这道面试题如何入手？# JobHunting - 待字闺中
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Today: Mostly cloudy with a 20 percent chance of snow. Highs in the mid 30s.
Tonight: Cloudy with a 20 percent chance of snow. Lows in the lower to mid
20s.
Saturday: Warmer. Mostly cloudy with a 10 percent chance of snow. Highs in
the lower to mid 40s. Winds 10 to 15 mph.
Saturday Night: Mostly cloudy. Chance of rain in the morning, then chance of
snow overnight. Probability of rain and snow 40 percent. Lows 25 to 31.
Sunday: Partly cloudy. Highs 40 to 46.
Sunday Night: Partly cloudy. Lows 24 to 30.
These words are automatically generated from various gridded weather
information such as: Temperature, Wind, Probability of Precipitation, and
Precipitation Type (Rain, Snow, etc.). Note there are dependencies from one
time period to another (e.g. “Warmer”) plus dependencies between phrases
within a time period as appears in the Saturday Night forecast.
Design the algorithm allowing the auto-generation of these textual
descriptions from said gridded fields. How would you approach this software
design problem?
Since “one size does not fit all”, the software must be extensible and
easily customized. For example, “Warm” in Alaska may mean something
different than in Florida. Also, the algorithms to produce the digital data
may differ from location to location.
What software design concepts (or approach) would you use?
怎么入手？数据结构？怎么设计？
Tonight: Cloudy with a 20 percent chance of snow. Lows in the lower to mid
20s.
Saturday: Warmer. Mostly cloudy with a 10 percent chance of snow. Highs in
the lower to mid 40s. Winds 10 to 15 mph.
Saturday Night: Mostly cloudy. Chance of rain in the morning, then chance of
snow overnight. Probability of rain and snow 40 percent. Lows 25 to 31.
Sunday: Partly cloudy. Highs 40 to 46.
Sunday Night: Partly cloudy. Lows 24 to 30.
These words are automatically generated from various gridded weather
information such as: Temperature, Wind, Probability of Precipitation, and
Precipitation Type (Rain, Snow, etc.). Note there are dependencies from one
time period to another (e.g. “Warmer”) plus dependencies between phrases
within a time period as appears in the Saturday Night forecast.
Design the algorithm allowing the auto-generation of these textual
descriptions from said gridded fields. How would you approach this software
design problem?
Since “one size does not fit all”, the software must be extensible and
easily customized. For example, “Warm” in Alaska may mean something
different than in Florida. Also, the algorithms to produce the digital data
may differ from location to location.
What software design concepts (or approach) would you use?
怎么入手？数据结构？怎么设计？