Idiom 0: Keep state variables to the minimum

In imperative programming, it is common to use mutable variable assignments liberally, but to exercise caution whenever mutable variables have a global scope. In TLA+, mutable variables are always global, so it is important to use them carefully and in a way that accurately reflects the global state of the system you are specifying.


A good TLA+ specification minimizes the computation state and makes it visible.

TLA+ does not have a special syntax for variable assignment. For a good reason. The power of TLA+ is in writing constraints on variables rather than in writing detailed commands. If you have been writing in languages such as C, C++, Java, Python, your first reflex would be to define a variable to store the intermediate result of a complex computation.

In programming languages, we introduce temporary variables for several reasons:

  1. To avoid repetitive computations of the same expression,
  2. To break down a large expression into a series of smaller expressions,
  3. To make the code concise.

Point 1 is a non-issue in TLA+, as it is mostly executed in the reader's brain, and people are probably less efficient in caching expressions than computers. Points 2 and 3 can be nicely addressed with LET-definitions in TLA+. Hence, there is no need for auxiliary variables.

Usually, we should minimize the specification state, that is, the scope of the data structures that are declared with VARIABLES. It does not mean that one variable is always better than two. It means that what is stored in VARIABLES should be absolutely necessary to describe the computations or the observed properties.


By avoiding auxiliary state variables, we localize the updates to the state. This improves specification readability. It also helps the tools, as large parts of the specification become deterministic.


Sometimes, we have to expose the internals of the computation. For instance, if we want to closely monitor the values of the computed expressions, when using the specification for model-based testing.

Sometimes, we have to break this idiom to make the specification more readable. Here is an example by Markus Kuppe. The specification of BlockingQueue that has one more variable is easier to read than the original specification with a minimal number of variables.


Consider the following implementation of Bubble sort in Python:

    my_list = [5, 4, 3, 8, 1]
    finished = False
    my_list_len = len(my_list)  # cache the length
    while not finished:
        finished = True
        if my_list_len > 0:
            prev = my_list[0]       # save the first element to use in the loop
        for i in range(1, my_list_len):
            current = my_list[i]
            if prev <= current:
                # save current for the next iteration
                prev = current
                # swap the elements
                my_list[i - 1] = current
                my_list[i] = prev
                finished = False

Notice that we have introduced three local variables to optimize the code:

  • my_list_len to cache the length of the list,
  • prev to cache the previously accessed element of the list, in order to minimize the number of list accesses,
  • current to cache the iterated element of the list.

In TLA+, one usually does not introduce local variables for the intermediate results of the computation, but rather introduces variables to represent the essential part of the algorithm state. (While we have spent some time on code optimization, we might have missed the fact that our sorting algorithm is not as good as Quicksort.) In the above example, the essential variables are finished and my_list.

Compare the above code to (a slightly more abstract) bubble sort in TLA+:

EXTENDS Integers, Sequences

in_list == <<5, 4, 3, 8, 1>>
VARIABLES my_list, finished

Init ==
    /\ my_list = in_list
    /\ finished = FALSE

IsSorted(lst) ==
    \A i \in DOMAIN lst \ {1}:
        lst[i - 1] <= lst[i]

WhenSorted ==
    /\ IsSorted(my_list)
    /\ finished' = TRUE
    /\ UNCHANGED my_list

WhenUnsorted ==
    /\ \E i \in DOMAIN my_list \ {1}:
        /\ my_list[i - 1] > my_list[i]
        /\ my_list' = [my_list EXCEPT ![i - 1] = my_list[i],
                                      ![i] = my_list[i - 1]]
    /\ finished' = FALSE

Next ==
    IF finished
    THEN UNCHANGED <<my_list, finished>>
    ELSE WhenSorted \/ WhenUnsorted

Our TLA+ code contains only two state variables: my_list and finished. Other variables are introduced by quantifiers (e.g., \E i \in ...). The state variables are not updated in the sense of programming languages. Rather, one writes constraints over unprimed and primed versions, e.g.:

        /\ my_list' = [my_list EXCEPT ![i - 1] = my_list[i],
                                      ![i] = my_list[i - 1]]

Of course, one can introduce aliases for intermediate expressions, for instance, by using let-definitions:

        LET prev == my_list[i - 1]
            current == my_list[i]
        /\ prev > current
        /\ my_list' = [my_list EXCEPT ![i - 1] = current, ![i] = prev]

However, the let-definitions are not variables, they are just aliases for more complex expressions. Importantly, one cannot update the value of an expression that is defined with a let-definition. In this sense, TLA+ is similar to functional languages, where side effects are carefully avoided and minimized.

In contrast to functional languages, the value of TLA+ is not in computing the result of a function application, but in producing sequences of states (called behaviors). Hence, some parts of a useful TLA+ specification should have side effects to record the states.