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Overview of the monitor based verification process as described by Falcone, Havelund and Reger in A Tutorial on Runtime Verification. The broad field of runtime verification methods can be classified by three dimensions: [9] The system can be monitored during the execution itself (online) or after the execution e.g. in form of log analysis ...
In computing, compiler correctness is the branch of computer science that deals with trying to show that a compiler behaves according to its language specification. [ citation needed ] Techniques include developing the compiler using formal methods and using rigorous testing (often called compiler validation) on an existing compiler.
The Tiny C Compiler, TCC, tCc, or TinyCC is an x86, X86-64 and ARM processor C compiler initially written by Fabrice Bellard. It is designed to work for slower computers with little disk space (e.g. on rescue disks). Windows operating system support was added in version 0.9.23 (17 June
Hercules - physical verification; HSIM; HSPICE; IC Compiler - place and route; IC Validator; NANOSIM; OptoCompiler; Physical Compiler; Proteus OPC; Protocol Analyzer (debugging tool) PrimeTime - static timing analysis; Saber; Sentaurus TCAD; Spice explorer; Synphony C Compiler - high-level synthesis; TetraMAX ATPG; VCS; VIP; XA; Yield Explorer ...
Compile and go system; Precompilation; Transcompilation; Recompilation; Notable runtimes; Android Runtime (ART) BEAM (Erlang) Common Language Runtime (CLR) and Mono; CPython and PyPy; crt0 (C target-specific initializer) Java virtual machine (JVM) LuaJIT; Objective-C and Swift's; V8 and Node.js; Zend Engine (PHP) Notable compilers & toolchains ...
Z3 was developed in the Research in Software Engineering (RiSE) group at Microsoft Research Redmond and is targeted at solving problems that arise in software verification and program analysis. Z3 supports arithmetic, fixed-size bit-vectors, extensional arrays, datatypes, uninterpreted functions, and quantifiers .
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MLIR (Multi-Level Intermediate Representation) is a unifying software framework for compiler development. [1] MLIR can make optimal use of a variety of computing platforms such as central processing units (CPUs), graphics processing units (GPUs), data processing units (DPUs), Tensor Processing Units (TPUs), field-programmable gate arrays (FPGAs), artificial intelligence (AI) application ...