinality errors that you should consider are reversed cardinalities (1-M relationship should be in the opposite direction) and errors on a minimum cardinal ity The error o f reversed cardinality is typically an oversight The incorrect cardinalities in dicated in the relationship specification are not noticed after the E R D is displayed You should carefully check all relationships after specification to ensure consistency with your intent Errors on m i n i m u m cardinality are typically the result o f overlooking key words in problem narratives such as "optional" and "required"
Overuse
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Generalization hierarchies and M-way associative entity types are specialized data model ing constructs A typical novice mistake is to use them inappropriately You should not use generalization hierarchies just because an entity can exist in multiple states For example, the requirement that a project task can be started, in process, or complete does not indicate the need for a generalization hierarchy If there is an established classification and specialized attributes and relationships for subtypes, a generalization hierarchy is an appropriate tool A n M-way associative entity type (an associative entity type representing an M-way re lationship) should be used w h e n the database is to record combinations o f three (or more) objects rather than just combinations o f two objects In most cases, only combinations o f two objects should be recorded For example, if a database needs to record the skills pro vided by an employee and the skills required by a project, binary relationships should be used If a database needs to record the skills provided by employees for specific projects, an M - w a y associative entity type is needed N o t e that the former situation with binary rela tionships is much more c o m m o n than the latter situation represented by an M-way associa tive entity type
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