Fix JavaDoc warnings

README.md

@@ -130,7 +130,7 @@ when using this approach ensure the value you are reporting accounts for concurr
 
 ### Summary
 
-Summaries and Histograms can both be used to monitor latencies (or other things like request sizes).
+Summaries and Histograms can both be used to monitor distributions, like latencies or request sizes.
 
 An overview of when to use Summaries and when to use Histograms can be found on [https://prometheus.io/docs/practices/histograms](https://prometheus.io/docs/practices/histograms).
 

simpleclient/src/main/java/io/prometheus/client/SimpleCollector.java

@@ -11,7 +11,7 @@
  * <p>
  * This class handles common initialization and label logic for the standard metrics.
  * You should never subclass this class.
- * <p>
+ *
  * <h2>Initialization</h2>
  * After calling build() on a subclass, {@link Builder#name(String) name},
  * {@link SimpleCollector.Builder#help(String) help},

simpleclient/src/main/java/io/prometheus/client/Summary.java

@@ -13,7 +13,7 @@
 import java.util.concurrent.TimeUnit;
 
 /**
- * {@link Summary} metrics and {@link Histogram} metrics can both be used to monitor latencies (or other things like request sizes).
+ * {@link Summary} metrics and {@link Histogram} metrics can both be used to monitor distributions like latencies or request sizes.
  * <p>
  * An overview of when to use Summaries and when to use Histograms can be found on <a href="https://prometheus.io/docs/practices/histograms">https://prometheus.io/docs/practices/histograms</a>.
  * <p>
@@ -47,12 +47,12 @@
  * The {@link Summary} class provides different utility methods for observing values, like {@link #observe(double)},
  * {@link #startTimer()} and {@link Timer#observeDuration()}, {@link #time(Callable)}, etc.
  * <p>
- * By default, {@link Summary} metrics provide the <tt>count</tt> and the <tt>sum</tt>. For example, if you measure
- * latencies of a REST service, the <tt>count</tt> will tell you how often the REST service was called,
- * and the <tt>sum</tt> will tell you the total aggregated response time.
- * You can calculate the average response time using a Prometheus query dividing <tt>sum / count</tt>.
+ * By default, {@link Summary} metrics provide the {@code count} and the {@code sum}. For example, if you measure
+ * latencies of a REST service, the {@code count} will tell you how often the REST service was called,
+ * and the {@code sum} will tell you the total aggregated response time.
+ * You can calculate the average response time using a Prometheus query dividing {@code sum / count}.
  * <p>
- * In addition to <tt>count</tt> and <tt>sum</tt>, you can configure a Summary to provide quantiles:
+ * In addition to {@code count} and {@code sum}, you can configure a Summary to provide quantiles:
  *
  * <pre>
  * Summary requestLatency = Summary.build()
@@ -76,9 +76,9 @@
  *
  * <ul>
  *   <li>You can set an allowed error of 0, but then the {@link Summary} will keep all observations in memory.</li>
- *   <li>You can track the minimum value with <tt>.quantile(0.0, 0.0)</tt>.
+ *   <li>You can track the minimum value with {@code .quantile(0.0, 0.0)}.
  *       This special case will not use additional memory even though the allowed error is 0.</li>
- *   <li>You can track the maximum value with <tt>.quantile(1.0, 0.0)</tt>.
+ *   <li>You can track the maximum value with {@code .quantile(1.0, 0.0)}.
  *       This special case will not use additional memory even though the allowed error is 0.</li>
  * </ul>
  *

simpleclient_jetty/src/main/java/io/prometheus/client/jetty/JettyStatisticsCollector.java

@@ -9,8 +9,7 @@
 
 /**
  * Collect metrics from jetty's org.eclipse.jetty.server.handler.StatisticsHandler.
- * <p>
- * <pre>{@code
+ * <pre>
  * Server server = new Server(8080);
  *
  * ServletContextHandler context = new ServletContextHandler();
@@ -29,7 +28,7 @@
  * server.setHandler(handlers);
  *
  * server.start();
- * }</pre>
+ * </pre>
  */
 public class JettyStatisticsCollector extends Collector {
   private final StatisticsHandler statisticsHandler;