Results 1 to 10 of about 4,221,155 (270)

Predicting Code Coverage without Execution [PDF]

arXiv.org, 2023
Code coverage is a widely used metric for quantifying the extent to which program elements, such as statements or branches, are executed during testing. Calculating code coverage is resource-intensive, requiring code building and execution with additional overhead for the instrumentation.
Tufano, Michele, Chandel, Shubham, Agarwal, Anisha, Sundaresan, Neel, Clement, Colin   +4 more
semanticscholar   +5 more sources

Automatically Assessing and Extending Code Coverage for NPM Packages [PDF]

International Conference/Workshop on Automation of Software Test, 2021
Typical Node.js applications extensively rely on packages hosted in the npm registry. As such packages may be used by thousands of other packages or applications, it is important to assess their code coverage.
Haiyang Sun, Andrea Rosà, Daniele Bonetta, Walter Binder   +3 more
openalex   +3 more sources

Exact Gap Computation for Code Coverage Metrics in ISO-C [PDF]

Electronic Proceedings in Theoretical Computer Science, 2012
Test generation and test data selection are difficult tasks for model based testing. Tests for a program can be meld to a test suite. A lot of research is done to quantify the quality and improve a test suite.
Dirk Richter, Christian Berg
doaj   +4 more sources

IGTG&R: An Intent Analysis-Guided Unit Test Generation and Refinement Framework [PDF]

Entropy
Code coverage-guided unit test generation (CGTG) and large language model-based test generation (LLMTG) are two principal approaches for the generation of unit tests. Each of these approaches has its inherent advantages and drawbacks.
Xiaojian Liu, Yangyang Zhang
doaj   +2 more sources

Machine learning-based dynamic analysis of Android apps with improved code coverage

EURASIP Journal on Information Security, 2019
This paper investigates the impact of code coverage on machine learning-based dynamic analysis of Android malware. In order to maximize the code coverage, dynamic analysis on Android typically requires the generation of events to trigger the user ...
Suleiman Y. Yerima, Mohammed K. Alzaylaee, Sakir Sezer   +2 more
doaj   +2 more sources

Code coverage at Google

Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2019
Code coverage is a measure of the degree to which a test suite exercises a software system. Although coverage is well established in software engineering research, deployment in industry is often inhibited by the perceived usefulness and the computational costs of analyzing coverage at scale.
Marko Ivanković, Goran Petrović, René Just, Gordon Fraser   +3 more
openaire   +2 more sources

Unveiling the Relationship Between Continuous Integration and Code Coverage

IEEE Working Conference on Mining Software Repositories, 2023
Continuous integration (CI) is a software engineering practice that advocates the frequent integration of software through an automated build process.
Unveiling Relationship
openalex   +2 more sources

Optimizing compilation with preservation of structural code coverage metrics to support software testing [PDF]

, 2014
Code-coverage-based testing is a widely-used testing strategy with the aim of providing a meaningful decision criterion for the adequacy of a test suite.
Aho, Ahuja, Allen, Allen, Bhansali, Chilenski, Gross, Harel, Harman, ISO, Jaramillo, Kirner, Lowry, Muchnick, Myers, Organisation IS, Padua, Skiena, Stallman, Stallman, Vilkomir, Wolfram   +21 more
core   +3 more sources

Productive Coverage: Improving the Actionability of Code Coverage

Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice
Code coverage is an intuitive and widely-used test adequacy measure. Established coverage measures treat each test goal (e.g., statement or branch) as equally important, and code-coverage adequacy requires every test goal to be covered.
Marko Ivankovic, Goran Petrovic, Yana Kulizhskaya, Mateusz Lewko, Luka Kalinovcic, Rene Just, Gordon Fraser   +6 more
openaire   +2 more sources

Code Coverage of Adaptive Random Testing [PDF]

IEEE Transactions on Reliability, 2013
Random testing is a basic software testing technique that can be used to assess the software reliability as well as to detect software failures. Adaptive random testing has been proposed to enhance the failure-detection capability of random testing. Previous studies have shown that adaptive random testing can use fewer test cases than random testing to
Chen, Tsong Yueh, Kuo, Fei-Ching, Liu, Huai, Wong, W. Eric   +3 more
core   +8 more sources