SEOct 11, 2021

Parsing Data Formats of the Inputs and Outputs of Geographic Models with Code Analysis

arXiv:2111.07752v1
Originality Incremental advance
AI Analysis

This work addresses a specific bottleneck in constructing and using model web services for geographic models, offering an incremental improvement over existing description-focused methods.

The paper tackles the problem of automatically parsing data formats for inputs and outputs of geographic models by analyzing source code relationships, which significantly improves efficiency in writing data format specifications and promotes model sharing as web services.

Model web services provide an approach for implementing and facilitating the sharing of geographic models. The description and acquisition of inputs and outputs (IO) of geographic models is a key issue in constructing and using model web services. These approaches for describing and acquiring the data formats of the IO of geographic models can be classified into two categories, i.e., intermediate-data-format-based and native-data-format-based. Nonetheless, these two categories mainly consider the description of the IO of geographical models but relatively pay little attention to the acquisition. To address this issue, this paper proposes an approach for automatically parsing data formats of the IO utilizing the relationship between the IO and source codes. This proposed approach can utilize such a strict and coupling relationship and the expression form of the data formats in the source codes to retrospectively derive the IO data format and automatically generate data format documentation. The feasibility of the proposed approach has been verified via a geographical model coded in the FORTRAN language, which shows that it significantly improves the efficiency of writing data format specifications and promotes sharing geographic models as model web services.

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