Program analysis

In computer science, program analysis is the process of analyzing the behavior of computer programs regarding a property such as correctness, robustness, safety and liveness. Program analysis focuses on two major areas: program optimization and program correctness. The first focuses on improving the program’s performance while reducing the resource usage while the latter focuses on ensuring that the program does what it is supposed to do. Program analysis can be performed without executing the program (static program analysis), during runtime (dynamic program analysis) or in a combination of both.

In computer science, program analysis is the process of analyzing the behavior of computer programs regarding a property such as correctness, robustness, safety and liveness. Program analysis focuses on two major areas: program optimization and program correctness. The first focuses on improving the program’s performance while reducing the resource usage while the latter focuses on ensuring that the program does what it is supposed to do. Program analysis can be performed without executing the program (static program analysis), during runtime (dynamic program analysis) or in a combination of both. ==Static program analysis== In the context of program correctness, static analysis can discover vulnerabilities during the development phase of the program. These vulnerabilities are easier to correct than the ones found during the testing phase since static analysis leads to the root of the vulnerability. Due to many forms of static analysis being computationally undecidable, the mechanisms for performing it may not always terminate with the correct answer. This can result in either false negatives ("no problems found" when the code does in fact have issues) or false positives, or because they may never return an incorrect answer but may also never terminate. Despite these limitations, static analysis can still be valuable: the first type of mechanism might reduce the number of vulnerabilities, while the second can sometimes provide strong assurance of the absence of certain classes of vulnerabilities. Incorrect optimizations are highly undesirable. So, in the context of program optimization, there are two main strategies to handle computationally undecidable analysis: An optimizer that is expected to complete in a relatively short amount of time, such as the optimizer in an optimizing compiler, may use a truncated version of an analysis that is guaranteed to complete in a finite amount of time, and guaranteed to only find correct optimizations. A third-party optimization tool may be implemented in such a way as to never produce an incorrect optimization, but also so that it can, in some situations, continue running indefinitely until it finds one (which may never happen). In this case, the developer using the tool would have to stop the tool and avoid running the tool on that piece of code again (or possibly modify the code to avoid tripping up the tool). However, there is also a third strategy that is sometimes applicable for languages that are not completely specified, such as C. An optimizing compiler is at liberty to generate code that does anything at runtime even crashes if it encounters source code whose semantics are unspecified by the language standard in use. ==Dynamic program analysis== Dynamic analysis can use runtime knowledge of the program to increase the precision of the analysis, while also providing runtime protection, but it can only analyze a single execution of the problem and might degrade the program’s performance due to the runtime checks. ==See also== Automated code review Language-based security Polyvariance Profiling (computer programming) Program verification Termination analysis ==References== ==External links==

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