Programming Models of Command Processing for Time-Series Data with Fault Tolerance to C++/CLI Graphics Codes
Gao-Wei Chang · 2021
This paper is to propose an object-oriented framework with C++/CLI programming models that process the input commands for time series with fault tolerance to the graphics in an integrated development environment, e.g., Microsoft Visual Studio. In this approach, the collection of those opcodes (e.g., string array) can be systematically augmented. Also, with the predefined template of multiple-division commands, the proposed methods can be immune to format error or incomplete operand divisions. The experimental results reveal the effectiveness of the fault tolerance to graphing time series.