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A Java virtual machine (JVM) is a virtual machine that enables a computer to run Java programs as well as programs written in other languages that are also compiled to Java bytecode. The JVM is detailed by a specification that formally describes what is required in a JVM implementation. Having a specification ensures interoperability of Java programs across different implementations so that program authors using the Java Development Kit (JDK) need not worry about idiosyncrasies of the underlying hardware platform.
OCaml is a general-purpose, high-level, multi-paradigm programming language which extends the Caml dialect of ML with object-oriented features. OCaml was created in 1996 by Xavier Leroy, Jérôme Vouillon, Damien Doligez, Didier Rémy, Ascánder Suárez, and others.
In computer science, an interpreter is a computer program that directly executes instructions written in a programming or scripting language, without requiring them previously to have been compiled into a machine language program. An interpreter generally uses one of the following strategies for program execution:
- Parse the source code and perform its behavior directly;
- Translate source code into some efficient intermediate representation or object code and immediately execute that;
- Explicitly execute stored precompiled bytecode made by a compiler and matched with the interpreter's virtual machine.
Bytecode is a form of instruction set designed for efficient execution by a software interpreter. Unlike human-readable source code, bytecodes are compact numeric codes, constants, and references that encode the result of compiler parsing and performing semantic analysis of things like type, scope, and nesting depths of program objects.
In computing, a library is a collection of resources that is leveraged during software development to implement a computer program. Commonly, a library consists of executable code such as compiled functions and classes, or a library can be a collection of source code. A resource library may contain data such as images and text.
In computing, just-in-time (JIT) compilation is compilation during execution of a program rather than before execution. This may consist of source code translation but is more commonly bytecode translation to machine code, which is then executed directly. A system implementing a JIT compiler typically continuously analyses the code being executed and identifies parts of the code where the speedup gained from compilation or recompilation would outweigh the overhead of compiling that code.
In computer programming, specifically when using the imperative programming paradigm, an assertion is a predicate connected to a point in the program, that always should evaluate to true at that point in code execution. Assertions can help a programmer read the code, help a compiler compile it, or help the program detect its own defects.
In computer science, symbolic execution (also symbolic evaluation or symbex) is a means of analyzing a program to determine what inputs cause each part of a program to execute. An interpreter follows the program, assuming symbolic values for inputs rather than obtaining actual inputs as normal execution of the program would. It thus arrives at expressions in terms of those symbols for expressions and variables in the program, and constraints in terms of those symbols for the possible outcomes of each conditional branch. Finally, the possible inputs that trigger a branch can be determined by solving the constraints.
In computer programming, a runtime system or runtime environment is a sub-system that exists in the computer where a program is created, as well as in the computers where the program is intended to be run. The name comes from the compile time and runtime division from compiled languages, which similarly distinguishes the computer processes involved in the creation of a program (compilation) and its execution in the target machine.
Jazelle DBX is an extension that allows some ARM processors to execute Java bytecode in hardware as a third execution state alongside the existing ARM and Thumb modes. Jazelle functionality was specified in the ARMv5TEJ architecture and the first processor with Jazelle technology was the ARM926EJ-S. Jazelle is denoted by a "J" appended to the CPU name, except for post-v5 cores where it is required for architecture conformance.
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.
Runtime verification is a computing system analysis and execution approach based on extracting information from a running system and using it to detect and possibly react to observed behaviors satisfying or violating certain properties. Some very particular properties, such as datarace and deadlock freedom, are typically desired to be satisfied by all systems and may be best implemented algorithmically. Other properties can be more conveniently captured as formal specifications. Runtime verification specifications are typically expressed in trace predicate formalisms, such as finite-state machines, regular expressions, context-free patterns, linear temporal logics, etc., or extensions of these. This allows for a less ad-hoc approach than normal testing. However, any mechanism for monitoring an executing system is considered runtime verification, including verifying against test oracles and reference implementations. When formal requirements specifications are provided, monitors are synthesized from them and infused within the system by means of instrumentation. Runtime verification can be used for many purposes, such as security or safety policy monitoring, debugging, testing, verification, validation, profiling, fault protection, behavior modification, etc. Runtime verification avoids the complexity of traditional formal verification techniques, such as model checking and theorem proving, by analyzing only one or a few execution traces and by working directly with the actual system, thus scaling up relatively well and giving more confidence in the results of the analysis, at the expense of less coverage. Moreover, through its reflective capabilities runtime verification can be made an integral part of the target system, monitoring and guiding its execution during deployment.
