diff --git a/docs/UNDERSTAND_REPO_AND_GSOC_TESTS.md b/docs/UNDERSTAND_REPO_AND_GSOC_TESTS.md
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+# changepoint repo quick guide
+
+This repository is the CRAN `changepoint` package. It provides exact and approximate changepoint detection algorithms with R front-end APIs and C back-end compute kernels.
+
+## 1) How this repo is organized
+
+- `R/`:
+  - User entry points: `cpt.mean()`, `cpt.var()`, `cpt.meanvar()` in `R/cpt.R`, and `cpt.reg()` in `R/CptReg.R`.
+  - Algorithm wrappers: `PELT`, `BINSEG`, `SEGNEIGH` wrappers call into C where needed.
+- `src/`:
+  - Core high-performance implementations for PELT/BinSeg/regression changepoint routines.
+- `tests/testthat/`:
+  - Regression tests for mean/variance/meanvar/regression behavior and plots/examples.
+- `man/`:
+  - `.Rd` documentation, including package-level and function examples.
+
+## 2) Mental model for `changepoint`
+
+At a high level:
+
+1. You call a front-end function (for example `cpt.mean(data, method="PELT")`).
+2. Input checks + penalty logic are applied in R.
+3. The chosen method dispatches to method-specific R wrappers.
+4. Wrappers call C implementations for speed where appropriate.
+5. Results are wrapped into S4 classes (`cpt`, `cpt.reg`, `cpt.range`) with plotting/summary methods.
+
+## 3) Where to read first
+
+1. `DESCRIPTION` and `NAMESPACE` for package scope and exports.
+2. `R/cpt.R` for top-level method/test-stat dispatch.
+3. `R/CptReg.R` for regression-changepoint flow.
+4. `R/PELT_one_func_minseglen.R` + `src/PELT_one_func_minseglen.c` to see R-to-C integration.
+5. `tests/testthat/` for expected behavior and edge cases.
+
+## 4) Easy test from GSoC spec
+
+Use `inst/gsoc/easy_envcpt_ar_tests.R` in this repo. It:
+
+- simulates a series with changing AR structure,
+- uses non-exported EnvCpt internals via `getFromNamespace("cpt.reg", "EnvCpt")`,
+- fits AR1 and AR2 changepoint models (without calling `envcpt()`),
+- saves a plot to `inst/gsoc/easy_envcpt_ar_plots.png`.
+
+Run:
+
+```bash
+Rscript inst/gsoc/easy_envcpt_ar_tests.R
+```
+
+## 5) Medium test in this repo
+
+Added: `tests/testthat/test-cptreg-edgecases.R`
+
+Coverage-focused edge cases include:
+- invalid method handling,
+- invalid `minseglen` handling,
+- warning path when `minseglen` is auto-bumped,
+- multi-dataset array input path,
+- unsupported `CROPS` path in `cpt.reg`.
+
+Run only this file quickly:
+
+```bash
+R -q -e "library(changepoint); testthat::test_file('tests/testthat/test-cptreg-edgecases.R')"
+```
+
+Note: full local `testthat::test_local('.')` may fail on systems missing local Fortran toolchain libs due native package compilation requirements.
+
+## 6) Hard test package scaffold
+
+A separate package scaffold is created at:
+
+- `/Users/kaikaizhang/Documents/research/gsoc-envcpt-ar-wrapper`
+
+It contains:
+- a wrapper function for AR1/AR2 with optional trend,
+- input validation,
+- unit tests,
+- GitHub Actions `R-CMD-check`,
+- covr + codecov workflow.
