Shaping Inputs with Constraints

Shaping Inputs with Constraints#

The Limits of Grammars#

So far, all the operations we have performed on our data were syntax-oriented - that is, we could shape the format and structure of our values, but not their semantics - that is, their actual meaning. Consider our Person/Age dataset from the previous section. What would we do if we want the ā€œageā€ in a specific range? Or we want it to be odd? Or we want the age to be distributed in a certain way?

All of this refers to context-free grammars, which are the ones Fandango uses.

Some of these can be obtained by altering the grammar - limiting the age to two digits at most, for instance, will keep the value below 100 - but others cannot. Properties that cannot be expressed in a grammar are called semantic properties - in contrast to syntactical properties, which is precisely what grammars are good for.

Specifying Constraints#

Fandango solves this problem through a pretty unique feature: It allows users to specify constraints which inputs have to satisfy. These thus narrow down the set of possible inputs.

Constraints are predicates over grammar symbols. Essentially, you write a Boolean expression, using grammar symbols (in <...>) to refer to individual elements of the input.

As an example, consider this Fandango constraint:

int(<age>) < 50

This constraint takes the <age> element from the input and converts it into an integer (all symbols are strings in the first place). Inputs are produced only if the resulting value is less than 50.

We can add such constraints to any .fan file, say the persons.fan file from the previous section. Constraints are preceded by a keyword where. So the line we add reads

where int(<age>) < 50

and the full persons.fan file reads

<start> ::= <person_name> "," <age>
<person_name> ::= <first_name> " " <last_name>
<first_name> ::= <name>
<last_name> ::= <name>
<name> ::= <ascii_uppercase_letter><ascii_lowercase_letter>+
<age> ::= <digit>+
where int(<age>) < 50

If we do this and run Fandango, we obtain a new set of inputs:

$ fandango fuzz -f persons.fan -n 10

Bcx Tw,48
Onk Dwqy,6
Ousfk Zgk,31
Szkeb Hq,0
Vfwkq Rm,5
Qv Nrm,30
Pzhn La,33
Bhj Admpn,6
Nlq Dpyyop,5
Xyyp Bgbhqo,1

We see that all persons produced now indeed have an age of less than 50. Even if an age begins with 0, it still represents a number below 50.

The language Fandango uses to express constraints is Python, so you can make use of arbitrary Python expressions. For instance, we can use Python Boolean operators (and, or, not) to request values in a range of 25-45:

Interestingly, having symbols in <...> does not conflict with the rest of Python syntax. Be sure, though, to leave spaces around < and > operators to avoid confusion.

25 <= int(<age>) and int(<age>) <= 45

and we obtain these inputs:

Qmytsk Xhmt,027
Hgzfg Usux,33
Fem Gzecj,39
Dlqvw Soqj,35
Rxmhsy Kempo,40
Kl Vjzzq,31
Tluhh Ee,36
Oa Ete,39
Bie Lwzvof,37
Hyhy Hs,42

Start with persons.fan and add a constraint such that we generate people whose age is a multiple of 7, as in

Nuo Qx,7
Mdpqh Zvuu,6405
Tzd Ktb,749
Fsu Fm,7
Baumi Xvxcj,728
Cldwf Enk,9688
Tgu Imqerc,56
Pjaho Nx,63
Ivshy Vbhik,147
Eqese Ned,7

(Hint: The modulo operator in Python is %).

Solution

This is not too hard. Simply add

where int(<age>) % 7 == 0

as a constraint.

Constraints and DerivationTree types#

Whenever Fandango evaluates a constraint, such as

int(<age>) > 20

the type of <age> is actually not a string, but a DerivationTree object - a tree representing the structure of the output.. For now, you can use DerivationTree objects almost as if they were strings:

  • You can convert them to other basic data types with (int(<age>), float(<age>), str(<age>))

  • You can invoke string methods on them (`.startswith(ā€˜0ā€™))

  • You can compare them against each other (<age_1> == <age_2>) as well as against other strings (<age> != "19")

  • You can print them, using implicit string conversions (print(<age>), which invokes <age>.__str__())

One thing you cannot do, though, is passing them directly as arguments to functions that do not expect a DerivationTree type. This applies to the vast majority of Python functions.

