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Product Requirements Document (PRD): Code Masking and Pattern Analysis Pipeline (10th February 2025) with INCOSE PRD template via https://gist.github.com/wtpayne/93926afe7d702278d56f9a3835000907
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PRD.md

Product Requirements Document (PRD)
Title: Code Masking and Pattern Analysis Pipeline

1. Purpose and Scope

This PRD defines the minimal set of requirements for a code-masking and pattern-analysis pipeline that parses multiple code Repositories, scrambles domain semantics while preserving structural patterns, and generates Polars_DataFrame outputs for subsequent analysis. These requirements conform to the INCOSE guidelines for clarity, singularity, consistency, measurability, and correctness.

A single Senior_Developer shall execute these requirements in less than 60 minutes, guaranteeing delivery of Code_Soup and Polars_DataFrame artifacts alongside a cluster-based contrastive analysis.

2. Definitions (Glossary)

  • Senior_Developer: The single developer who executes each requirement in this PRD.
  • System: The code or tooling that implements the pipeline and executes the transformations, clustering, and analysis.
  • Repository: The codebase retrieved from a version-control platform.
  • Dependency: Each external library or module referenced by the code.
  • Config_File: Each configuration file (for example, pyproject.toml, Dockerfile, package.json) present in the Repository.
  • Polars_DataFrame: The tabular structure that stores Repository-level or snippet-level features for analysis.
  • AST: The Abstract_Syntax_Tree representation of code, used to parse and transform structural elements.
  • Scrambled_Code: The anonymized code snippets that preserve structural style but omit domain-specific semantics.
  • Code_Soup: The aggregated set of Scrambled_Code snippets labeled with cluster or metadata.
  • LLM: The Large_Language_Model that extracts stylistic patterns from Code_Soup or generates contrastive analysis.
  • Local_Environment: The Senior_Developer’s controlled environment or machine used to run the pipeline.

3. Requirements

  1. [R1] The Senior_Developer shall retrieve each Repository to the Local_Environment in less than 5 minutes.

  2. [R2] The System shall parse each Repository, extract each Dependency and Config_File, and store each result in the Polars_DataFrame with the columns [Repository_Name, Dependencies, Config_Files, LOC].

  3. [R3] The System shall cluster each Repository by [Dependencies AND Config_Files] within 1 minute.

  4. [R4] The System shall parse each code file into the AST, anonymize each local identifier, reorder statements in a random manner with constraints, and produce the Scrambled_Code that preserves structural patterns but removes domain semantics.

  5. [R5] The System shall collect each snippet of Scrambled_Code into Code_Soup and label each snippet by the cluster membership.

  6. [R6] The System shall use the LLM to analyze each snippet in Code_Soup and generate structured features in the Polars_DataFrame within 10 minutes.

  7. [R7] The System shall produce a comparative summary of each cluster’s structural patterns, highlighting differences in method-chaining usage or import organization.

  8. [R8] The Senior_Developer shall complete the final delivery of Code_Soup, the Polars_DataFrame, and each analysis result in less than 60 minutes from the start of the task.

4. Style Compliance with INCOSE Guidelines

  1. Precision

    • Definite Article: Each requirement refers to the System or the Developer rather than using “a” or “an.”
    • Active Voice: Each requirement clearly identifies the subject (e.g., “The System shall…”).
    • Quantified Metrics: Timing constraints and data structure columns are precisely stated.

  2. Singularity

    • Each requirement states one main action, avoiding combinators like “and/or.”
    • Conditions or clusters are explicitly bracketed (e.g., [Dependencies AND Config_Files]).

  3. Non-Ambiguity

    • No vague adverbs (“quickly,” “usually”) or adjectives (“relevant,” “appropriate”).
    • No pronouns referencing undefined nouns (e.g., “it,” “they”).

  4. Completeness

    • Each requirement is self-contained and does not rely on headings for clarity.
    • Applicability conditions (e.g., time limits) are stated explicitly.

  5. Realism

    • No unachievable absolutes (e.g., “100%”), each time-based or performance-based threshold is measurable.

  6. Uniform Language

    • Each requirement uses consistent terms defined in the Glossary.
    • No abbreviations are used without definition, and acronyms (LLM, AST) are consistently spelled.

  7. Modularity

    • Related requirements (e.g., parsing, clustering, and code transformation) are grouped under this PRD.

5. Verification

  • Demonstration: The Senior_Developer shall run the pipeline within the Local_Environment and show that clustering and AST-based transformations are completed within the stated time limits.
  • Inspection: Polars_DataFrame columns and Code_Soup snippets shall be checked to confirm anonymization of code and presence of structural patterns.
  • Analysis: The LLM’s summaries shall be inspected to verify that method-chaining or import style differences are highlighted per cluster.

6. Acceptance Criteria

A Senior_Developer completes each requirement within 60 minutes end-to-end, producing:

  1. A Polars_DataFrame that captures Dependencies, Config_Files, and relevant code metrics.
  2. A set of Scrambled_Code snippets combined into Code_Soup and labeled by cluster.
  3. A final analysis or summary that highlights contrastive code patterns in a parseable format.

