Analysis of software performed when running a program
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Program execution
General concepts
Code
Translation
Compiler
Compile time
Optimizing compiler
Intermediate representation (IR)
Execution
Runtime system
Runtime
Executable
Interpreter
Virtual machine
Types of code
Source code
Object code
Bytecode
Machine code
Microcode
Compilation strategies
Ahead-of-time (AOT)
Just-in-time (JIT)
Tracing just-in-time
Compile and go system
Precompilation
Transcompilation
Recompilation
Notable runtimes
Android Runtime (ART)
BEAM
Common Language Runtime (CLR) and Mono
CPython and PyPy
crt0
Java virtual machine (JVM)
LuaJIT
Objective-C and Swift's
V8 and Node.js
Zend Engine
Notable compilers & toolchains
GNU Compiler Collection (GCC)
LLVM and Clang
MSVC
v
t
e
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.
Analysis can focus on different aspects of the software including but not limited to: behavior, test coverage, performance and security.
To be effective, the target program must be executed with sufficient test inputs[1] to address the ranges of possible inputs and outputs. Software testing measures, such as code coverage, and tools such as mutation testing, are used to identify where testing is inadequate.
^Khatiwada, Saket; Tushev, Miroslav; Mahmoud, Anas (2018-01-01). "Just enough semantics: An information theoretic approach for IR-based software bug localization". Information and Software Technology. 93: 45–57. doi:10.1016/j.infsof.2017.08.012.
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