# ADR-015: Informal Trace Format in JSON

authorsproposed bylast revised
Igor KonnovVitor Enes, Andrey Kupriyanov2022-11-03

## Summary

We propose a simple format for counterexamples (traces) in JSON. Although Apalache already supports serialization to JSON in ADR005, it is a general serialization format for all the constructs of TLA+ that are supported by Apalache. This makes tool integration harder. It also make it hard to communicate counterexamples to engineers who are not familiar with TLA+. This ADR-015 contains a very simple format that does not require any knowledge of TLA+ and can be easily integrated into other tools.

## Context

A TLA+ execution (called a behavior in TLA+) is a very powerful concept. It can represent virtually any execution of a state machine, including sequential programs, concurrent programs, and distributed systems. Counterexamples that are produced by TLC and Apalache are just executions of a TLA+ state machine. These counterexamples have two shapes:

1. A finite execution, that is, a sequence of states.

2. A lasso execution, that is, a finite sequence of states (prefix) followed by an infinitely repeated sequence of states (loop). Any infinite execution of a finite-state system can be represented by a lasso. (In general, executions of infinite-state systems cannot be represented by lassos.)

Although the concept of an execution in TLA+ is quite simple, it builds upon the vocabulary of TLA+. Moreover, TLA+ counterexamples are using the expression language of TLA+.

To illustrate the problem, consider a very simple TLA+ specification of the MissionariesAndCannibals puzzle (specified by Leslie Lamport). We use a typed version of this specification, see MissionariesAndCannibalsTyped. Consider the following instance of the specification:

------------------- MODULE MC_MissionariesAndCannibalsTyped -----------------
Missionaries == { "m1_OF_PERSON", "m2_OF_PERSON" }
Cannibals == { "c1_OF_PERSON", "c2_OF_PERSON" }

VARIABLES
\* @type: Str;
bank_of_boat,
\* @type: Str -> Set(PERSON);
who_is_on_bank

INSTANCE MissionariesAndCannibalsTyped

NoSolution ==
who_is_on_bank["E"] /= {}
=============================================================================


By checking the invariant NoSolution, we obtain the following counterexample in TLA+:

---------------------------- MODULE counterexample ----------------------------

EXTENDS MC_MissionariesAndCannibalsTyped

(* Constant initialization state *)
ConstInit == TRUE

(* Initial state *)
State0 ==
bank_of_boat = "E"
/\ who_is_on_bank
= "E"
:> { "c1_OF_PERSON", "c2_OF_PERSON", "m1_OF_PERSON", "m2_OF_PERSON" }
@@ "W" :> {}

(* Transition 0 to State1 *)
State1 ==
bank_of_boat = "W"
/\ who_is_on_bank
= "E" :> { "c1_OF_PERSON", "m1_OF_PERSON" }
@@ "W" :> { "c2_OF_PERSON", "m2_OF_PERSON" }

(* Transition 0 to State2 *)
State2 ==
bank_of_boat = "E"
/\ who_is_on_bank
= "E" :> { "c1_OF_PERSON", "m1_OF_PERSON", "m2_OF_PERSON" }
@@ "W" :> {"c2_OF_PERSON"}

(* Transition 0 to State3 *)
State3 ==
bank_of_boat = "W"
/\ who_is_on_bank
= "E" :> {"c1_OF_PERSON"}
@@ "W" :> { "c2_OF_PERSON", "m1_OF_PERSON", "m2_OF_PERSON" }

(* Transition 0 to State4 *)
State4 ==
bank_of_boat = "E"
/\ who_is_on_bank
= "E" :> { "c1_OF_PERSON", "c2_OF_PERSON" }
@@ "W" :> { "m1_OF_PERSON", "m2_OF_PERSON" }

(* Transition 0 to State5 *)
State5 ==
bank_of_boat = "W"
/\ who_is_on_bank
= "E" :> {}
@@ "W"
:> { "c1_OF_PERSON", "c2_OF_PERSON", "m1_OF_PERSON", "m2_OF_PERSON" }

(* The following formula holds true in the last state and violates the invariant *)
InvariantViolation == who_is_on_bank["E"] = {}

================================================================================
(* Created by Apalache on Wed Dec 22 09:18:50 CET 2021 *)
(* https://github.com/informalsystems/apalache *)


The above counterexample looks very simple and natural, if the reader knows TLA+. In our experience, these examples look alien to engineers, who are not familiar with TLA+. It is unfortunate, since the counterexamples have a very simple shape:

1. They are simply sequences of states.

2. Every state is a mapping from variable names to expressions that do not refer to other variables.

3. The expressions are using a very small subset of TLA operators:

4. Integer and string literals.

5. Set constructor, sequence/tuple constructor, record constructor.

6. TLC operators over functions: :> and @@.

In hindsight, the above expressions are not very far from the JSON format. As many engineers know JSON, it seems natural to write these counterexamples in JSON.