All delivered materials must pass Verification as described in Section 5.

End of PRD****Product Requirements Document (PRD)
Title: Code Masking and Pattern Analysis Pipeline

1. Purpose and Scope

This PRD defines the minimal set of requirements for a code-masking and pattern-analysis pipeline that parses multiple code Repositories, scrambles domain semantics while preserving structural patterns, and generates Polars_DataFrame outputs for subsequent analysis. These requirements conform to the INCOSE guidelines for clarity, singularity, consistency, measurability, and correctness.

A single Senior_Developer shall execute these requirements in less than 60 minutes, guaranteeing delivery of Code_Soup and Polars_DataFrame artifacts alongside a cluster-based contrastive analysis.

2. Definitions (Glossary)

  • Senior_Developer: The single developer who executes each requirement in this PRD.
  • System: The code or tooling that implements the pipeline and executes the transformations, clustering, and analysis.
  • Repository: The codebase retrieved from a version-control platform.
  • Dependency: Each external library or module referenced by the code.
  • Config_File: Each configuration file (for example, pyproject.toml, Dockerfile, package.json) present in the Repository.
  • Polars_DataFrame: The tabular structure that stores Repository-level or snippet-level features for analysis.
  • AST: The Abstract_Syntax_Tree representation of code, used to parse and transform structural elements.
  • Scrambled_Code: The anonymized code snippets that preserve structural style but omit domain-specific semantics.
  • Code_Soup: The aggregated set of Scrambled_Code snippets labeled with cluster or metadata.
  • LLM: The Large_Language_Model that extracts stylistic patterns from Code_Soup or generates contrastive analysis.
  • Local_Environment: The Senior_Developer’s controlled environment or machine used to run the pipeline.

3. Requirements

  1. [R1] The Senior_Developer shall retrieve each Repository to the Local_Environment in less than 5 minutes.

  2. [R2] The System shall parse each Repository, extract each Dependency and Config_File, and store each result in the Polars_DataFrame with the columns [Repository_Name, Dependencies, Config_Files, LOC].

  3. [R3] The System shall cluster each Repository by [Dependencies AND Config_Files] within 1 minute.

  4. [R4] The System shall parse each code file into the AST, anonymize each local identifier, reorder statements in a random manner with constraints, and produce the Scrambled_Code that preserves structural patterns but removes domain semantics.

  5. [R5] The System shall collect each snippet of Scrambled_Code into Code_Soup and label each snippet by the cluster membership.

  6. [R6] The System shall use the LLM to analyze each snippet in Code_Soup and generate structured features in the Polars_DataFrame within 10 minutes.

  7. [R7] The System shall produce a comparative summary of each cluster’s structural patterns, highlighting differences in method-chaining usage or import organization.

  8. [R8] The Senior_Developer shall complete the final delivery of Code_Soup, the Polars_DataFrame, and each analysis result in less than 60 minutes from the start of the task.

4. Style Compliance with INCOSE Guidelines

  1. Precision

    • Definite Article: Each requirement refers to the System or the Developer rather than using “a” or “an.”
    • Active Voice: Each requirement clearly identifies the subject (e.g., “The System shall…”).
    • Quantified Metrics: Timing constraints and data structure columns are precisely stated.

  2. Singularity

    • Each requirement states one main action, avoiding combinators like “and/or.”
    • Conditions or clusters are explicitly bracketed (e.g., [Dependencies AND Config_Files]).

  3. Non-Ambiguity

    • No vague adverbs (“quickly,” “usually”) or adjectives (“relevant,” “appropriate”).
    • No pronouns referencing undefined nouns (e.g., “it,” “they”).

  4. Completeness

    • Each requirement is self-contained and does not rely on headings for clarity.
    • Applicability conditions (e.g., time limits) are stated explicitly.

  5. Realism

    • No unachievable absolutes (e.g., “100%”), each time-based or performance-based threshold is measurable.

  6. Uniform Language

    • Each requirement uses consistent terms defined in the Glossary.
    • No abbreviations are used without definition, and acronyms (LLM, AST) are consistently spelled.

  7. Modularity

    • Related requirements (e.g., parsing, clustering, and code transformation) are grouped under this PRD.

5. Verification

  • Demonstration: The Senior_Developer shall run the pipeline within the Local_Environment and show that clustering and AST-based transformations are completed within the stated time limits.
  • Inspection: Polars_DataFrame columns and Code_Soup snippets shall be checked to confirm anonymization of code and presence of structural patterns.
  • Analysis: The LLM’s summaries shall be inspected to verify that method-chaining or import style differences are highlighted per cluster.

6. Acceptance Criteria

A Senior_Developer completes each requirement within 60 minutes end-to-end, producing:

  1. A Polars_DataFrame that captures Dependencies, Config_Files, and relevant code metrics.
  2. A set of Scrambled_Code snippets combined into Code_Soup and labeled by cluster.
  3. A final analysis or summary that highlights contrastive code patterns in a parseable format.

All delivered materials must pass Verification as described in Section 5.

End of PRD

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