Editorial and corrections policy

Review depth is proportional to risk and complexity. Architecture, security, payments, infrastructure, data handling, and version-sensitive implementation guidance require closer technical checking than general explanatory material.

Review may include checking code and configuration for internal consistency, comparing behavior with primary documentation, verifying version assumptions, reviewing security implications, and confirming that limitations and tradeoffs are stated clearly.

A separate reviewer is credited only when a distinct person has performed and accepted that review. The absence of a “reviewed by” credit must not be interpreted as an independent expert review.

Primary sources are preferred for factual and technical claims. Depending on the topic, these may include official framework or vendor documentation, standards, specifications, release notes, source repositories, regulatory publications, and original project evidence that can be disclosed.

Version-sensitive statements should identify the relevant version or publication context where omission could mislead readers. External sources should be linked close to the claim when practical, and quotations must preserve their original meaning.

Performance, cost, reliability, traffic, conversion, rating, client-result, and similar quantitative claims must be verifiable and properly qualified. A target, estimate, benchmark, internal observation, and achieved client result are different types of evidence and must not be presented as interchangeable.

SoftwareCrafting may use AI-assisted tools during research organization, outlining, editing, summarization, code explanation, or quality checks. AI output is not treated as a source and does not replace accountable human authorship or technical review.

The responsible author or editor must verify factual claims, test or inspect technical examples where appropriate, check cited sources directly, remove fabricated details, and ensure the final article reflects SoftwareCrafting's editorial judgment.

Material AI involvement should be disclosed when it is relevant to a reader's assessment of originality, methodology, evidence, or potential limitations. Client confidential information and personal data must not be placed into third-party AI systems without appropriate authorization and safeguards.

Readers can report factual errors, broken examples, outdated versions, misleading claims, attribution problems, or undisclosed conflicts by emailing contact@softwarecrafting.in. Please include the page URL, the disputed passage, and supporting evidence when available.

Reports are assessed against the article, relevant sources, and any available project records. Confirmed material errors are corrected as promptly as practical. Minor spelling or formatting fixes may be made without a correction note.

Material corrections should be explained on the affected page when the original error could have changed a reader's decision or implementation. Substantive revisions may update the displayed modification date; dates must not be changed merely to imply freshness.

Content that cannot be corrected to a reliable standard may be consolidated, redirected, clearly archived, or removed. Commercial relationships or service relevance do not override the correction decision.

SoftwareCrafting publishes content related to services it provides. Relevant service links or calls to action may appear in articles, but they should not distort technical conclusions, hide meaningful alternatives, or turn unsupported promotional language into an engineering recommendation.

Sponsorships, affiliate relationships, supplied products, or other material conflicts should be disclosed on the affected content. No payment guarantees positive coverage or prevents a justified correction.