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Observability of the Java Virtual Machine

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The JVM is one of the most observable runtimes. It provides us lots of tools for troubleshooting a JVM application in production. 1. Thread observability Threads are how the JVM actually does work. When something is wrong in production, the symptom is almost always a thread: stopped, blocked, leaking etc. Thread dumps work on any JVM with no  instrumentation, no agents, no restarts. <Example project link with /threaddump endpoint>         // (1) Deadlock — two threads grab the same pair of locks in opposite order.         new Thread(() -> grab(LOCK_A, LOCK_B), "deadlock-A-then-B").start();         new Thread(() -> grab(LOCK_B, LOCK_A), "deadlock-B-then-A").start(); http://localhost:8080/actuator/threaddump To list the JVMS, we can use the command below. PS C:\observe-jvm> jps -lv 25296 jdk.jcmd/sun.tools.jps.Jps -Dapplication.home=C:\Program Files\Microsoft\jdk-21.0.3.9-hotspot -Xms8m -Djdk.module.main=...
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A Code Analyzer for a Subset of Java Language (J-) Using ANTLR - PART 2

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As we know, semantic analysis of a compiler includes checking the types of expressions. To do that, we have to maintain a Symbol Table which maps variable names to their types and locations. There maybe many variables with the same name which are in different scopes. This is legal in most languages and we have to handle this situation. We have to know when following scopes are entered in: - class scope - method scope - no inner block scopes (my language does not support this currently) We will do type-checking in two phases. First we'll populate the Symbol Table and it will contain the symbols with their scopes. Then, we'll check the types of symbols that are subject to addition operation by querying the symbol table. ANTLR allows us to inject code in different places of the generated parser. We need to know when a class/method scope is entered and the end of any scope is reached. Below is some grammar code from the project : classDecl @init {visitor.beforeClass(); System.out.p...
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A Code Analyzer for a Subset of Java Language (J-) Using ANTLR - PART 1

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Our goal is to write a code analyzer for a language that is called "J minus". Source code of the whole project can be found here: https://code.google.com/p/j-minus/ Lets start with the language definition: Lexical Rules: Identifiers: Sequence of letters. Integer literals: A sequence of decimal digits. Binary operators: && Grammar Rules: Program -> MainClass ClassDecl* MainClass -> class id { public static void main (String [] id) { Statement* }} ClassDecl -> class id { VarDecl* MethodDecl* } VarDecl -> Type id ; MethodDecl -> public Type id ( ( formalParameter (, formalParameter)* )? ) { varDecl* statement* return exp; } FormalParameter -> Type id Statement -> id = Exp; Exp -> AdditionExp | SimpleExp SimpleExp -> id | int AdditionExp -> SimpleExp + SimpleExp Type: 'int' | 'boolean' ; We must pass following steps to reach our goal: 1) Implement the lexer and parser for the language. (use ANTLR) 2) Build the Abs...
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"Parsing" Konusu ile ilgili Temel Kavramlar

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--Halen yazım aşamasında-- Regular expressions yardımıyla bir programın "lexical" yapısını ifade edebildiğimizi görmüştük. Aynı şeyi dildeki cümleler için yapmak mümkün mü? Dildeki cümlelerin yapısını ifade etmek için "context free grammar" kavramı kullanılmakta. Dildeki karmaşık yapıları oluşturmak için "production" yaparak ilerlemek gerekiyor. Aşağıda 5 tane production ile ifade edilen bir dili inceleyelim: S -> S ; S S -> ID = E E -> E + E E -> ID E -> NUM Bu kuralları kullanarak bir cümle üretmeye çalışalım: S ; S ID = E ; ID = E ID = E + E; ID = E ID = ID + NUM; ID = NUM Burada ürettiğimiz cümlenin kaynak kodu (lexer ele almadan önce) şöyle olabilirdi: var = i + 4; j = 5 Burada tokenlerin değerleri: var, i, j, 4, 5 Token türleri: ID, NUM, "+", ";", "=" Gramer ifadesinde sağ tarafta bulunamayan sonlanmış semboller dikkati çekiyor. Bunlara "terminal symbol" deniliyor. Terminal semboller, token tür...
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The WeakReference class, monitoring memory leak and garbage collection in a Java application

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 Below is a Stack implementation that uses an internal resizeable array structure.  public class MyStack< T > implements Stack< T > { private static final int CAPACITY = 100 ; private Object[] array ; private int pos = 0 ; public MyStack () { this . array = new Object[ CAPACITY ] ; } @Override public void push ( T item) { if ( pos >= array . length / 2 ) { Object[] newArray = new Object[ pos * 2 ] ; System. arraycopy ( array , 0 , newArray , 0 , array . length ) ; array = newArray ; } array [ pos ++] = item ; } @Override public T pop () { if (isEmpty()) { throw new RuntimeException( "empty stack" ) ; } @SuppressWarnings ( "unchecked" ) T item = ( T ) array [ pos - 1 ] ; pos -= 1 ; return item ; } @Override @SuppressWarnings ( "unchecked" ) public T peek...
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Simplescalar Simulator - Part 2: sim-outorder.c

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sim-outorder implements a very detailed out-of-order issue superscalar processor with a two-level memory system and speculative execution support. This simulator is a performance simulator, tracking the latency of all pipeline operations. Let's have a look at SimpleScalar simulator's code related to iTLB. (Instruction Translation Lookaside Buffer) First, there are simulator options related to iTLB: /* register simulator-specific options */ void sim_reg_options(struct opt_odb_t *odb) { /* TLB options */ opt_reg_string(odb, "-tlb:itlb", "instruction TLB config, i.e., { |none}", &itlb_opt, "itlb:16:4096:4:l", /* print */TRUE, NULL); opt_reg_int(odb, "-tlb:lat", "inst/data TLB miss latency (in cycles)", &tlb_miss_lat, /* default */30, /* print */TRUE, /* format */NULL); } /* check simulator-specific option values */ void  sim_check_options(... ) { /* sim-outorder.c  line: 1098*/   /* u...
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Notes on Java Performance

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Performance monitoring, performance profiling and performance tuning are different activities. For example, monitoring is not an intrusive action but profiling is. Because it may be changing the responsiveness of the running application. User CPU utilization vs Kernel CPU utilization: The ideal situation is when Kernel CPU utilization is 0%. So ideally, all the CPU cycles must be spent on our application code. JVM just in time compiler performs dynamic optimizations. So it makes decisions while the program is running and generates native code with better performance. Java 1.0 was completely interpreted but beginning with Java 1.1.8, there was a just-in-time compiler. It was 8 times faster. After that, paralellizing the garbage collector was a huge improvement. There are hundreds of Java tuning flags. https://github.com/ScottOaks/JavaPerformanceTuning Boolean flags use this syntax: -XX:+FlagName enables the flag, and -XX:-FlagName disables the flag. 32 BIT VS 64 BIT Fr...
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