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An advanced static analysis tool that detects potential run-time logic errors in Ada programs. CodeScene: 2023-10-13 (6.3.5) No; proprietary — C, C++, C#, Objective-C Java, Groovy, Scala JavaScript, TypeScript VB.NET Python Swift, Go, PHP, Ruby Behavioral analysis of code. Helps identify, prioritize, and manage technical debt.
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; GNU Compiler Collection (GCC) LLVM and Clang; MSVC
Currently, runtime verification techniques are often presented with various alternative names, such as runtime monitoring, runtime checking, runtime reflection, runtime analysis, dynamic analysis, runtime/dynamic symbolic analysis, trace analysis, log file analysis, etc., all referring to instances of the same high-level concept applied either ...
At runtime, the analysis can be performed online, in order to detect errors on the fly. Alternatively, the instrumentation can simply dump the execution trace for offline analysis. The latter approach is preferred for expensive refined predictive analyses that require random access to the execution trace or take more than linear time.
ESC/Java (and more recently ESC/Java2), the "Extended Static Checker for Java," is a programming tool that attempts to find common run-time errors in Java programs at compile time. [1] The underlying approach used in ESC/Java is referred to as extended static checking , which is a collective name referring to a range of techniques for ...
Java, ColdFusion, Apache, MongoDB Works with any Language supported by the JVM: Performs Application Performance Management and Performance and Root Cause Analysis. Combines APM and Low Level Developer Style Tooling; also includes a debugger and Java, memory, thread, and CPU profilers. Proprietary GlowCode by Electric Software, Inc. Windows
A study in 2012 by VDC Research reported that 28.7% of the embedded software engineers surveyed use static analysis tools and 39.7% expect to use them within 2 years. [9] A study from 2010 found that 60% of the interviewed developers in European research projects made at least use of their basic IDE built-in static analyzers.
The peer code review practice involves manually inspecting source code to examine algorithms, review design, and search for subtle errors that automated tools cannot detect. Although the peer inspection itself cannot be automated, peer code reviews preparation, notification, and tracking can be automated.