CSC/ECE 517 Spring 2015 E1527 SWAR

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E1527. Refactor Autometareviews gem and migration to Web-Service

Introduction to Autometareview project

This project is developed as part of Expertiza <reference></reference> project.
The automated metareview tool identifies the quality of a review using natural language processing and machine learning techniques (completely automated). Feedback is provided to reviewers on the following metrics:

  1. Review relevance: This metric tells the reviewer how relevant the review is to the content of the author's submission. Numeric feedback in the scale of 0--1 is provided to indicate a review's relevance.
  2. Review Content Type: This metric identifies whether the review contains 'summative content' -- positive feedback, problem detection content' -- problems identified by reviewers in the author's work or 'advisory content' -- content indicating suggestions or advice provided by reviewers. A numeric feedback on the scale of 0--1 is provided for each content type to indicate whether the review contains that type of content.
  3. Review Coverage: This metric indicates the extent to which a review covers the main points of a submission. Numeric value in the range of 0--1 indicates the coverage of a review.
  4. Plagiarism: Indicates the presence of plagiarism in the review text.
  5. Tone: The metric indicates whether a review has a positive, negative or neutral tone.
  6. Quantity: Indicates the number of unique words used by the reviewer in the review.

    7. Problem Statement

    Currently, Autometareviews project is used as a gem in Expertiza project. Purpose of this project is to migrate this gem to a web service and expose its methods on web, which can be consumed by any application as web service. Older gem was dependent old libraries such as Stanford-core-nlp, rwordnet, etc. We will migrate them to new libraries without breaking the existing feature-set. We are also going to refactor the source code of this gem file to promote readability, reduced complexity, and code redundancies. We will fix any bug or bottleneck that we can find to improve the performance of this service. We will not add any new feature to the existing feature set provided by the gem. Before making any modification to the existing features, we will present them before Dr. Gehringer and his Expertiza team.

    Scope

    The scope of this project includes migration of existing gem application to a web-service, refactoring the existing classes and migrating to newer libraries, wherever possible. The classes that we propose to refactor are tone.rb, degree_of_relevance.rb, wordnet_based_similarity.rb, sentence_state.rb, cluster_generation.rb, plagiarism_check.rb, graph_generator.rb, predict_class.rb, and review_coverage.rb. No new feature will be developed as part of this project. Any major code change due to inclusion of newer libraries will be communicated to Expertiza project team. Existing code will be tested to ensure the functionality does not change.

    Standards

    All developed code will adhere to the ruby on rails coding guidelines.

    List of Tasks

    Below are detailed explanations to the tasks listed in the description documentation.


    1. Refactor Code

    Problem 1: Efficient Loop constructs. Description: Many loops over models are implemented using generic “for” loops. Solution: As specified by Ruby guideline, we plan to use efficient ruby loops, such as “each” and “find_each”. Problem 2: Very large methods Description: Several methods have huge amount of code, which makes them difficult to understand and debug. Solution: In most cases, large methods can be shortened through the use of smaller helper methods. Such methods could be reused across different components. Problem 3: Ambiguous method names Description: Many methods have ambiguity between the name used for them and the feature implemented by them. Solution: We will rename such methods to clearly state the feature implemented by them. Problem 4: Legacy Code Description: As the system has been modified for bug fixes and enhancements, unnecessary code has accumulated. Solution: Isolate and remove all dead code. Problem 5: Code beautification Description: Coding style used in gem is not based on Ruby on Rails style, which makes it difficult to read for any Ruby programmer. Solution: Beautify the code with a consistent standard of documentation, and style.

    2. Upgrade system to use latest dependent ruby gems

    The libraries used by gem are very old. We plan to migrate the dependent libraries to their latest versions. Libraries, we have identified are: 1) Stanford-core-nlp 2) rwordnet 3) rjb 4) bind-it We will also migrate the project to use Java 8.


    3. Migrate gem to Web service

    Web service will expose calculate_metareview_metric method over web, which will consume review, submission, an array of rubrics. It will return the autometareview result as JSON.

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