// If we hit the max load factor or we have too many overflow buckets,
	// and we're not already in the middle of growing, start growing.
	if !h.growing() && (overLoadFactor(h.count+1, h.B) || tooManyOverflowBuckets(h.noverflow, h.B)) {
		hashGrow(t, h)
		goto again // Growing the table invalidates everything, so try again
	}

	if insertb == nil {

	// If we hit the max load factor or we have too many overflow buckets,
	// and we're not already in the middle of growing, start growing.
	if !h.growing() && (overLoadFactor(h.count+1, h.B) || tooManyOverflowBuckets(h.noverflow, h.B)) {
		hashGrow(t, h)
		goto again // Growing the table invalidates everything, so try again
	}

	if insertb == nil {

	// If we hit the max load factor or we have too many overflow buckets,
	// and we're not already in the middle of growing, start growing.
	if !h.growing() && (overLoadFactor(h.count+1, h.B) || tooManyOverflowBuckets(h.noverflow, h.B)) {
		hashGrow(t, h)
		goto again // Growing the table invalidates everything, so try again
	}

	if insertb == nil {

	doublecap := newcap + newcap
	if newLen > doublecap {
		return newLen
	}

	const threshold = 256
	if oldCap < threshold {
		return doublecap
	}
	for {
		// Transition from growing 2x for small slices
		// to growing 1.25x for large slices. This formula
		// gives a smooth-ish transition between the two.
		newcap += (newcap + 3*threshold) >> 2

		// We need to check `newcap >= newLen` and whether `newcap` overflowed.

type spanSet struct {
	// A spanSet is a two-level data structure consisting of a
	// growable spine that points to fixed-sized blocks. The spine
	// can be accessed without locks, but adding a block or
	// growing it requires taking the spine lock.
	//
	// Because each mspan covers at least 8K of heap and takes at
	// most 8 bytes in the spanSet, the growth of the spine is
	// quite limited.
	//

         * than a handful of exceptions. But it seems prudent to set a cap on how many we'll cache.
         * This avoids out-of-control memory consumption, and it keeps the cache from growing so
         * large that doing the lookup is noticeably slower than redoing the work would be.
         *
         * Ideally we'd have a real eviction policy, but until we see a problem in practice, I hope

<2> The `app` subproject
<3> The `app` source code
<4> The `app` build script
<5> The optional settings file
=====

== Step 2. Add another Subproject to the Build
Imagine that our project is growing and requires a custom library to function.

Let's create this imaginary `lib`.
First, create a `lib` folder:

[source,text]
----
mkdir lib
----

[source,text]
----
cd lib
----

func FreeOSMemory() {
	freeOSMemory()
}

// SetMaxStack sets the maximum amount of memory that
// can be used by a single goroutine stack.
// If any goroutine exceeds this limit while growing its stack,
// the program crashes.
// SetMaxStack returns the previous setting.
// The initial setting is 1 GB on 64-bit systems, 250 MB on 32-bit systems.
// There may be a system-imposed maximum stack limit regardless

			cleanup := setBits(bits)
			defer cleanup()

			b.StopTimer()
			x := New(data)
			size := testSaveRestore(nil, nil, x)       // verify correctness
			buf := bytes.NewBuffer(make([]byte, size)) // avoid growing
			b.SetBytes(int64(size))
			b.StartTimer()
			b.ReportAllocs()
			for i := 0; i < b.N; i++ {
				buf.Reset()
				if err := x.Write(buf); err != nil {
					b.Fatal(err)
				}
				var y Index

	secureHTTPClient *http.Client
	httpClient       *http.Client
	refreshTicker    *time.Ticker

	// Cached key will be removed from cache if (time.now - cachedItem.lastUsedTime >= evictionDuration), this prevents key cache growing indefinitely.
	evictionDuration time.Duration

	// Refresher job running interval.
	refreshInterval time.Duration

	// Refresher job running interval on failure.
	refreshIntervalOnFailure time.Duration