Archived learning reference. New learning content is maintained at Android Engineers Academy. For interview preparation, use the question library. The exercises and historical catalog below remain available for reference.

Android Engineering Foundations

Practice the data structures and reasoning that appear in everyday Android work. Start with the small exercises below, then use the historical topic catalog as a reference rather than a required checklist.

Learning order

Step	Learn	Show that you understand
1	Lists, sets, maps, and equality	Deduplicate identifiers while preserving order.
2	Time and space complexity	Explain why a set avoids repeated list scans.
3	Stacks and queues	Model a navigation history or pending-work queue.
4	Sorting and binary search	Explain the sorted-input requirement and boundary cases.
5	State and separation of concerns	Keep data transformations independent of UI code.

Worked example: merge identifiers from two pages

A paginated feed returns [3, 1, 3], then [1, 2]. We want [3, 1, 2]: the first occurrence wins, and display order remains stable.

fun mergeIds(existing: List<Int>, incoming: List<Int>): List<Int> {
    val seen = mutableSetOf<Int>()
    val result = mutableListOf<Int>()
    for (id in existing + incoming) {
        if (seen.add(id)) result.add(id)
    }
    return result
}

fun main() {
    check(mergeIds(listOf(3, 1, 3), listOf(1, 2)) == listOf(3, 1, 2))
    check(mergeIds(emptyList(), emptyList()).isEmpty())
    check(mergeIds(listOf(7), listOf(7, 7)) == listOf(7))
}

Trace the calls to seen.add: 3 succeeds, 1 succeeds, the second 3 fails, the next 1 fails, and 2 succeeds. With expected constant-time hash-set operations, this takes expected O(n + m) time and O(n + m) additional space, including the concatenated list. Scanning the growing output list for every identifier would instead have quadratic worst-case time.

Try it: remove the concatenated intermediate list while preserving the result. Then decide how the rule changes if a later page contains a newer version of the same item. Explain whether the first or latest item should win before changing your implementation.

Worked example: find a value in sorted identifiers

For [2, 5, 8, 12, 19], search for 12. The middle value is 8, so discard it and everything left of it. Search indices 3 through 4; index 3 contains 12. If the target is 7, the narrowed interval eventually becomes empty and the result is absent.

Try it: implement an iterative binary search that returns an index or -1. Check an empty list, one element, first/last elements, a missing value, and duplicates. State whether your implementation returns any occurrence or the first occurrence. Expected search complexity is O(log n) time and O(1) extra space; sorting unsorted input is separate work.

Continue learning

Android Engineers Academy provides the broader learning paths. Apply a foundation in the Compose masterclass, then explain the choice in your project README.