Shadow Symbolic Execution for Testing Software Patches

Kuchta, Tomasz; Palikareva, Hristina; Cadar, Cristian

doi:10.1145/3208952

Cited by 19 publications

(17 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To answer RQs 1-3 we used the C programs of GNU Coreutils 1 , used in many existing studies [26], [27], [28]. GNU Coreutils is a collection of text, file, and shell utility programs widely used in Unix systems.…”

Section: Program Versions Usedmentioning

confidence: 99%

“…We selected these commits to validate the fault revelation ability of relevant mutants. Since we approximate relevant mutants, we needed commits where 1 https://www.gnu.org/software/coreutils/ 2 Measured with cloc (http://cloc.sourceforge.net/) [26]. Among these faults, two were discarded due to technical difficulties in compiling the code (the build system uses very old versions of the build tools).…”

Section: Program Versions Usedmentioning

confidence: 99%

“…To establish such a mapping in the case of C programs, we unify the commit modifications into a single program, as done in the literature [26], and apply any standard (unmodified) mutation tool to generate the mutants. The code unification of the commit modification is done through annotation that has no side-effect.…”

Section: E Mutation Mapping Across Versionsmentioning

confidence: 99%

“…The annotations are manually inserted in the program, according the semantics presented in previous studies [26].…”

Section: E Mutation Mapping Across Versionsmentioning

confidence: 99%

See 3 more Smart Citations

Commit-Aware Mutation Testing

Laurent

Ojdanić

et al. 2020

2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)

View full text Add to dashboard Cite

In Continuous Integration, developers want to know how well they have tested their changes. Unfortunately, in these cases, the use of mutation testing is suboptimal since mutants affect the entire set of program behaviours and not the changed ones. Thus, the extent to which mutation testing can be used to test committed changes is questionable. To deal with this issue, we define commit-relevant mutants; a set of mutants that affect the changed program behaviours and represent the commit-relevant test requirements. We identify such mutants in a controlled way, and check their relationship with traditional mutation score (score based on the entire set of mutants or on the mutants located on the commits). We conduct experiments in both C and Java, using 83 commits, 2,253,610 mutants from 25 projects. Our findings reveal that there is a relatively weak correlation (Kendall/Pearson 0.15-0.4) between the sought (commit-relevant) and traditional mutation scores, indicating the need for a commit-aware test assessment metric. Our analysis also shows that traditional mutation is far from the envisioned case as it loses approximately 50%-60% of the commit-relevant mutants when analysing 5-25 mutants. More importantly, our results demonstrate that traditional mutation has approximately 30% lower chances of revealing commit-introducing faults than commit-aware mutation testing.

show abstract

Section: Program Versions Usedmentioning

confidence: 99%

Section: Program Versions Usedmentioning

confidence: 99%

Section: E Mutation Mapping Across Versionsmentioning

confidence: 99%

“…The annotations are manually inserted in the program, according the semantics presented in previous studies [26].…”

Section: E Mutation Mapping Across Versionsmentioning

confidence: 99%

See 2 more Smart Citations

Commit-Aware Mutation Testing

Laurent

Ojdanić

et al. 2020

2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)

View full text Add to dashboard Cite

show abstract

“…GSON#44CAD04 17 : This commit allows Gson to deserialize a number represented as a string. Listing 9 shows the relevant part of the test generated by DCI SBAM P L , based on testNumberDeserialization of PrimitiveTest as a seed.…”

Section: Rq4: How Do Human and Generated Tests That Detect Behavioralmentioning

confidence: 99%

An approach and benchmark to detect behavioral changes of commits in continuous integration

et al. 2020

View full text Add to dashboard Cite

When a developer pushes a change to an application's codebase, a good practice is to have a test case specifying this behavioral change. Thanks to continuous integration (CI), the test is run on subsequent commits to check that they do no introduce a regression for that behavior.In this paper, we propose an approach that detects behavioral changes in commits. As input, it takes a program, its test suite, and a commit. Its output is a set of test methods that capture the behavioral difference between the pre-commit and postcommit versions of the program. We call our approach DCI (Detecting behavioral changes in CI). It works by generating variations of the existing test cases through (i) assertion amplification and (ii) a search-based exploration of the input space.We evaluate our approach on a curated set of 60 commits from 6 open source Java projects. To our knowledge, this is the first ever curated dataset of real-world behavioral changes. Our evaluation shows that DCI is able to generate test methods that detect behavioral changes. Our approach is fully automated and can be integrated into current development processes. The main limitations are that it targets unit tests B. Danglot Inria Lille -Nord Europe

show abstract

TDCT: Target-Driven Concolic Testing Using Extended Units by Calculating Function Relevance

Fan

Wang

et al. 2022

Algorithms and Architectures for Parallel Processing

View full text Add to dashboard Cite

Shadow Symbolic Execution for Testing Software Patches

Cited by 19 publications

References 48 publications

Commit-Aware Mutation Testing

Commit-Aware Mutation Testing

An approach and benchmark to detect behavioral changes of commits in continuous integration

TDCT: Target-Driven Concolic Testing Using Extended Units by Calculating Function Relevance

Contact Info

Product

Resources

About