Warning

If you want to pass a symbol as a function argument, convert it to the proper type (int(<age>), float(<age>), str(<age>)) first. Otherwise, you will likely raise an internal error in that very function.

Warning

On symbols, the [...] operator operates differently from strings - it returns a subtree (a substring) of the produced output: <name>[0] returns the <first_name> element, not the first character. If you want to access a character (or a range of characters) of a symbol, convert it into a string first, as in str(<name>)[0].

We will learn more about derivation trees, DerivationTree types, and their operators in Accessing Input Elements.

Constraints on the Command Line#

If you want to experiment with constraints, keeping on editing .fan files is a bit cumbersome. As an alternative, Fandango also allows to specify constraints on the command line. This is done with the -c (constraint) option, followed by the constraint expression (typically in quotes).

Starting with the original persons.fan, we can thus apply age constraints as follows:

$ fandango fuzz -f persons.fan -n 10 -c '25 <= int(<age>) and int(<age>) <= 45'

Constraints can be given multiple times, so the above can also be obtained as

$ fandango fuzz -f persons.fan -n 10 -c '25 <= int(<age>)' -c 'int(<age>) <= 45'

Note

On the command line, always put constraints in single quotes ('...'), as the angle brackets might otherwise be interpreted as I/O redirection.

When do constraints belong in a .fan file, and when on the command line? As a rule of thumb:

  • If a constraint is necessary for obtaining valid input files (i.e. if the inputs would not be accepted otherwise), it belongs into the .fan file.

  • If a constraint is optional, for instance for shaping inputs towards a particular goal, then it can also go on the command line.

How Fandango Solves Constraints#

How does Fandango obtain these inputs? In a nutshell, Fandango is an evolutionary test generator:

  1. It first uses the grammar to generate a population of inputs.

  2. It then checks which individual inputs are closest in fulfilling the given constraints. For instance, for a constraint int(<X>) == 100, an input where <X> has a value of 90 is closer to fulfillment than one with value of, say 20.

Selecting the best inputs is also known as ā€œsurvival of the fittestā€

  1. The best inputs are selected, the others are discarded.

  2. Fandango then generates new offspring by mutating the remaining inputs, recomputing parts according to grammar rules. It can also exchange parts with those from other inputs; this is called crossover.

  3. Fandango then repeats Steps 2-4 until all inputs satisfy the constraints.

All of this happens within Fandango, which runs through these steps with high speed. The -v option (verbose) produces some info on how the algorithm progresses:

$ fandango -v fuzz -f persons.fan -n 10 -c 'int(<age>) % 7 == 0'

fandango:INFO: ---------- Parsing FANDANGO content ----------
fandango:INFO: <stdlib>: loading cached spec from /home/runner/.cache/fandango/c6d5b8d821f36cb11de70ec76c7a9f7fbe76431d76b22c2c0ad1c1d519a9e1a0.pickle
fandango:INFO: persons.fan: loading cached spec from /home/runner/.cache/fandango/b414727fa16fea7721cf90f0cb6eac30d01a9c9c39c671088a7c3e894a1c0083.pickle
fandango:INFO: int(<age>) % 7 == 0: loading cached spec from /home/runner/.cache/fandango/a753104490d484ad02278019279173c89eebe7fe1eab0add655483b140a71aef.pickle
fandango:INFO: File mode: text
fandango:INFO: ---------- Initializing FANDANGO algorithm ---------- 
fandango:INFO: Generating initial population (size: 100)...

