totpeak = math.Max(math.Max(tot.Peak, totpeak), tot.Curr)
		lpeak = math.Max(math.Max(v[Large].Peak, lpeak), v[Large].Curr)
		speak = math.Max(math.Max(v[Small].Peak, speak), v[Small].Curr)
		if lpeak > 0 || speak > 0 {
			count++
		}
	}
	if count > 0 {
		lrg := XferStats{
			Avg:  lavg / float64(count),
			Curr: lcurr / float64(count),
			Peak: lpeak,
		}
		sml := XferStats{

	"sort"
	"strings"
	"time"
)

const (
	// deadline (in seconds) up to which the go routine leak detection has to be retried.
	leakDetectDeadline = 5
	// pause time (in milliseconds) between each snapshot at the end of the go routine leak detection.
	leakDetectPauseTimeMs = 50
)

// LeakDetect - type with  methods for go routine leak detection.
type LeakDetect struct {
	relevantRoutines map[string]bool
}

}

func (rx *XferStats) merge(o XferStats) XferStats {
	curr := calcAvg(rx.curr(), o.curr(), rx.N, o.N)
	peak := rx.Peak
	if o.Peak > peak {
		peak = o.Peak
	}
	if curr > peak {
		peak = curr
	}
	return XferStats{
		Avg:     calcAvg(rx.Avg, o.Avg, rx.N, o.N),
		Peak:    peak,
		Curr:    curr,
		measure: rx.measure,
		N:       rx.N + o.N,
	}
}

                break;
            }
        }
    }

    /**
     * Report a potential resource leak
     */
    private void reportPotentialLeak(ResourceHolder holder) {
        log.warn("Potential resource leak detected: {} ({}) - open for {} ms", holder.resourceId, holder.resourceType, holder.getAge());

        if (log.isDebugEnabled() && holder.allocationStackTrace != null) {

}

type latencyStat struct {
	lastmin lastMinuteLatency
	curr    time.Duration
	avg     time.Duration
	peak    time.Duration
	N       int64
}

func (l *latencyStat) update(d time.Duration) {
	l.lastmin.add(d)
	l.N++
	if d > l.peak {
		l.peak = d
	}
	l.curr = l.lastmin.getTotal().avg()
	l.avg = time.Duration((int64(l.avg)*(l.N-1) + int64(l.curr)) / l.N)
}

        // The leak counter may or may not increment depending on GC timing
        assertNotNull(stats.get("totalLeaks"));
    }

    private void createLeakyResource() {
        TestResource resource = new TestResource("leaky");
        resourceManager.registerResource(resource);
        // Resource goes out of scope without closing - potential leak
    }

    @Test

			}
		case "av":
			z.Avg, err = dc.ReadFloat64()
			if err != nil {
				err = msgp.WrapError(err, "Avg")
				return
			}
		case "p":
			z.Peak, err = dc.ReadFloat64()
			if err != nil {
				err = msgp.WrapError(err, "Peak")
				return
			}
		case "n":
			z.N, err = dc.ReadInt64()
			if err != nil {
				err = msgp.WrapError(err, "N")
				return
			}
		default:

         */
        public JvmThreadsObj() {
            // Default constructor
        }

        /** Current number of threads */
        public int count;
        /** Peak number of threads */
        public int peak;
    }

    /**
     * Data transfer object representing JVM class loading statistics.
     */
    public static class JvmClassesObj {
        /**
         * Default constructor.

research](https://scholar.google.com/scholar?q=gpu+side+channel) shows that it
might be possible to use side channel attacks on the GPU to leak data from other
running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

  @Override public void log(String message) {
    Timber.tag("OkHttp").d(message);
  }
});
```

**Warning**: The logs generated by this interceptor when using the `HEADERS` or `BODY` levels have
the potential to leak sensitive information such as "Authorization" or "Cookie" headers and the
contents of request and response bodies. This data should only be logged in a controlled way or in
a non-production environment.