tftsr-devops_investigation/node_modules/sucrase/dist/computeSourceMap.js

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feat: initial implementation of TFTSR IT Triage & RCA application Implements Phases 1-8 of the TFTSR implementation plan. Rust backend (Tauri 2.x, src-tauri/): - Multi-provider AI: OpenAI-compatible, Anthropic, Gemini, Mistral, Ollama - PII detection engine: 11 regex patterns with overlap resolution - SQLCipher AES-256 encrypted database with 10 versioned migrations - 28 Tauri IPC commands for triage, analysis, document, and system ops - Ollama: hardware probe, model recommendations, pull/delete with events - RCA and blameless post-mortem Markdown document generators - PDF export via printpdf - Audit log: SHA-256 hash of every external data send - Integration stubs for Confluence, ServiceNow, Azure DevOps (v0.2) Frontend (React 18 + TypeScript + Vite, src/): - 9 pages: full triage workflow NewIssue→LogUpload→Triage→Resolution→RCA→Postmortem→History+Settings - 7 components: ChatWindow, TriageProgress, PiiDiffViewer, DocEditor, HardwareReport, ModelSelector, UI primitives - 3 Zustand stores: session, settings (persisted), history - Type-safe tauriCommands.ts matching Rust backend types exactly - 8 IT domain system prompts (Linux, Windows, Network, K8s, DB, Virt, HW, Obs) DevOps: - .woodpecker/test.yml: rustfmt, clippy, cargo test, tsc, vitest on every push - .woodpecker/release.yml: linux/amd64 + linux/arm64 builds, Gogs release upload Verified: - cargo check: zero errors - tsc --noEmit: zero errors - vitest run: 13/13 unit tests passing Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
2026-03-15 03:36:25 +00:00
"use strict";Object.defineProperty(exports, "__esModule", {value: true});var _genmapping = require('@jridgewell/gen-mapping');
var _charcodes = require('./parser/util/charcodes');
/**
* Generate a source map indicating that each line maps directly to the original line,
* with the tokens in their new positions.
*/
function computeSourceMap(
{code: generatedCode, mappings: rawMappings},
filePath,
options,
source,
tokens,
) {
const sourceColumns = computeSourceColumns(source, tokens);
const map = new (0, _genmapping.GenMapping)({file: options.compiledFilename});
let tokenIndex = 0;
// currentMapping is the output source index for the current input token being
// considered.
let currentMapping = rawMappings[0];
while (currentMapping === undefined && tokenIndex < rawMappings.length - 1) {
tokenIndex++;
currentMapping = rawMappings[tokenIndex];
}
let line = 0;
let lineStart = 0;
if (currentMapping !== lineStart) {
_genmapping.maybeAddSegment.call(void 0, map, line, 0, filePath, line, 0);
}
for (let i = 0; i < generatedCode.length; i++) {
if (i === currentMapping) {
const genColumn = currentMapping - lineStart;
const sourceColumn = sourceColumns[tokenIndex];
_genmapping.maybeAddSegment.call(void 0, map, line, genColumn, filePath, line, sourceColumn);
while (
(currentMapping === i || currentMapping === undefined) &&
tokenIndex < rawMappings.length - 1
) {
tokenIndex++;
currentMapping = rawMappings[tokenIndex];
}
}
if (generatedCode.charCodeAt(i) === _charcodes.charCodes.lineFeed) {
line++;
lineStart = i + 1;
if (currentMapping !== lineStart) {
_genmapping.maybeAddSegment.call(void 0, map, line, 0, filePath, line, 0);
}
}
}
const {sourceRoot, sourcesContent, ...sourceMap} = _genmapping.toEncodedMap.call(void 0, map);
return sourceMap ;
} exports.default = computeSourceMap;
/**
* Create an array mapping each token index to the 0-based column of the start
* position of the token.
*/
function computeSourceColumns(code, tokens) {
const sourceColumns = new Array(tokens.length);
let tokenIndex = 0;
let currentMapping = tokens[tokenIndex].start;
let lineStart = 0;
for (let i = 0; i < code.length; i++) {
if (i === currentMapping) {
sourceColumns[tokenIndex] = currentMapping - lineStart;
tokenIndex++;
currentMapping = tokens[tokenIndex].start;
}
if (code.charCodeAt(i) === _charcodes.charCodes.lineFeed) {
lineStart = i + 1;
}
}
return sourceColumns;
}