When an SQL WHERE clause contains three or more combined AND and OR conditions on similar values, which keyword or keywords make the condition easier to write and understand?

Introduction / Context:
When writing SQL WHERE clauses, it is common to combine several equality and inequality tests using AND and OR. For example, you might need to test whether a value equals one of several constants or not equal to a set of constants. If you write every comparison separately, the condition quickly becomes long and hard to read. SQL provides the IN and NOT IN keywords to simplify such conditions. This question asks which keyword or keywords are most appropriate when three or more AND or OR conditions are combined in this way.

Given Data / Assumptions:

We are dealing with an SQL WHERE clause that has many similar equality or inequality comparisons.
There are at least three conditions combined with AND or OR operators.
The comparisons involve testing whether a column value matches or does not match several constant values.
The goal is to make the condition easier to write and easier for humans to understand.
We are not focusing on pattern matching or wildcard matching here.

Concept / Approach:
The IN keyword allows you to test whether an expression equals any value in a list. For example, column_name IN (10, 20, 30) is equivalent to column_name = 10 OR column_name = 20 OR column_name = 30, but is much shorter and more readable. The NOT IN keyword is the logical negation and checks that the expression is not equal to any value in the list. For example, column_name NOT IN (10, 20, 30) is equivalent to column_name <> 10 AND column_name <> 20 AND column_name <> 30. Whenever several equality or inequality predicates target the same column, rewriting them using IN or NOT IN is the standard simplification technique.

Step-by-Step Solution:
Step 1: Consider a situation with three or more OR conditions such as column_name = 10 OR column_name = 20 OR column_name = 30. This pattern is a perfect candidate for simplification using IN, giving column_name IN (10, 20, 30). Step 2: Consider a situation with three or more AND conditions such as column_name <> 10 AND column_name <> 20 AND column_name <> 30. This scenario is the natural use case for NOT IN, giving column_name NOT IN (10, 20, 30). Step 3: Recognize that the question mentions three or more AND and OR conditions, which implies that both positive membership tests and negative membership tests may appear in typical queries. Step 4: Because both kinds of patterns exist, the best answer is that both IN and NOT IN are useful tools for simplifying such conditions, rather than only one of them.

Verification / Alternative check:
A quick verification can be done by comparing the logical meaning of the expanded form with the compact IN or NOT IN form. For example, check that column_name IN ('A', 'B', 'C') is logically equivalent to column_name = 'A' OR column_name = 'B' OR column_name = 'C'. If you expand the IN list, you recover the original separate OR predicates. Similarly, column_name NOT IN ('A', 'B', 'C') is logically equivalent to column_name <> 'A' AND column_name <> 'B' AND column_name <> 'C'. Thus, IN and NOT IN preserve the semantics while making the expression shorter and easier to understand.

Why Other Options Are Wrong:
Using ONLY the LIKE keyword is wrong because LIKE is used for pattern matching with wildcards and is not intended to replace equality tests against a fixed list of constants. It also introduces unnecessary complexity and can be slower.
Using ONLY IN is incomplete because it covers only the case where you want to match any of several values, and does not help when you need to exclude several values, which is handled cleanly by NOT IN.
Using ONLY NOT IN is similarly incomplete because sometimes you want to select rows that match any of several allowed values, where IN is the natural choice.

Common Pitfalls:
A common mistake is to mix IN with additional equality predicates on the same column, such as column_name = 10 OR column_name IN (20, 30), when a single IN list would be clearer. Another pitfall is to use NOT IN on a column that contains null values without understanding that comparisons with null may yield unknown results, potentially filtering out more rows than expected. Developers sometimes also overuse LIKE for simple equality tests, which can cause confusion and performance issues. Recognizing when to use IN and NOT IN leads to cleaner SQL and fewer logical errors.

Final Answer:
When several AND and OR conditions are combined, it is easiest to use both IN and NOT IN as appropriate to simplify the SQL condition.