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Perhaps the type of a parameter should be BOOLEAN (based on parameter names)

Query goal: Find routine parameters that based on the name seem to hold truth values. Find parameters that name starts with "is_" or "has_" or "can_" or "on_" and that do not have Boolean type.
Notes about the query: The query does not consider objects that are a part of an extension. There could be multiple routines with the same name but with different parameters in the same schema (overloading). Thus, for the unique identification of the routine it is necessary to present also its parameters in addition to the schema name and routine name.
Query type: Problem detection (Each row in the result could represent a flaw in the design)
Query reliability: Medium (Medium number of false-positive results)
Query license: MIT License
Data source: INFORMATION_SCHEMA+system catalog
SQL query: Click on query to copy it

WITH params AS (SELECT 
specific_schema AS routine_schema,
regexp_replace(specific_name,'_[0-9]*$','') AS routine_name,
pg_get_function_identity_arguments(translate(substring(specific_name,'_[0-9]+$'),'_','')::int::oid) AS parameters,
parameter_name,
ordinal_position,
data_type
FROM 
information_schema.parameters
WHERE specific_schema NOT IN (SELECT schema_name
FROM INFORMATION_SCHEMA.schemata
WHERE schema_name<>'public' AND
schema_owner='postgres' AND schema_name IS NOT NULL) 
AND NOT EXISTS (SELECT 1
FROM pg_catalog.pg_depend d inner join pg_catalog.pg_proc pc ON d.objid=pc.oid
WHERE EXISTS (SELECT 1 FROM pg_catalog.pg_extension e WHERE d.refobjid=e.oid) AND
pc.proname || '_' || pc.oid = parameters.specific_name))
SELECT routine_schema, routine_name, parameters, parameter_name, ordinal_position, data_type
FROM params
WHERE parameter_name~*'^(is|has|can|on)_' 
AND data_type<>'boolean'
ORDER BY routine_schema, routine_name, parameters, ordinal_position;

Collections where the query belongs to

Collection nameCollection description
Find problems automaticallyQueries, 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 .
Lexicon bad smells and linguistic antipatternsQueries made to find the occurrences of lexicon bad smells and linguistic antipatterns

Categories where the query belongs to

Category nameCategory description
Boolean dataQueries of this category provide information about truth-values data that is kept in the database.
Data typesQueries of this category provide information about the data types and their usage.
Result quality depends on namesQueries 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.
User-defined routinesQueries of this category provide information about the user-defined routines

Reference materials for further reading

Reference
Linguistic antipattern "D.2 Name suggests boolean but type is not": Arnaoudova, V., Di Penta, M., Antoniol, G., 2016. Linguistic antipatterns: What they are and how developers perceive them. Empirical Software Engineering, 21(1), pp.104-158.

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