遇到EXCEPTION DECODER大家是怎么做的呢?
程序总是在某种特定的情况下报错,提示用EXCEPTION DECODE分析,但是又没这样的工具data:image/png;base64,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用了arduino里面的MYSQL库文件,运行到一定时间,就会出现超时故障,头痛.这是两个问题,请教各位同学应该怎么处理
页:
[1]