| Goal | Find non-key base table columns with the same name and type that have different default values. Be consistent. Columns with the same name and type shouldn't probably have different default values in case of different tables. "If you do something a certain way, do all similar things in the same way." (Robert C. Martin, Clean Code) |
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| Notes | In case of the string_agg function, the line break (br) tag is used as a part of the separator for the better readability in case the query result is displayed in a web browser. The query excludes columns that name suggests that it contains data about state/status. Entities that belong to different entity types might have different inital state. The queries consider both column names in Estonian and English. |
| Type | Problem detection Each row in the result could represent a flaw in the design |
| Reliability | Low Many false-positive results |
| License | MIT (opens in new tab) |
| Fixing Suggestion | Use default values consistently. |
| Data Source | INFORMATION_SCHEMA+system catalog |
| SQL Query |
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Collections
This query belongs to the following collections:
Find problems about base tables
A selection of queries that return information about the data types, field sizes, default values as well as general structure of base tables. Contains all the types of queries - problem detection, software measure, and general overview
Find problems automatically
Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not .
| Name | Description |
|---|---|
| Find problems about base tables | A selection of queries that return information about the data types, field sizes, default values as well as general structure of base tables. Contains all the types of queries - problem detection, software measure, and general overview |
| Find problems automatically | Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not . |
Categories
This query is classified under the following categories:
Default value
Queries of this catergory provide information about the use of default values.
Inconsistencies
Queries of this catergory provide information about inconsistencies of solving the same problem in different places.
Result quality depends on names
Queries of this category use names (for instance, column names) to try to guess the meaning of a database object. Thus, the goodness of names determines the number of false positive and false negative results.
Validity and completeness
Queries of this category provide information about whether database design represents the world (domain) correctly (validity) and whether database design captures all the information about the world (domain) that is correct and relevant (completeness).
| Name | Description |
|---|---|
| Default value | Queries of this catergory provide information about the use of default values. |
| Inconsistencies | Queries of this catergory provide information about inconsistencies of solving the same problem in different places. |
| Result quality depends on names | Queries of this category use names (for instance, column names) to try to guess the meaning of a database object. Thus, the goodness of names determines the number of false positive and false negative results. |
| Validity and completeness | Queries of this category provide information about whether database design represents the world (domain) correctly (validity) and whether database design captures all the information about the world (domain) that is correct and relevant (completeness). |
Further reading and related materials:
| Reference |
|---|
| The corresponding code smell in case of cleaning code is "G11: Inconsistency". (Robert C. Martin, Clean Code) |
| Smell "Overloaded attribute names": Sharma, T., Fragkoulis, M., Rizou, S., Bruntink, M. and Spinellis, D.: Smelly relations: measuring and understanding database schema quality. In: Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Practice, pp. 55-64. ACM, (2018). |