fandango:INFO: Initial population generated in 0.07 seconds
fandango:INFO: ---------- Starting evolution ----------
fandango:INFO: ---------- Evolution finished ----------
fandango:INFO: Perfect solutions found: (10)
fandango:INFO: Fitness of final population: 1.00
fandango:INFO: Time taken: 0.00 seconds
Wdx Kpe,77
Xrwrtm Giwldt,98
Wn Mpy,399
Mncdn Zlpxr,084
Pxqrb Lijryc,49
Ckvv Yd,6090
Kxje Rdmnv,4683
Nt Miot,22484
Qz Ntzxt,7
Jf Srjszu,49588
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0001.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0002.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0003.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0004.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0005.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0006.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0007.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0008.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0009.txt'
fandango:INFO: Parsing '/tmp/tmpubayx_wn/fandango-0010.txt'

Note

The -v option comes right after fandango (and not after fandango fuzz), as -v affects all commands (and not just fuzz).

When Constraints Cannot be Solved#

Normally, Fandango continues evolving the population until all inputs satisfy the constraints. Some constraints, however, may be difficult or even impossible to solve. After a maximum number of generations (which can be set using -N), Fandango stops and produces the inputs it has generated so far. We can see this if we specify False as a constraint:

$ fandango -v fuzz -f persons.fan -n 10 -c 'False' -N 50

fandango:INFO: ---------- Parsing FANDANGO content ----------
fandango:INFO: <stdlib>: loading cached spec from /home/runner/.cache/fandango/c6d5b8d821f36cb11de70ec76c7a9f7fbe76431d76b22c2c0ad1c1d519a9e1a0.pickle
fandango:INFO: persons.fan: loading cached spec from /home/runner/.cache/fandango/b414727fa16fea7721cf90f0cb6eac30d01a9c9c39c671088a7c3e894a1c0083.pickle

fandango:INFO: False: saving spec to cache /home/runner/.cache/fandango/935a24ad0df474cb7a33185d32dd87047a14ee147ef83fa4320c0e0083ba48d4.pickle
fandango:INFO: File mode: text
fandango:INFO: ---------- Initializing FANDANGO algorithm ---------- 
fandango:INFO: Generating initial population (size: 100)...

fandango:INFO: Initial population generated in 0.07 seconds
fandango:INFO: ---------- Starting evolution ----------
fandango:INFO: Generation 1 - Fitness: 0.02 - #solutions found: 0

fandango:INFO: Generation 1: Increasing mutation rate from 0.20 to 0.22

fandango:INFO: Generation 1: Increasing crossover rate from 0.80 to 0.84
fandango:INFO: Generation 1: Increasing MAX_REPETITION from 5 to 7
fandango:INFO: Generation 1: Increasing Fuzzing Budget from 50 to 75
fandango:INFO: Generation 1 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 2 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 2: Increasing mutation rate from 0.22 to 0.24
fandango:INFO: Generation 2: Increasing crossover rate from 0.84 to 0.88
fandango:INFO: Generation 2: Increasing MAX_REPETITION from 7 to 10
fandango:INFO: Generation 2: Increasing Fuzzing Budget from 75 to 112
fandango:INFO: Generation 2 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 3 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 3: Increasing mutation rate from 0.24 to 0.27
fandango:INFO: Generation 3: Increasing crossover rate from 0.88 to 0.93
fandango:INFO: Generation 3: Increasing MAX_REPETITION from 10 to 15
fandango:INFO: Generation 3: Increasing Fuzzing Budget from 112 to 168
fandango:INFO: Generation 3 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 4 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 4: Increasing mutation rate from 0.27 to 0.29
fandango:INFO: Generation 4: Increasing crossover rate from 0.93 to 0.97
fandango:INFO: Generation 4: Increasing MAX_REPETITION from 15 to 22
fandango:INFO: Generation 4: Increasing Fuzzing Budget from 168 to 200
fandango:INFO: Generation 4 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 5 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 5: Increasing mutation rate from 0.29 to 0.32
fandango:INFO: Generation 5: Increasing crossover rate from 0.97 to 1.00
fandango:INFO: Generation 5: Increasing MAX_REPETITION from 22 to 33

