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Multiple issues in array data setter

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难度
4/5
预计耗时
3-5 天
新手友好度
35/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
停滞
技术栈
python
领域
api

调研方向

从链接的 poc_idl_array.py 复现开始，将数组元素赋值与 issue 中描述的内置类型行为进行比较。跟踪为固定数组生成的 Python 消息类，然后为数值、bool、byte 和 string 数组补充范围和类型拒绝的覆盖；当无效赋值都能一致地失败，同时合法值仍能成功时，即表示完成。

由索引模型根据 Issue 内容生成。

描述

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, ...).

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  • 阅读贡献指南

从这里开始

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  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库，在一个分支上完成修改。
  4. 提交 Pull Request，并在描述里引用这个 Issue 编号。

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