The FEEL language


Literal expressions, decision tables, and many other DMN elements rely on textual expressions to work. The FEEL (Friendly Enough Expression Language) shines as a readable language for programmers and business analysts. The language design follows these principles:

  • Side-effect free
  • Simple data model with numbers, dates, strings, lists, and contexts
  • Simple syntax designed for a broad audience
  • Three-valued logic (true, false, null)

This section presents an example-guided approach, that shows the most used features of FEEL.

Conditional statements

Here you can see an example of a decision node with a literal expression as the decision logic. Notice how the FEEL expression defines the output value:

You also could define different behaviors:

Example Return value
if 20 > 0 then "YES" else "NO" "YES"
if (20 - (10 * 2)) > 0 then "YES" else "NO" "NO"
if (2 ** 3) = 16 then "YES" else "NO" "YES"
if (4 / 2) != 2 then "YES" else "NO" "NO"

Loop statements

Loop statements can transform lists or verify if some elements satisfy a specific condition:

Example Return value
for i in [1, 2, 3, 4, 5] return i * i [1, 4, 9, 16, 25]
some i in [1, 2, 3, 4, 5] satisfies i > 4 true
some i in [1, 2, 3, 4, 5] satisfies i > 5 false

If you're curious about this kind of statement, you may try to discover more about this one: every i in [list] satisfies [condition] ;-)

Range statements

Ranges have a tricky syntax to determine included and excluded elements in a given interval. The following examples clarify that by checking if some number is included in each range:

Example Return value
1 in [1..10] true
1 in (1..10] false
10 in [1..10] true
10 in [1..10) false

String functions

FEEL has many useful functions to handle strings. Here you can see a list the most frequently used:

Example Return value
string length("Learn DMN in 15 minutes") 23
upper case("Learn DMN in 15 minutes") "LEARN DMN IN 15 MINUTES"
lower case("Learn DMN in 15 minutes") "learn dmn in 15 minutes"
substring("Learn DMN in 15 minutes", 7, 3) "DMN"
replace("Learn DMN in 15 minutes", "DMN", "FEEL") "Learn FEEL in 15 minutes"
contains("Learn DMN in 15 minutes", "DMN") true
contains("Learn DMN in 15 minutes", "FEEL") false
string(123) "123"

Number functions

FEEL has many useful functions to handle numbers as well:

Example Return value
abs(-1) 1
even(2) true
even(3) false
odd(4) false
odd(5) true
sqrt(9) 3.0

Date and Time functions

You can create date or time values by using strings or numbers, see:

Example Return value
date("2020-12-31") [2020, 12, 31]
date(2020, 12, 31) [2020, 12, 31]
time("14:59:59") [14, 59, 59]
time(14, 59, 59) [14, 59, 59]
date and time("2020-12-31T14:59:59") [2020, 12, 31, 14, 59, 59]
date and time(2020, 12, 31, 14, 59, 59) [2020, 12, 31, 14, 59, 59]
day of week(date("2020-12-31")) "Thursday"
month of year(date("2020-12-31")) "December"
week of year(date("2020-12-31")) 53

List functions

Finally, FEEL has a bunch of functions to manipulate lists intuitively:

Example Return value
concatenate([1, 2, 3], [4, 5]) [1, 2, 3, 4, 5]
count([1, 2, 3, 4, 5]) 5
distinct values([1, 1, 2, 2, 3, 3, 4, 5]) [1, 2, 3, 4, 5]
flatten([1, [2, 3], [4, 5]]) [1, 2, 3, 4, 5]
max([1, 2, 3, 4, 5]) 5
mean([1, 2, 3, 4, 5]) 3
min([1, 2, 3, 4, 5]) 1
reverse([1, 2, 3, 4, 5]) [5, 4, 3, 2, 1]
sort([5, 4, 1, 2, 3]) [1, 2, 3, 4, 5]
sum([1, 2, 3, 4, 5]) 15
index of(["a", "b", "c", "d", "e", "f"], "c") 3
append([1, 2, 3, 4, 5], 6) [1, 2, 3, 4, 5, 6]
list contains([1, 2, 3, 4, 5], 5) true
list contains([1, 2, 3, 4, 5], 6) false
remove(["a", "b", "c", "d", "e", "f"], 2) ["a", "c", "d", "e", "f"]
sublist([1, 2, 3, 4, 5], 2, 3) [2, 3, 4]

Here you've learned the most frequently used FEEL expressions. There are other powerful features you may learn on the DMN spec. If you're feeling inspired, take a look there :-)

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