fandango:INFO: Generation 5 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.01, Population size: 100
fandango:INFO: Generation 6 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 6: Increasing mutation rate from 0.32 to 0.35
fandango:INFO: Generation 6: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 6: Increasing MAX_REPETITION from 33 to 49
fandango:INFO: Generation 6 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.01, Population size: 100
fandango:INFO: Generation 7 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 7: Increasing mutation rate from 0.35 to 0.39
fandango:INFO: Generation 7: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 7: Increasing MAX_REPETITION from 49 to 73
fandango:INFO: Generation 7 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.01, Population size: 100
fandango:INFO: Generation 8 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 8: Increasing mutation rate from 0.39 to 0.43
fandango:INFO: Generation 8: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 8: Increasing MAX_REPETITION from 73 to 109
fandango:INFO: Generation 8 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 9 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 9: Increasing mutation rate from 0.43 to 0.47
fandango:INFO: Generation 9: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 9: Increasing MAX_REPETITION from 109 to 163
fandango:INFO: Generation 9 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100

fandango:INFO: Generation 10 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 10: Increasing mutation rate from 0.47 to 0.52
fandango:INFO: Generation 10: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 10: Increasing MAX_REPETITION from 163 to 244
fandango:INFO: Generation 10 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 11 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 11: Increasing mutation rate from 0.52 to 0.57
fandango:INFO: Generation 11: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 11: Increasing MAX_REPETITION from 244 to 366
fandango:INFO: Generation 11 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 12 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 12: Increasing mutation rate from 0.57 to 0.63
fandango:INFO: Generation 12: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 12: Increasing MAX_REPETITION from 366 to 549
fandango:INFO: Generation 12 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 13 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 13: Increasing mutation rate from 0.63 to 0.69
fandango:INFO: Generation 13: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 13: Increasing MAX_REPETITION from 549 to 823
fandango:INFO: Generation 13 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 14 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 14: Increasing mutation rate from 0.69 to 0.76
fandango:INFO: Generation 14: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 14: Increasing MAX_REPETITION from 823 to 1234
fandango:INFO: Generation 14 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 15 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 15: Increasing mutation rate from 0.76 to 0.84
fandango:INFO: Generation 15: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 15: Increasing MAX_REPETITION from 1234 to 1851
fandango:INFO: Generation 15 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 16 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 16: Increasing mutation rate from 0.84 to 0.92
fandango:INFO: Generation 16: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 16: Increasing MAX_REPETITION from 1851 to 2776
fandango:INFO: Generation 16 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 17 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 17: Increasing mutation rate from 0.92 to 1.00
fandango:INFO: Generation 17: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 17: Increasing MAX_REPETITION from 2776 to 4164
fandango:INFO: Generation 17 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 18 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 18: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 18: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 18: Increasing MAX_REPETITION from 4164 to 6246
fandango:INFO: Generation 18 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 19 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 19: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 19: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 19: Increasing MAX_REPETITION from 6246 to 9369
fandango:INFO: Generation 19 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 20 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 20: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 20: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 20: Increasing MAX_REPETITION from 9369 to 14053
fandango:INFO: Generation 20 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 21 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 21: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 21: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 21: Increasing MAX_REPETITION from 14053 to 21079
fandango:INFO: Generation 21 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 22 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 22: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 22: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 22: Increasing MAX_REPETITION from 21079 to 31618

fandango:INFO: Generation 22 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 23 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 23: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 23: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 23: Increasing MAX_REPETITION from 31618 to 47427
fandango:INFO: Generation 23 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 24 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 24: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 24: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 24: Increasing MAX_REPETITION from 47427 to 71140
fandango:INFO: Generation 24 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 25 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 25: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 25: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 25: Increasing MAX_REPETITION from 71140 to 106710
fandango:INFO: Generation 25 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 26 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 26: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 26: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 26: Increasing MAX_REPETITION from 106710 to 160065
fandango:INFO: Generation 26 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 27 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 27: Increasing mutation rate from 1.00 to 1.00

