Beginning iOS Programming
Verified live by HTTP probe across 16 observations. Pulse has been flat over the last 30 days.
HTTP liveness
realSignal telemetry
4 families · 2 observed · observed onlyappcoda.comedge
behind Cloudflareserver
cloudflareTranco rank
#686,689
Analyst read
generated from the observed metrics above · no external narrativeBeginning iOS Programming's listed site resolved live when we last probed it on Aug 19, 2026, so we mark it verified alive. Its Pulse Index is 44.2 of 100, built from 2 of 4 observed signal families. Observed footprint: 3 functional tags. It has no curated competitive-alternative edges yet, so the comparable set below is functional tag-similarity — read it with the confidence flags.
Comparable set
curated alternatives → functional tag-similarity| Company | Basis | Overlap | Pulse | 30d Δ | Status |
|---|---|---|---|---|---|
| A Best-in-Class iOS Appeducation | similar | 100% | 40.0 | 0.0 | ● live |
| Metaleducation | similar | 100% | 8.0 | 0.0 | — unverified |
| Great Medium Tutorial for Swifteducation | similar | 100% | 8.0 | 0.0 | — unverified |
| Parsing JSON in Swifteducation | similar | 75% | 40.0 | +9.6 | ● live |
| Swift in Action: Building Realtime iOS Apps with Firebaseeducation | similar | 75% | 8.0 | 0.0 | — unverified |
| Swiftriseducation | similar | 75% | 16.0 | 0.0 | → redirected |
| Linuxereducation | similar | 75% | 32.8 | -7.2 | ● live |
| Avoiding the Most Common Auto Layout Mistakes: An Email Courseeducation | similar | 75% | 0.0 | 0.0 | ■ inactive |
Confidence reflects source and category coherence: curated = an editorially linked alternative; similar = strong functional tag-overlap in the same category; tag-overlap = shared tags only and may be noisy. Overlap is the shared functional-tag ratio (Jaccard) for tag-matched rows. Pulse is the observed-activity index real and 30d Δ its signed month change; a dash means insufficient observed history, never zero.
Structure
observed attributesFunding & team
not in sourceNo disclosed funding in our sources. Funding data covers only ~1% of the corpus (462 rounds across 79K products), so absence here is unknown, not zero— we don't estimate a number we can't source.