diff --git a/inst/gsoc/SUBMISSION_RESULTS.md b/inst/gsoc/SUBMISSION_RESULTS.md
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+# GSoC test results
+
+## Easy
+
+- Script: `inst/gsoc/easy_envcpt_ar_tests.R`
+- Plot output: `inst/gsoc/easy_envcpt_ar_plots.png`
+- Reproducible command:
+  - `Rscript inst/gsoc/easy_envcpt_ar_tests.R`
+- Latest local result:
+  - AR1 changepoints: `200`
+  - AR2 changepoints: `199`
+- GitHub artifacts:
+  - Script: `https://github.com/KaiKz/changepoint/blob/gsoc-tests-deliverables/inst/gsoc/easy_envcpt_ar_tests.R`
+  - Plot: `https://github.com/KaiKz/changepoint/blob/gsoc-tests-deliverables/inst/gsoc/easy_envcpt_ar_plots.png`
+
+## Medium
+
+- Added tests:
+  - `tests/testthat/test-cptreg-edgecases.R`
+- Reproducible command:
+  - `R -q -e "library(changepoint); testthat::test_file('tests/testthat/test-cptreg-edgecases.R')"`
+- Latest local result:
+  - test file passes locally
+- GitHub artifacts:
+  - Test file: `https://github.com/KaiKz/changepoint/blob/gsoc-tests-deliverables/tests/testthat/test-cptreg-edgecases.R`
+  - Commit: `https://github.com/KaiKz/changepoint/commit/d92ae02`
+  - PR: `https://github.com/KaiKz/changepoint/pull/new/gsoc-tests-deliverables`
+
+## Hard
+
+- Package scaffold path:
+  - `/Users/kaikaizhang/Documents/research/gsoc-envcpt-ar-wrapper`
+- Key function:
+  - `R/fit_ar_changepoint.R`
+- Reproducible commands:
+  - `R -q -e "testthat::test_local('.', reporter='summary')"`
+  - `R -q -e "cov <- covr::package_coverage(path='.'); covr::percent_coverage(cov)"`
+- Latest local result:
+  - tests pass
+  - coverage: `85.71%`
+- GitHub artifacts:
+  - Repository: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper`
+  - Main function: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper/blob/main/R/fit_ar_changepoint.R`
+  - Commit: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper/commit/717a815`
+  - CI workflow: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper/actions/workflows/R-CMD-check.yaml`
+  - Coverage workflow: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper/actions/workflows/coverage.yaml`
+
+## Submission links
+
+- Medium fork URL: `https://github.com/KaiKz/changepoint`
+- Medium commit URL: `https://github.com/KaiKz/changepoint/commit/d92ae02`
+- Medium PR URL: `https://github.com/KaiKz/changepoint/pull/new/gsoc-tests-deliverables`
+- Hard package repository URL: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper`
+- Hard CI URL: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper/actions/workflows/R-CMD-check.yaml`
+- Hard coverage URL: `https://github.com/KaiKz/gsoc-envcpt-ar-wrapper/actions/workflows/coverage.yaml`
diff --git a/inst/gsoc/easy_envcpt_ar_plots.png b/inst/gsoc/easy_envcpt_ar_plots.png
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diff --git a/inst/gsoc/easy_envcpt_ar_tests.R b/inst/gsoc/easy_envcpt_ar_tests.R
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+set.seed(20260331)
+
+suppressPackageStartupMessages({
+  library(EnvCpt)
+})
+
+# Generate piecewise AR(1) and AR(2) signals with changepoints in dependence.
+generate_piecewise_ar <- function(n_per_segment = 200) {
+  seg1 <- as.numeric(stats::arima.sim(
+    n = n_per_segment,
+    model = list(ar = 0.2),
+    sd = 1
+  ))
+  seg2 <- as.numeric(stats::arima.sim(
+    n = n_per_segment,
+    model = list(ar = 0.75),
+    sd = 1
+  ))
+  seg3 <- as.numeric(stats::arima.sim(
+    n = n_per_segment,
+    model = list(ar = c(0.6, -0.25)),
+    sd = 1
+  ))
+  c(seg1, seg2, seg3)
+}
+
+# Use EnvCpt non-exported function, as required by the GSoC easy test.
