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internal/fuzz: log average execs/sec since last log

This change also fixes a bug with calculating the
total interesting count. When fuzzing with an empty
corpus, the fuzzing engine adds an starting corpus
value in that run in order to start fuzzing. That
meant that the interesting total count was off by one:
it would start at 1, even though the cache was empty.
Added some tests for this as well.

Fixes #48787

Change-Id: I47acf96f0a0797214ebb24a95366d8460bf303bc
Reviewed-on: https://go-review.googlesource.com/c/go/+/354150
Trust: Katie Hockman <katie@golang.org>
Run-TryBot: Katie Hockman <katie@golang.org>
TryBot-Result: Go Bot <gobot@golang.org>
Reviewed-by: Jay Conrod <jayconrod@google.com>
Reviewed-by: Roland Shoemaker <roland@golang.org>
This commit is contained in:
Katie Hockman 2021-10-05 16:25:06 -04:00
parent 4d8db00641
commit aecf4b12e1
2 changed files with 33 additions and 8 deletions

View File

@ -184,6 +184,20 @@ stdout ok
! stdout ^ok
stdout FAIL
# Fuzzing indicates that one new interesting value was found with an empty
# corpus, and the total size of the cache is now 1.
go clean -fuzzcache
go test -fuzz=Fuzz -fuzztime=10000x success_fuzz_test.go
stdout 'new interesting: 1'
stdout 'total: 1'
# Fuzzing again with a small fuzztime does not find any other interesting
# values but still indicates that the cache size is 1.
go test -fuzz=Fuzz -fuzztime=2x success_fuzz_test.go
stdout 'new interesting: 0'
stdout 'total: 1'
-- noop_fuzz_test.go --
package noop_fuzz

View File

@ -556,6 +556,13 @@ type coordinator struct {
// count is the number of values fuzzed so far.
count int64
// countLastLog is the number of values fuzzed when the output was last
// logged.
countLastLog int64
// timeLastLog is the time at which the output was last logged.
timeLastLog time.Time
// interestingCount is the number of unique interesting values which have
// been found this execution.
interestingCount int64
@ -618,12 +625,13 @@ func newCoordinator(opts CoordinateFuzzingOpts) (*coordinator, error) {
return nil, err
}
c := &coordinator{
opts: opts,
startTime: time.Now(),
inputC: make(chan fuzzInput),
minimizeC: make(chan fuzzMinimizeInput),
resultC: make(chan fuzzResult),
corpus: corpus,
opts: opts,
startTime: time.Now(),
inputC: make(chan fuzzInput),
minimizeC: make(chan fuzzMinimizeInput),
resultC: make(chan fuzzResult),
corpus: corpus,
timeLastLog: time.Now(),
}
if opts.MinimizeLimit > 0 || opts.MinimizeTimeout > 0 {
for _, t := range opts.Types {
@ -676,6 +684,7 @@ func (c *coordinator) updateStats(result fuzzResult) {
}
func (c *coordinator) logStats() {
now := time.Now()
if c.warmupRun() {
runSoFar := c.warmupInputCount - c.warmupInputLeft
if coverageEnabled {
@ -684,14 +693,16 @@ func (c *coordinator) logStats() {
fmt.Fprintf(c.opts.Log, "fuzz: elapsed: %s, testing seed corpus: %d/%d completed\n", c.elapsed(), runSoFar, c.warmupInputCount)
}
} else {
rate := float64(c.count) / time.Since(c.startTime).Seconds() // be more precise here
rate := float64(c.count-c.countLastLog) / now.Sub(c.timeLastLog).Seconds()
if coverageEnabled {
interestingTotalCount := len(c.corpus.entries) - len(c.opts.Seed)
interestingTotalCount := int64(c.warmupInputCount-len(c.opts.Seed)) + c.interestingCount
fmt.Fprintf(c.opts.Log, "fuzz: elapsed: %s, execs: %d (%.0f/sec), new interesting: %d (total: %d)\n", c.elapsed(), c.count, rate, c.interestingCount, interestingTotalCount)
} else {
fmt.Fprintf(c.opts.Log, "fuzz: elapsed: %s, execs: %d (%.0f/sec)", c.elapsed(), c.count, rate)
}
}
c.countLastLog = c.count
c.timeLastLog = now
}
// peekInput returns the next value that should be sent to workers.