In computer science, garbage collection (GC) is a form of automatic memory management. The garbage collector attempts to reclaim memory which was allocated by the program, but is no longer referenced; such memory is called garbage. Garbage collection was invented by American computer scientist John McCarthy around 1959 to simplify manual memory management in Lisp.
Java is a high-level, class-based, object-oriented programming language that is designed to have as few implementation dependencies as possible. It is a general-purpose programming language intended to let programmers write once, run anywhere (WORA), meaning that compiled Java code can run on all platforms that support Java without the need to recompile. Java applications are typically compiled to bytecode that can run on any Java virtual machine (JVM) regardless of the underlying computer architecture. The syntax of Java is similar to C and C++, but has fewer low-level facilities than either of them. The Java runtime provides dynamic capabilities that are typically not available in traditional compiled languages. As of 2019, Java was one of the most popular programming languages in use according to GitHub, particularly for client–server web applications, with a reported 9 million developers.
In computer science, a memory leak is a type of resource leak that occurs when a computer program incorrectly manages memory allocations in a way that memory which is no longer needed is not released. A memory leak may also happen when an object is stored in memory but cannot be accessed by the running code. A memory leak has symptoms similar to a number of other problems and generally can only be diagnosed by a programmer with access to the program's source code.
In computer science, reference counting is a programming technique of storing the number of references, pointers, or handles to a resource, such as an object, a block of memory, disk space, and others.
In computer programming, tracing garbage collection is a form of automatic memory management that consists of determining which objects should be deallocated by tracing which objects are reachable by a chain of references from certain "root" objects, and considering the rest as "garbage" and collecting them. Tracing garbage collection is the most common type of garbage collection – so much so that "garbage collection" often refers to tracing garbage collection, rather than other methods such as reference counting – and there are a large number of algorithms used in implementation.
Java Card is a software technology that allows Java-based applications (applets) to be run securely on smart cards and more generally on similar secure small memory footprint devices which are called "secure elements" (SE). Today, a Secure Element is not limited to its smart cards and other removable cryptographic tokens form factors; embedded SEs soldered onto a device board and new security designs embedded into general purpose chips are also widely used. Java Card addresses this hardware fragmentation and specificities while retaining code portability brought forward by Java.
In software engineering, profiling is a form of dynamic program analysis that measures, for example, the space (memory) or time complexity of a program, the usage of particular instructions, or the frequency and duration of function calls. Most commonly, profiling information serves to aid program optimization, and more specifically, performance engineering.
In computer science, manual memory management refers to the usage of manual instructions by the programmer to identify and deallocate unused objects, or garbage. Up until the mid-1990s, the majority of programming languages used in industry supported manual memory management, though garbage collection has existed since 1959, when it was introduced with Lisp. Today, however, languages with garbage collection such as Java are increasingly popular and the languages Objective-C and Swift provide similar functionality through Automatic Reference Counting. The main manually managed languages still in widespread use today are C and C++ – see C dynamic memory allocation.
Dynamic program analysis is analysis of computer software that involves executing the program in question. Dynamic program analysis includes familiar techniques from software engineering such as unit testing, debugging, and measuring code coverage, but also includes lesser-known techniques like program slicing and invariant inference. Dynamic program analysis is widely applied in security in the form of runtime memory error detection, fuzzing, dynamic symbolic execution, and taint tracking.
In software development, the programming language Java was historically considered slower than the fastest 3rd generation typed languages such as C and C++. The main reason being a different language design, where after compiling, Java programs run on a Java virtual machine (JVM) rather than directly on the computer's processor as native code, as do C and C++ programs. Performance was a matter of concern because much business software has been written in Java after the language quickly became popular in the late 1990s and early 2000s.
Eclipse OpenJ9 is a high performance, scalable, Java virtual machine (JVM) implementation that is fully compliant with the Java Virtual Machine Specification.
Memory safety is the state of being protected from various software bugs and security vulnerabilities when dealing with memory access, such as buffer overflows and dangling pointers. For example, Java is said to be memory-safe because its runtime error detection checks array bounds and pointer dereferences. In contrast, C and C++ allow arbitrary pointer arithmetic with pointers implemented as direct memory addresses with no provision for bounds checking, and thus are potentially memory-unsafe.
Dalvik is a discontinued process virtual machine (VM) in the Android operating system that executes applications written for Android. Dalvik was an integral part of the Android software stack in the Android versions 4.4 "KitKat" and earlier, which were commonly used on mobile devices such as mobile phones and tablet computers, and more in some devices such as smart TVs and wearables. Dalvik is open-source software, originally written by Dan Bornstein, who named it after the fishing village of Dalvík in Eyjafjörður, Iceland.
Azul Systems, Inc. develops runtimes for executing Java-based applications. Founded in March 2002, Azul Systems is headquartered in Sunnyvale, California.
Splunk Inc. is an American software company based in San Francisco, California, that produces software for searching, monitoring, and analyzing machine-generated data via a web-style interface.
In computer science, region-based memory management is a type of memory management in which each allocated object is assigned to a region. A region, also called a zone, arena, area, or memory context, is a collection of allocated objects that can be efficiently reallocated or deallocated all at once. Like stack allocation, regions facilitate allocation and deallocation of memory with low overhead; but they are more flexible, allowing objects to live longer than the stack frame in which they were allocated. In typical implementations, all objects in a region are allocated in a single contiguous range of memory addresses, similarly to how stack frames are typically allocated.
The garbage-first collector (G1) is a garbage collection algorithm introduced in the Oracle HotSpot Java virtual machine (JVM) 6 and supported from 7 Update 4. It was planned to replace concurrent mark sweep collector (CMS) in JVM 7 and was made default in Java 9.
Android Runtime (ART) is an application runtime environment used by the Android operating system. Replacing Dalvik, the process virtual machine originally used by Android, ART performs the translation of the application's bytecode into native instructions that are later executed by the device's runtime environment.
In the fields of information technology (IT) and systems management, IT operations analytics (ITOA) is an approach or method to retrieve, analyze, and report data for IT operations. ITOA may apply big data analytics to large datasets to produce business insights. In 2014, Gartner predicted its use might increase revenue or reduce costs. By 2017, it predicted that 15% of enterprises will use IT operations analytics technologies.