+fit_envcpt_nonexported_ar <- function(x, order = c(1L, 2L), with_trend = FALSE, minseglen = 20L) {
+  order <- as.integer(order[1])
+  stopifnot(is.numeric(x), length(x) > 100)
+  stopifnot(order %in% c(1L, 2L))
+  stopifnot(is.logical(with_trend), length(with_trend) == 1L)
+
+  cpt_reg <- getFromNamespace("cpt.reg", "EnvCpt")
+  n <- length(x)
+
+  if (order == 1L) {
+    if (!with_trend) {
+      design <- cbind(x[-1], rep(1, n - 1), x[-n])
+    } else {
+      design <- cbind(x[-1], rep(1, n - 1), seq_len(n - 1), x[-n])
+    }
+  } else {
+    if (!with_trend) {
+      design <- cbind(x[-c(1, 2)], rep(1, n - 2), x[2:(n - 1)], x[1:(n - 2)])
+    } else {
+      design <- cbind(
+        x[-c(1, 2)],
+        rep(1, n - 2),
+        seq_len(n - 2),
+        x[2:(n - 1)],
+        x[1:(n - 2)]
+      )
+    }
+  }
+
+  cpt_reg(
+    data = design,
+    method = "PELT",
+    minseglen = minseglen,
+    dist = "Normal",
+    class = TRUE,
+    param.estimates = TRUE
+  )
+}
+
+series <- generate_piecewise_ar()
+
+fit_ar1 <- fit_envcpt_nonexported_ar(series, order = 1L, with_trend = FALSE)
+fit_ar2 <- fit_envcpt_nonexported_ar(series, order = 2L, with_trend = FALSE)
+
+png("inst/gsoc/easy_envcpt_ar_plots.png", width = 1600, height = 700, res = 130)
+par(mfrow = c(1, 2))
+plot(fit_ar1, main = "EnvCpt non-exported AR1 changepoints")
+plot(fit_ar2, main = "EnvCpt non-exported AR2 changepoints")
+dev.off()
+
+cat("AR1 changepoints:\n")
+print(cpts(fit_ar1))
+cat("AR2 changepoints:\n")
+print(cpts(fit_ar2))
+
+cat("\nSession info:\n")
+print(sessionInfo())
diff --git a/tests/testthat/test-cptreg-edgecases.R b/tests/testthat/test-cptreg-edgecases.R
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+context("cpt.reg edge-case tests")
+
+set.seed(42)
+n <- 120
+x1 <- rnorm(n)
+x2 <- rnorm(n)
+y <- c(rnorm(n / 2, mean = 0), rnorm(n / 2, mean = 2))
+reg_data <- cbind(y, 1, x1, x2)
+
+test_that("unsupported method is rejected", {
+  expect_error(
+    cpt.reg(reg_data, method = "BinSeg"),
+    "Invalid method, must be AMOC or PELT"
+  )
+})
+
+test_that("invalid minseglen values are rejected", {
+  expect_error(
+    cpt.reg(reg_data, minseglen = 0),
+    "must be positive integer"
+  )
+  expect_error(
+    cpt.reg(reg_data, minseglen = 2.5),
+    "must be positive integer"
+  )
+})
+
+test_that("small minseglen is bumped to number of columns", {
+  expect_warning(
+    fit <- cpt.reg(reg_data, method = "AMOC", minseglen = 1),
+    "minseglen is too small"
+  )
+  expect_s4_class(fit, "cpt.reg")
+})
+
+test_that("multiple datasets return list of cpt.reg", {
+  reg_data_2 <- reg_data
+  reg_data_2[, 1] <- reg_data_2[, 1] + rnorm(nrow(reg_data_2), sd = 0.05)
+  arr <- array(NA_real_, dim = c(2, nrow(reg_data), ncol(reg_data)))
+  arr[1, , ] <- reg_data
+  arr[2, , ] <- reg_data_2
+  out <- cpt.reg(arr, method = "AMOC", minseglen = 5)
+  expect_type(out, "list")
+  expect_equal(length(out), 2)
+  expect_s4_class(out[[1]], "cpt.reg")
+  expect_s4_class(out[[2]], "cpt.reg")
+})
+
+test_that("CROPS penalty remains unsupported for cpt.reg", {
+  expect_error(
+    cpt.reg(reg_data, penalty = "CROPS", pen.value = c(2, 4)),
+    "CROPS has not yet been implemented for cpt.reg"
+  )
+})