fandango:INFO: Generation 27: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 27: Increasing MAX_REPETITION from 160065 to 240097
fandango:INFO: Generation 27 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 28 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 28: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 28: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 28: Increasing MAX_REPETITION from 240097 to 360145
fandango:INFO: Generation 28 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 29 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 29: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 29: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 29: Increasing MAX_REPETITION from 360145 to 540217
fandango:INFO: Generation 29 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 30 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 30: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 30: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 30: Increasing MAX_REPETITION from 540217 to 810325
fandango:INFO: Generation 30 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 31 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 31: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 31: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 31: Increasing MAX_REPETITION from 810325 to 1215487

fandango:INFO: Generation 31 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 32 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 32: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 32: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 32: Increasing MAX_REPETITION from 1215487 to 1823230
fandango:INFO: Generation 32 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 33 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 33: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 33: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 33: Increasing MAX_REPETITION from 1823230 to 2734845
fandango:INFO: Generation 33 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 34 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 34: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 34: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 34: Increasing MAX_REPETITION from 2734845 to 4102267
fandango:INFO: Generation 34 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 35 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 35: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 35: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 35: Increasing MAX_REPETITION from 4102267 to 6153400
fandango:INFO: Generation 35 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 36 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 36: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 36: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 36: Increasing MAX_REPETITION from 6153400 to 9230100
fandango:INFO: Generation 36 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 37 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 37: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 37: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 37: Increasing MAX_REPETITION from 9230100 to 13845150
fandango:INFO: Generation 37 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 38 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 38: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 38: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 38: Increasing MAX_REPETITION from 13845150 to 20767725
fandango:INFO: Generation 38 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 39 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 39: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 39: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 39: Increasing MAX_REPETITION from 20767725 to 31151587
fandango:INFO: Generation 39 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 40 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 40: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 40: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 40: Increasing MAX_REPETITION from 31151587 to 46727380
fandango:INFO: Generation 40 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 41 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 41: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 41: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 41: Increasing MAX_REPETITION from 46727380 to 70091070
fandango:INFO: Generation 41 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 42 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 42: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 42: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 42: Increasing MAX_REPETITION from 70091070 to 105136605
fandango:INFO: Generation 42 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 43 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 43: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 43: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 43: Increasing MAX_REPETITION from 105136605 to 157704907
fandango:INFO: Generation 43 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 44 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 44: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 44: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 44: Increasing MAX_REPETITION from 157704907 to 236557360
fandango:INFO: Generation 44 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 45 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 45: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 45: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 45: Increasing MAX_REPETITION from 236557360 to 354836040
fandango:INFO: Generation 45 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 46 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 46: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 46: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 46: Increasing MAX_REPETITION from 354836040 to 532254060
fandango:INFO: Generation 46 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 47 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 47: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 47: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 47: Increasing MAX_REPETITION from 532254060 to 798381090
fandango:INFO: Generation 47 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 48 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 48: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 48: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 48: Increasing MAX_REPETITION from 798381090 to 1197571635
fandango:INFO: Generation 48 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 49 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 49: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 49: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 49: Increasing MAX_REPETITION from 1197571635 to 1796357452
fandango:INFO: Generation 49 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: Generation 50 - Fitness: 0.00 - #solutions found: 0

fandango:INFO: Generation 50: Increasing mutation rate from 1.00 to 1.00
fandango:INFO: Generation 50: Increasing crossover rate from 1.00 to 1.00
fandango:INFO: Generation 50: Increasing MAX_REPETITION from 1796357452 to 2694536178
fandango:INFO: Generation 50 stats -- Best fitness: 0.00, Avg fitness: 0.00, Avg diversity: 0.02, Population size: 100
fandango:INFO: ---------- Evolution finished ----------
fandango:INFO: Perfect solutions found: (0)
fandango:INFO: Fitness of final population: 0.00
fandango:INFO: Time taken: 4.81 seconds
fandango:ERROR: Population did not converge to a perfect population
fandango:ERROR: Only found 0 perfect solutions, instead of the required 10

As you see, Fandango produces a population of zero. Of course, if the constraint is False, then there can be no success.

Tip

Fandango has a --best-effort option that allows you to still output the final population.

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