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Multiple issues in array data setter

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  • ¿Algo no está bien?
#153 1 comentario 0 reacciones 0 asignados Ver en GitHub

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
35/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Estancado
Stack tecnológico
python
Área
api

Línea de trabajo

Comienza con la reproducción vinculada poc_idl_array.py y compara la asignación de elementos de arrays con el comportamiento de los tipos integrados descrito en el issue. Rastrea las clases de mensajes de Python generadas para arrays de tamaño fijo y añade cobertura para el rechazo por rango y por tipo en arrays numéricos, bool, byte y string; se considera terminado cuando las asignaciones no válidas fallan de forma consistente mientras los valores legítimos siguen funcionando.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

help wanted

Bug report

Required Info:

  • Operating System:
    • Ubuntu 20.04
  • Installation type:
    • Binary installation via apt
  • Version or commit hash:
    • foxy
  • DDS implementation:
    • Fast-RTPS
  • Client library (if applicable):
    • N/A
Steps to reproduce issue
  1. Clone and build messages
$ mkdir -p ~/idltest_ws/src
$ cd ~/idltest_ws/src
$ git clone [email protected]:squizz617/idltest_msgs.git
$ cd ~/idltest_ws
$ colcon build --symlink-install
  1. Source workspaces (replace zsh with bash if using Bash)
$ source /opt/ros/foxy/setup.zsh
$ source ~/idltest_ws/install/setup.zsh
  1. Download and run PoC
$ wget https://gist.githubusercontent.com/squizz617/13631a18d25a1b7836414cce0c579227/raw/3e5113c78f2b1b7fe3296a2b29298afad6d8349e/poc_idl_array.py
$ chmod a+x poc_idl_array.py
$ ./poc_idl_array.py
Expected behavior

The PoC is self-explanatory. On the fixed arrays of built-in types, it tests the following three properties: (1) setting legitimate values should succeed, (2) setting out-of-valid-range values should fail, and (3) setting values of mismatching types should fail.

Actual behavior

The issues can be broadly categorized into three types.

  1. Missing range checks for numeric type (integer and float) arrays

uint8 array allows out of range integers to be assigned:

from idltest_msgs.msg import UInt8FixedArray
ui8fa = UInt8FixedArray()
ui8fa.data[0] = -1 # should fail but doesn't
print(ui8fa.data[0]) # value becomes 255
ui8fa.data[1] = 256 # should fail but doesn't
print(ui8fa.data[1]) # value becomes 0

int8 array also allows out of range integers to be assigned:

from idltest_msgs.msg import Int8FixedArray
i8fa = Int8FixedArray()
ui8fa.data[0] = -129 # should fail but doesn't
print(ui8fa.data[0]) # value becomes 127
ui8fa.data[1] = 128 # should fail but doesn't
print(ui8fa.data[1]) # value becomes -128

float32 array allows double to be assigned:

from idltest_msgs.msg import Float32FixedArray
f32fa = Float32FixedArray()
f32fa.data[0] = 1.0e+365 # should fail but doesn't
print(f32fa.data[0]) # value becomes inf
  1. Auto casting of data of wrong types

Integer arrays accept floats and casts them to int, dropping precision:

i8fa = Int8FixedArray()
i8fa.data[2] = 3.141592 # should fail but doesn't
print(i8fa.data[2]) # value becomes 3
i8fa.data[3] = 314.1592 # should fail but doesn't
print(i8fa.data[3]) # value becomes 58

For the types that cannot be casted to int, the assignment fails but the exception is raised not by the IDL:

i8fa.data[4] = "string" # fails (int() casting failure, not idl type check failure)
i8fa.data[5] = \x00 # fails (int() casting failure, not idl type check failure)
  1. Missing type checks for bool, byte, and string arrays

Any data of any type can be assigned to bool, byte or string arrays:

boolfa = BoolFixedArray()
bytefa = ByteFixedArray()
sfa = StringFixedArray()

# nothing fails
boolfa.data[0] = 32
boolfa.data[1] = 3.141592
boolfa.data[2] = 1.0e+365
boolfa.data[3] = 3.141592
boolfa.data[4] = "string"
boolfa.data[5] = [1, 2, 3]
boolfa.data[6] = {1: 2}
print(boolfa) # the illegitimate values are assigned as is

bytefa.data[0] = 32
bytefa.data[1] = 3.141592
bytefa.data[2] = 1.0e+365
bytefa.data[3] = 3.141592
bytefa.data[4] = "string"
bytefa.data[5] = [1, 2, 3]
bytefa.data[6] = {1: 2}
print(bytefa) # the illegitimate values are assigned as is

sfa.data[0] = 32
sfa.data[1] = 3.141592
sfa.data[2] = 1.0e+365
sfa.data[3] = 3.141592
sfa.data[4] = [1, 2, 3]
sfa.data[5] = {1: 2}
print(sfa) # the illegitimate values are assigned as is

In a nutshell, array elements are not properly checked at the time of assignment, unlike what's done for the built-in types (e.g., we cannot assign 256 or 3.14 to a uint8 variable, we cannot assign 3.14 to a string variable, ...).

Lenguaje dominante
EmberScript
Estrellas
26
Forks
68
Merge medio
1 d 9 h
PR fusionados (30 d)
3

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