## Options

1. Use the TLA+ format:

• Pros:

• easy to understand, if you know TLA+.
• it looks amazing in PDF.
• Cons:

• quite hard to understand, if you don't know TLA+.
• quite hard to parse automatically.
2. Use the JSON serialization as in ADR005:

• Pros:

• easy to parse automatically.
• Cons:

• too detailed and too verbose.
• requires the knowledge of Apalache IR and of TLA+.
3. Use the Informal Trace Format, which is proposed in this ADR:

• Pros:

• almost no introduction is required to read the traces.
• relatively compact.
• easy to parse automatically.
• uses the idioms that are understood by the engineers.
• not bound to TLA+.
• Cons:

• consistency of the format is in conflict with the ease of writing.

## Solution

In this ADR, we propose a very simple format that represents executions of state machines that follows the concepts of TLA+ and yet avoids complexity of TLA+. It is so simple that we call it "Informal Trace Format" (ITF). (Obviously, it is formal enough to be machine-readable). By convention, the files in this format should end with the extension .itf.json.

### The ITF Format

Trace object. A trace in ITF is a JSON object:

{
"#meta": <optional object>,
"params": <optional array of strings>,
"vars":  <array of strings>,
"states": <array of states>,
"loop": <optional int>
}


The field #meta is an arbitrary JSON object, whose purpose is to provide the reader with additional comments about the trace. For example, it may look like:

  "#meta": {
"description": "Generated by Apalache",
"source": "MissionariesAndCannibalsTyped.tla"
}


The optional field params is an array of names that must be set in the initial state (if there are any parameters). The parameters play the same role as CONSTANTS in TLA+. For example, the field may look like:

  "params": [ "Missionaries", "Cannibals" ]


The field vars is an array of names that must be set in every state. For example, the field may look like:

  "vars": [ "bank_of_boat", "who_is_on_bank" ]


The field states is an array of state objects (see below). For example, the field may look like:

  "states": [ <state0>, <state1>, <state2> ]


The optional field loop specifies the index of the state (in the array of states) that starts the loop. The loop ends in the last state. For example, the field may look like:

  "loop": 1


State object. A state is a JSON object:

  {
"#meta": <optional object>,
"<var1>": <expr>,
...
"<varN>": <expr>
}


As in the trace object, the field #meta may be an arbitrary object. Different tools may use this object to write their metadata into this object.

The names <var1>, ..., <varN> are the names of the variables that are specified in the field vars. Each state must define a value for every specified variable. The syntax of <expr> is specified below.

Expressions. As usual, expressions are inductively defined. An expression <expr> is one of the following:

1. A JSON Boolean: either false or true.

2. A JSON string literal, e.g., "hello". TLA+ strings are written as strings in this format.

3. A JSON integer, e.g., 123. According to RFC7159, JSON integers must be in the range: [-(2**53)+1, (2**53)-1]. Integers in this range may be written as JSON integers.

4. A big integer of the following form: { "#bigint": "[-][0-9]+" }. We are using this format, as many JSON parsers impose limits on integer values, see RFC7159. Big and small integers may be written in this format.

5. A list of the form [ <expr>, ..., <expr> ]. A list is just a JSON array. TLA+ sequences are written as lists in this format.

6. A record of the form { "field1": <expr>, ..., "fieldN": <expr> }. A record is just a JSON object. Field names should not start with # and hence should not pose any collision with other constructs. TLA+ records are written as records in this format.

7. A tuple of the form { "#tup": [ <expr>, ..., <expr> ] }. There is no strict rule about when to use sequences or tuples. Apalache differentiates between tuples and sequences, and it may produce both forms of expressions.

8. A set of the form { "#set": [ <expr>, ..., <expr> ] }. A set is different from a list in that it does not assume any ordering of its elements. However, it is only a syntax form in our format. Apalache distinguishes between sets and lists and thus it will output sets in the set form. Other tools may interpret sets as lists.

9. A map of the form { "#map": [ [ <expr>, <expr> ], ..., [ <expr>, <expr> ] ] }. That is, a map holds a JSON array of two-element arrays. Each two-element array p is interpreted as follows: p[0] is the map key and p[1] is the map value. Importantly, a key may be an arbitrary expression. It does not have to be a string or an integer. TLA+ functions are written as maps in this format.

