FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2102742419> ?p ?o ?g. }

• W2102742419 endingPage "624" @default.
• W2102742419 startingPage "608" @default.
• W2102742419 abstract "The empirical assessment of test techniques plays an important role in software testing research. One common practice is to seed faults in subject software, either manually or by using a program that generates all possible mutants based on a set of mutation operators. The latter allows the systematic, repeatable seeding of large numbers of faults, thus facilitating the statistical analysis of fault detection effectiveness of test suites; however, we do not know whether empirical results obtained this way lead to valid, representative conclusions. Focusing on four common control and data flow criteria (block, decision, C-use, and P-use), this paper investigates this important issue based on a middle size industrial program with a comprehensive pool of test cases and known faults. Based on the data available thus far, the results are very consistent across the investigated criteria as they show that the use of mutation operators is yielding trustworthy results: generated mutants can be used to predict the detection effectiveness of real faults. Applying such a mutation analysis, we then investigate the relative cost and effectiveness of the above-mentioned criteria by revisiting fundamental questions regarding the relationships between fault detection, test suite size, and control/data flow coverage. Although such questions have been partially investigated in previous studies, we can use a large number of mutants, which helps decrease the impact of random variation in our analysis and allows us to use a different analysis approach. Our results are then; compared with published studies, plausible reasons for the differences are provided, and the research leads us to suggest a way to tune the mutation analysis process to possible differences in fault detection probabilities in a specific environment" @default.
• W2102742419 created "2016-06-24" @default.
• W2102742419 creator A5007057846 @default.
• W2102742419 creator A5026464816 @default.
• W2102742419 creator A5050825479 @default.
• W2102742419 creator A5078533117 @default.
• W2102742419 date "2006-08-01" @default.
• W2102742419 modified "2023-10-04" @default.
• W2102742419 title "Using Mutation Analysis for Assessing and Comparing Testing Coverage Criteria" @default.
• W2102742419 cites W1501076421 @default.
• W2102742419 cites W1560412976 @default.
• W2102742419 cites W1985378987 @default.
• W2102742419 cites W1985551847 @default.
• W2102742419 cites W1996596150 @default.
• W2102742419 cites W2028536280 @default.
• W2102742419 cites W2033140592 @default.
• W2102742419 cites W2049695835 @default.
• W2102742419 cites W2053003592 @default.
• W2102742419 cites W2099441126 @default.
• W2102742419 cites W2102634733 @default.
• W2102742419 cites W2108557864 @default.
• W2102742419 cites W2110068396 @default.
• W2102742419 cites W2111068183 @default.
• W2102742419 cites W2121084350 @default.
• W2102742419 cites W2124300773 @default.
• W2102742419 cites W2125814238 @default.
• W2102742419 cites W2126627822 @default.
• W2102742419 cites W2128260238 @default.
• W2102742419 cites W2146408397 @default.
• W2102742419 cites W2170913273 @default.
• W2102742419 cites W4229772528 @default.
• W2102742419 cites W4236200536 @default.
• W2102742419 cites W4243258316 @default.
• W2102742419 cites W4256285596 @default.
• W2102742419 cites W2112687552 @default.
• W2102742419 doi "https://doi.org/10.1109/tse.2006.83" @default.
• W2102742419 hasPublicationYear "2006" @default.
• W2102742419 type Work @default.
• W2102742419 sameAs 2102742419 @default.
• W2102742419 citedByCount "418" @default.
• W2102742419 countsByYear W21027424192012 @default.
• W2102742419 countsByYear W21027424192013 @default.
• W2102742419 countsByYear W21027424192014 @default.
• W2102742419 countsByYear W21027424192015 @default.
• W2102742419 countsByYear W21027424192016 @default.
• W2102742419 countsByYear W21027424192017 @default.
• W2102742419 countsByYear W21027424192018 @default.
• W2102742419 countsByYear W21027424192019 @default.
• W2102742419 countsByYear W21027424192020 @default.
• W2102742419 countsByYear W21027424192021 @default.
• W2102742419 countsByYear W21027424192022 @default.
• W2102742419 countsByYear W21027424192023 @default.
• W2102742419 crossrefType "journal-article" @default.
• W2102742419 hasAuthorship W2102742419A5007057846 @default.
• W2102742419 hasAuthorship W2102742419A5026464816 @default.
• W2102742419 hasAuthorship W2102742419A5050825479 @default.
• W2102742419 hasAuthorship W2102742419A5078533117 @default.
• W2102742419 hasConcept C104317684 @default.
• W2102742419 hasConcept C105795698 @default.
• W2102742419 hasConcept C106159264 @default.
• W2102742419 hasConcept C111919701 @default.
• W2102742419 hasConcept C119857082 @default.
• W2102742419 hasConcept C120936955 @default.
• W2102742419 hasConcept C124101348 @default.
• W2102742419 hasConcept C127413603 @default.
• W2102742419 hasConcept C128942645 @default.
• W2102742419 hasConcept C151552104 @default.
• W2102742419 hasConcept C152877465 @default.
• W2102742419 hasConcept C160191386 @default.
• W2102742419 hasConcept C163565370 @default.
• W2102742419 hasConcept C177264268 @default.
• W2102742419 hasConcept C185592680 @default.
• W2102742419 hasConcept C199360897 @default.
• W2102742419 hasConcept C200601418 @default.
• W2102742419 hasConcept C2777904410 @default.
• W2102742419 hasConcept C33923547 @default.
• W2102742419 hasConcept C41008148 @default.
• W2102742419 hasConcept C501734568 @default.
• W2102742419 hasConcept C53942775 @default.
• W2102742419 hasConcept C55493867 @default.
• W2102742419 hasConcept C97686452 @default.
• W2102742419 hasConcept C98045186 @default.
• W2102742419 hasConceptScore W2102742419C104317684 @default.
• W2102742419 hasConceptScore W2102742419C105795698 @default.
• W2102742419 hasConceptScore W2102742419C106159264 @default.
• W2102742419 hasConceptScore W2102742419C111919701 @default.
• W2102742419 hasConceptScore W2102742419C119857082 @default.
• W2102742419 hasConceptScore W2102742419C120936955 @default.
• W2102742419 hasConceptScore W2102742419C124101348 @default.
• W2102742419 hasConceptScore W2102742419C127413603 @default.
• W2102742419 hasConceptScore W2102742419C128942645 @default.
• W2102742419 hasConceptScore W2102742419C151552104 @default.
• W2102742419 hasConceptScore W2102742419C152877465 @default.
• W2102742419 hasConceptScore W2102742419C160191386 @default.
• W2102742419 hasConceptScore W2102742419C163565370 @default.
• W2102742419 hasConceptScore W2102742419C177264268 @default.
• W2102742419 hasConceptScore W2102742419C185592680 @default.
• W2102742419 hasConceptScore W2102742419C199360897 @default.

• next