waylonflinn/weblas

Unit Test Float Encode Exhaustively

Open

#11 opened on Dec 16, 2015

View on GitHub
 (2 comments) (0 reactions) (0 assignees)JavaScript (701 stars) (56 forks)batch import
correctnesshelp wanted

Description

The floating point encode step is a tricky bit to get right. Issue #10 shows that numerical stability issues can make a big difference in some edge cases.

Encoding each unique floating point value as an element of a 4098 square matrix should require only a few hundred of these matrices. This should be doable in a reasonable amount of time.

References

Contributor guide

Tech stack
javascript
Domain
testing
Issue type
test
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
IEEE 754 floating pointWebGL fundamentalsweblas codebase structureunit testing practices
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
20
Research direction
First, review the existing float encode implementation in the weblas source code (likely in a WebGL shader or JavaScript helper). Understand the matrix format (4096 elements per matrix) and the encoding scheme. Then, generate a comprehensive set of test cases covering all IEEE 754 special values (NaN, Infinity, denormals) and edge cases. Use JavaScript's Float32Array to create known floating point values and compare the encoded output against a reference implementation. Check issue #10 for previously identified numerical stability issues that need attention.
Unit Test Float Encode Exhaustively · waylonflinn/weblas#11 | Good First Issue