Dynamic code analysis

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Dynamic code analysis

The dynamic analysis process can be divided into several steps: When performing the test launch, the program can be executed both on a real and a virtual processor. The source code should be necessarily compiled into an executable file, i. Dynamic analysis can be performed on programs written in various programming languages: There exist special dynamic code analysis utilities intended for program launch and output data gathering and analysis.

Many contemporary development environments already have dynamic analysis tools as one of its modules.

Dynamic code analysis

Such is, for example, the Microsoft Visual Studio 's debugger and profiler. Dynamic analysis tools differ in the way they interact with the program being checked: Dynamic analysis is executed by passing a set of data to the input of the program being checked.

That's why the efficiency of analysis depends directly on the quality and quantity of the input test data. It's them that the fullness of code coverage obtained through the test depends on.

Dynamic testing can provide the following metrics to you: Dynamic testing is most important in the areas where program reliability, response time, and consumed resources are the crucial criteria.

It may be, for instance, a real-time system managing a responsible production area or a database server. Any bug that occurs in these systems may be critical. Dynamic testing can be performed on the principles of white box and black box.

Their only difference is that you have information about the program code in case of the " white box ", while you don't have it in case of the " black box ".

There also exists the so called "gray box" method when you know the program structure but these data are not used in the testing itself. When performing dynamic testing, you also have to minimize the influence of instrumentation on execution of the program being tested temporal characteristics, resources consumed, or program errors.

Dynamic testing allows you to make sure that the product works well or reveals errors showing that the program doesn't work. The second goal of the testing is a more productive one from the viewpoint of quality enhancement, as it doesn't allow you to ignore the program drawbacks.

But if no defects have been revealed during the testing, it doesn't necessarily mean there are no any at all. Another important aspect is whether testing utilities have errors themselves.

A separate task third-party utilities may be used to solve is creation of input test data. Some utilities use the following method: At the next iteration of test launch the utility will generate a new set of input parameters, and son on - until it gets the needed result.

Thus, dynamic analysis has both weak and strong points. The pros of dynamic code analysis are the following: In most cases, generation of false positives is impossible, as error detection occurs right at the moment of its occurrence; thus, the error detected is not a prediction based on the analysis of the program model, but a statement of the fact of its occurrence; Usually you don't need the source code; it allows you to test proprietary code.

These are the cons of dynamic code analysis: Dynamic analysis detects defects only on the route defined by the concrete input data; defects in other code fragments won't be found; It cannot check the correctness of code operation, i. Having its own weak and strong points, the dynamic analysis technology can be used most effectively together with the static analysis technology.I do agree that the static code analysis and dynamic code analysis should be employed together.

Basically, the limitations of the static code analysis can be improved by the advantages of the dynamic code analysis, and vice versa. Static analysis involves no dynamic execution of the software under test and can detect possible defects in an early stage, before running the program.

Static analysis is done after coding and before executing unit tests.

Dynamic program analysis - Wikipedia

Static analysis can be done by a machine to automatically “walk through. Dynamic program analysis is the analysis of computer software that is performed with executing programs built from that software on a real or virtual processor (analysis performed without executing programs is known as static code analysis).

A list of open source tools to perform static or dynamic code analysis on JavaScript programs like JSLint, JSHint, Esprima, Flow, Plato. Some work also for Angular, kaja-net.com, JQuery or Typescript contexts. Static and dynamic code analyses are performed during source code reviews.

Static code analysis is done without executing any of the code; dynamic code analysis relies on studying how the code. Dynamic analysis is the testing and evaluation of a program by executing data in real-time.

The objective is to find errors in a program while it is running, rather than by repeatedly examining the code .

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