Dynamic program analysis is the act of analyzing software that involves executing a program – as opposed to static program analysis, which does not execute it.
Thread Level Speculation (TLS), also known as Speculative Multi-threading, or Speculative Parallelization, is a technique to speculatively execute a section of computer code that is anticipated to be executed later in parallel with the normal execution on a separate independent thread. Such a speculative thread may need to make assumptions about the values of input variables. If these prove to be invalid, then the portions of the speculative thread that rely on these input variables will need to be discarded and squashed. If the assumptions are correct the program can complete in a shorter time provided the thread was able to be scheduled efficiently.
In computer science, ahead-of-time compilation is the act of compiling an (often) higher-level programming language into an (often) lower-level language before execution of a program, usually at build-time, to reduce the amount of work needed to be performed at run time.
The Da Vinci Machine, also called the Multi Language Virtual Machine, was a Sun Microsystems project aiming to prototype the extension of the Java Virtual Machine (JVM) to add support for dynamic languages.
Concolic testing is a hybrid software verification technique that performs symbolic execution, a classical technique that treats program variables as symbolic variables, along a concrete execution path. Symbolic execution is used in conjunction with an automated theorem prover or constraint solver based on constraint logic programming to generate new concrete inputs with the aim of maximizing code coverage. Its main focus is finding bugs in real-world software, rather than demonstrating program correctness.
A high-level language computer architecture (HLLCA) is a computer architecture designed to be targeted by a specific high-level programming language (HLL), rather than the architecture being dictated by hardware considerations. It is accordingly also termed language-directed computer design, coined in McKeeman (1967) and primarily used in the 1960s and 1970s. HLLCAs were popular in the 1960s and 1970s, but largely disappeared in the 1980s. This followed the dramatic failure of the Intel 432 (1981) and the emergence of optimizing compilers and reduced instruction set computer (RISC) architectures and RISC-like complex instruction set computer (CISC) architectures, and the later development of just-in-time compilation (JIT) for HLLs. A detailed survey and critique can be found in Ditzel & Patterson (1980).
Differential testing, also known as differential fuzzing, is a software testing technique that detect bugs, by providing the same input to a series of similar applications, and observing differences in their execution. Differential testing complements traditional software testing because it is well-suited to find semantic or logic bugs that do not exhibit explicit erroneous behaviors like crashes or assertion failures. Differential testing is also called back-to-back testing.
Grigore Roșu is a computer science professor at the University of Illinois at Urbana-Champaign and a researcher in the Information Trust Institute. He is known for his contributions in runtime verification, the K framework, matching logic, and automated coinduction.
References
- Willem Visser, Corina S. Păsăreanu, Sarfraz Khurshid. Test Input Generation with Java PathFinder. In: George S. Avrunin, Gregg Rothermel (Eds.): Proceedings of the ACM/SIGSOFT International Symposium on Software Testing and Analysis 2004. ACM Press, 2004. ISBN 1-58113-820-2.
- Willem Visser, Klaus Havelund, Guillaume Brat, Seungjoon Park, Flavio Lerda, Model Checking Programs, Automated Software Engineering 10(2), 2003.
- Klaus Havelund, Willem Visser, Program Model Checking as a New Trend, STTT 4(1), 2002.
- Klaus Havelund, Thomas Pressburger, Model Checking Java Programs using Java PathFinder, STTT 2(4), 2000.