10. An expression that cannot be serialized: { "#unserializable": "<string representation>" }. For instance, the set of all integers is represented with { "#unserializable": "Int" }. This should be a very rare expression, which should not occur in normal traces. Usually, it indicates some form of an error.

### ITF as input to Apalache

To be able to read ITF traces, Apalache demands the following:

• The #meta field must be present
• The #meta field must contain a field varTypes, which is an object, the keys of which are the variables declared in vars, and the values are string representations of their types (as defined in ADR002).

For example:

"#meta": {
"varTypes": {
"bank_of_boat": "Str",
"who_is_on_bank": "Str -> Set(PERSON)"
}
}


### Example

The counterexample to NoSolution may be written in the ITF format as follows:

{
"#meta": {
"source": "MC_MissionariesAndCannibalsTyped.tla",
"varTypes": {
"bank_of_boat": "Str",
"who_is_on_bank": "Str -> Set(PERSON)"
}
},
"vars": [ "bank_of_boat", "who_is_on_bank" ],
"states": [
{
"#meta": { "index": 0 },
"bank_of_boat": "E",
"who_is_on_bank": {
"#map": [
[ "E", { "#set": [ "c1_OF_PERSON", "c2_OF_PERSON",
"m1_OF_PERSON", "m2_OF_PERSON" ] } ],
[ "W", { "#set": [] } ]
]
}
},
{
"#meta": { "index": 1 },
"bank_of_boat": "W",
"who_is_on_bank": {
"#map": [
[ "E", { "#set": [ "c1_OF_PERSON", "m1_OF_PERSON" ] } ],
[ "W", { "#set": [ "c2_OF_PERSON", "m2_OF_PERSON" ] } ]
]
}
},
{
"#meta": { "index": 2 },
"bank_of_boat": "E",
"who_is_on_bank": {
"#map": [
[ "E", { "#set": [ "c1_OF_PERSON",
"m1_OF_PERSON", "m2_OF_PERSON" ] } ],
[ "W", { "#set": [ "c2_OF_PERSON" ] } ]
]
}
},
{
"#meta": { "index": 3 },
"bank_of_boat": "W",
"who_is_on_bank": {
"#map": [
[ "E", { "#set": [ "c1_OF_PERSON" ] } ],
[ "W", { "#set": [ "c2_OF_PERSON", "m1_OF_PERSON", "m2_OF_PERSON" ] } ]
]
}
},
{
"#meta": { "index": 4 },
"bank_of_boat": "E",
"who_is_on_bank": {
"#map": [
[ "E", { "#set": [ "c1_OF_PERSON", "c2_OF_PERSON" ] } ],
[ "W", { "#set": [ "m1_OF_PERSON", "m2_OF_PERSON" ] } ]
]
}
},
{
"#meta": { "index": 5 },
"bank_of_boat": "W",
"who_is_on_bank": {
"#map": [
[ "E", { "#set": [ ] } ],
[ "W", { "#set": [ "c1_OF_PERSON", "c2_OF_PERSON",
"m1_OF_PERSON", "m2_OF_PERSON" ] } ]
]
}
}
]
}


Compare the above trace format with the TLA+ counterexample. The TLA+ example looks more compact. The ITF example is heavier on the brackets and braces, but it is also designed with machine-readability and tool automation in mind, whereas TLA+ counterexamples are not. However, the example in the ITF format is also self-explanatory and does not require any understanding of TLA+.

Note that we did not output the operator InvariantViolation of the TLA+ example. This operator is simply not a part of the trace. It could be added in the #meta object by Apalache.

### Discussion

Shon Feder @shonfeder flagged important concerns about irregularity of the proposed format in the PR comments. In a regular approach we would treat all expressions uniformly. For example:

// proposed form:
"hello"
// regular form:
{ "#type": "string", "#value": "hello" }

// proposed form:
{ "#set": [ 1, 2, 3] }
// regular form:
{
"#type": "set",
"#value": [
{ "#type": "int", "#value": "1" },
{ "#type": "int", "#value": "2" },
{ "#type": "int", "#value": "3" }
]
}


The more regular approach is less concise. In the future, we might want to add a flag that lets the user choose between the regular output and the output proposed in this ADR, which is more ad hoc.

Another suggestion is to use JSON schema. For the moment, it seems to be a heavy-weight solution with no obvious value. However, we should keep it in mind and use schemas, when the need arises.

## Consequences

Reserved for the future.