In software engineering, code coverage is a percentage measure of the degree to which the source code of a program is executed when a particular test suite is run. A program with high test coverage has more of its source code executed during testing, which suggests it has a lower chance of containing undetected software bugs compared to a program with low test coverage. Many different metrics can be used to calculate test coverage. Some of the most basic are the percentage of program subroutines and the percentage of program statements called during execution of the test suite.
Test coverage was among the first methods invented for systematic software testing. The first published reference was by Miller and Maloney in Communications of the ACM, in 1963.
To measure what percentage of code has been executed by a test suite, one or more coverage criteria are used. These are usually defined as rules or requirements, which a test suite must satisfy.
There are a number of coverage criteria, but the main ones are:
Function coverage - has each function (or subroutine) in the program been called?
Statement coverage - has each statement in the program been executed?
Edge coverage - has every edge in the control-flow graph been executed?
Branch coverage - has each branch (also called the DD-path) of each control structure (such as in if and case statements) been executed? For example, given an if statement, have both the true and false branches been executed? (This is a subset of edge coverage.)
Condition coverage - has each Boolean sub-expression evaluated both to true and false? (Also called predicate coverage.)
For example, consider the following C function:
int foo (int x, int y)
{
int z = 0;
if ((x > 0) && (y > 0))
{
z = x;
}
return z;
}
Assume this function is a part of some bigger program and this program was run with some test suite.
Function coverage will be satisfied if, during this execution, the function foo was called at least once.
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Software testing is the act of examining the artifacts and the behavior of the software under test by validation and verification. Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Test techniques include, but are not necessarily limited to: analyzing the product requirements for completeness and correctness in various contexts like industry perspective, business perspective, feasibility and viability of implementation, usability, performance, security, infrastructure considerations, etc.
Cyclomatic complexity is a software metric used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code. It was developed by Thomas J. McCabe, Sr. in 1976. Cyclomatic complexity is computed using the control-flow graph of the program: the nodes of the graph correspond to indivisible groups of commands of a program, and a directed edge connects two nodes if the second command might be executed immediately after the first command.
In programming and software development, fuzzing or fuzz testing is an automated software testing technique that involves providing invalid, unexpected, or random data as inputs to a computer program. The program is then monitored for exceptions such as crashes, failing built-in code assertions, or potential memory leaks. Typically, fuzzers are used to test programs that take structured inputs. This structure is specified, e.g., in a or protocol and distinguishes valid from invalid input.
Test of VLSI Systems covers theoretical knowledge related to the major algorithms used in VLSI test, and design for test techniques. Basic knowledge related to computer-aided design for test technique
Explores fuzzing as an automated technique to improve program coverage in security testing.
Covers software security testing approaches and coverage metrics.
Explores the roles of testing in VLSI systems, different testing methodologies, cost analysis, factors affecting yield, and the importance of testing in modern technologies.
The pursuit of software security and reliability hinges on the identification and elimination of software vulnerabilities, a challenge compounded by the vast and evolving complexity of modern systems. Fuzzing has emerged as an indispensable technique for b ...
Fuzzing has emerged as the most broadly used testing technique to discover bugs. Effective fuzzers rely on coverage to prioritize inputs that exercise new program areas. Edge-based code coverage of the Program Under Test (PUT) is the most commonly used cov ...
This Replicating Computational Report (RCR) describes (a) our datAFLow fuzzer and (b) how to replicate the results in "datAFLow: Toward a Data-Flow-Guided Fuzzer." Our primary artifact is the datAFLow fuzzer. Unlike traditional coverage-guided greybox fuzz ...