Lectures

We revisit the most treacherous parts of Go: the slice model as a “window” into an array (header: pointer/ len/ cap), why you must store the result of append, how a nil slice differs from an empty one, how to control aliasing via a full slice expression ( s[a:b:c]), and where copy helps. For maps: rules about nil maps, the v, ok := m[k] idiom, and stable output via sorting keys.

We break down Go’s string model as a sequence of bytes in UTF-8: how len, indexing, and range differ, why byte is not a “character”, and why rune is not always “what the user sees”. Then we build practical input normalization at the boundary: strings.TrimSpace, strings.Fields, strings.Join, case handling via strings.ToLower, and comparisons via strings.EqualFold. Finally: command parsing, searching ( strings.Contains), building strings with strings.Builder, and debugging strings by printing with %q.

We break down the “go-way” of error handling: why error is just a regular value, how to read the contract func X(...) (T, error), why an early return and guard clauses matter, how to add context via fmt.Errorf with %w, and how to properly check root causes with errors.Is/ errors.As. We’ll also look at errors.Join, a mermaid execution-flow diagram, and a mini TaskBox example built on a map.

We break down Go’s key idea: everything is passed by value, and a pointer is just a value-address. Using examples, we’ll see how the & and * operators work, why slice and map “already reference things”, what the difference is between new, make, and nil, and what traps show up in loops and with append. We’ll reinforce “value semantics” with a mini task-list logic using nextID, map, and slice.

We break down how to model data in Go so that errors “can’t happen”: we lock in invariants (for example, id > 0), introduce domain types ( TaskID, TaskTitle, Status), create factory functions with the (T, error) contract, normalize input via TrimSpace/ Fields, and keep validation at the system boundary (for example, stdin). We will also compare “parallel slices” with storing data via a map and discuss common mistakes.