File:Metrics models.jpg

Introduction

In this final project “Text Metric”, first, we will integrate a couple of external sources such as Github, Trello to fetch information. Second, we will introduce the idea of "Readability." To get the level of readability, we will import the content of write-ups written by students, split the sentences to get the number of sentences, the number of words, etc., and then we calculate the indices by using these numbers and formulas.

Our primary task for the final project is to design tables which allow the Expertiza app to store data fetched from external sources, such as GitHub, Trello, and write-ups. For the next step, we would like to utilize this raw data for virtualized charts and grading metrics.

Current Design

Currently, there are three models created to store the raw data from metrics source. (Metrics, Metric_data_points, Metric_data_point_types)

Metrics

Models:

Schema:

Metric_data_points

Model:

Schema:

Metric_data_point_types

Model:

Schema:

The current framework only defined the schema, but the models are still empty, and the methods of the data parser have not been implemented yet.

This schema is a clever design because it follows the "Open to Extension and Closed to Modification" principle. When new data is added to the database, developers don't have to change the metric_data_point_types and metric_data_points tables. The developers only need to add two methods to translate the data type to and from strings. By browsing the code, the most basic types already have those methods to meet our requirements. But it is not flawless, and we will talk about the problems in the next section.

Besides, we only have GitHub to be our data source currently. As a result, we also need to find other data sources to be one of the grading metrics.

Analysis of the Problem

1.In model metric_data_points, it is defined that each metric_data_point belongs to a metric and a metric_data_point_type. However, in both model metric_data_point and metric, they haven’t defined has_many metric_data_points. So we can’t query all the metric_data_points of a metric or a metric_data_point_type.

2.In schema metric_data_points, value has been defined as a string to accommodate different data type. But this requires the program to translate data into strings when storing the data and translating the string back to data when accessing it. To make it worse, using strings to store data types, such as float type or Time class, would either lose the precision or incur more abundant storage space.

3.More external sources are needed.

Proposed Design