IEH Engine Qualitative Audit: A Comprehensive Guide

In this comprehensive guide, we delve into the process of conducting a qualitative audit of an Intelligent Error Handling (IEH) engine. This audit aims to systematically investigate the parser's entire surface area for potential failure modes, assess the quality of the corresponding instructional hints, and ultimately produce a formal report. The primary goal is to identify gaps and areas for improvement, ensuring the IEH engine effectively serves as an "instructional teacher" for all existing features. This guide outlines the steps involved, from creating an error inventory to generating a detailed audit report.

Goal of the Qualitative Audit

The core objective of this qualitative audit is to thoroughly examine the IEH engine's capabilities in handling errors and providing helpful guidance to users. The goal is to ensure that the engine not only identifies errors but also offers clear, actionable advice on how to resolve them. This is crucial for enhancing user experience and promoting a deeper understanding of the system's functionalities. By systematically investigating potential failure modes and evaluating the quality of instructional hints, we can pinpoint areas that require improvement and ensure the IEH engine meets its strategic objectives.

To achieve this, the audit will focus on the following key aspects:

• Comprehensive Error Identification: Identifying all possible syntax errors and failure modes within the parser.
• Quality of Instructional Hints: Evaluating the clarity, accuracy, and helpfulness of the error messages and hints provided to users.
• Gap Analysis: Identifying areas where hints are missing or inadequate, and determining the necessary improvements.
• Adherence to Standards: Ensuring that the error handling and hints align with the established “Visionary State” standards for the project.

By addressing these aspects, the audit will lay the foundation for a more robust and user-friendly IEH engine, capable of effectively guiding users through potential issues and enhancing their overall experience. This proactive approach to error handling is essential for maintaining the integrity and usability of the system.

File/Directory Targets for the Audit

To conduct a thorough audit, we need to focus on specific files and directories within the project. These file/directory targets provide essential information about the engine's structure, error handling mechanisms, and existing hints. The key targets include:

• docs/_design/IEH_Audit_Report.md (New File): This file will serve as the central repository for the audit findings. It will contain a detailed report of the investigation, including identified errors, evaluations of existing hints, and recommendations for improvements. The report will be structured in a clear, organized manner to facilitate easy review and action.
• spec/grammar/dsl.ebnf (Reference for all possible syntax constructs): This file is crucial for understanding the grammar and syntax rules of the system. By reviewing this file, we can identify all possible syntax errors that the IEH engine should be able to handle. It provides a comprehensive overview of the language constructs and their potential failure points.
• bindings/python/src/STRling/core/parser.py (Reference for error raise sites): This file contains the Python implementation of the parser and is the primary location where errors are raised. Examining this file will help us understand how errors are detected and handled within the system. It allows us to identify the specific points in the code where errors are triggered and the corresponding error messages.
• tooling/error_corpus.json (Reference for existing hints): This file serves as a repository of existing error hints. It provides a baseline for evaluating the current state of error handling in the system. By reviewing this file, we can assess the quality and coverage of the existing hints and identify areas where new or improved hints are needed.

By targeting these specific files and directories, the audit can provide a comprehensive and focused assessment of the IEH engine's error handling capabilities. This targeted approach ensures that all critical aspects of the system are thoroughly examined, leading to actionable insights and recommendations.

Sub-Tasks & Implementation Plan

To effectively conduct the qualitative audit of the IEH engine, we will break the process down into three distinct phases. Each phase is designed to build upon the previous one, ensuring a systematic and thorough investigation. Here’s a detailed sub-tasks & implementation plan:

1. Phase 1: Create Error Inventory

The initial phase involves building a comprehensive list of all possible syntax errors that the IEH engine should be able to handle. This inventory will serve as the foundation for the audit and ensure that no potential failure mode is overlooked. The key steps in this phase include:

• Review spec/grammar/dsl.ebnf and parser.py: These files will be thoroughly reviewed to identify all possible syntax errors. The dsl.ebnf file provides the grammar rules, while parser.py shows how these rules are implemented and where errors are raised. This dual review ensures a complete understanding of the system's error potential.
• Comprehensive List Creation: The inventory must go far beyond the existing five cases in error_corpus.json. It should encompass a wide range of potential errors, covering all major grammar categories. This extensive coverage is crucial for a thorough audit.
• Categorization of Errors: Errors will be categorized for better organization and analysis. The categories include:
  • Groups: Unclosed (, unclosed (?<name>, invalid group name (?<1a>).
  • Quantifiers: Invalid ranges a{5,2}, incomplete a{, invalid non-digit a{foo}.
  • Character Classes: Unclosed [, empty [], invalid range [z-a].
  • Anchors: Misplaced anchors a^b.
  • Escapes: Invalid hex \xGG, invalid unicode \uGGGG, invalid property \p{Foo}.
  • Flags: Misspelled flag %flags foo, flag in the wrong position.

2. Phase 2: Audit & Qualitative Review

In the second phase, we will evaluate the quality of the existing error hints and their adherence to the