The DOI matches its Crossref record; 39 of the 40 references it cites were found in a registry or an index.
Using entropy measures for comparison of software traces
Open accessAbstract
The analysis of execution paths (also known as software traces) collected from a given software product can help in a number of areas including software testing, software maintenance and program comprehension. The lack of a scalable matching algorithm operating on detailed execution paths motivates the search for an alternative solution. This paper proposes the use of word entropies for the classification of software traces. Using a well-studied defective software as an example, we investigate the application of both Shannon and extended entropies (Landsberg-Vedral, Renyi and Tsallis) to the classification of traces related to various software defects. Our study shows that using entropy measures for comparisons gives an efficient and scalable method for comparing traces. The three extended entropies, with parameters chosen to emphasize rare events, all perform similarly and are superior to the Shannon entropy.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb00917.x · Cited by 48,949
Adhi Harmoko, S., M.Komp, Jacquard, J. M., Zuse, K., & Eniac (2005) · Cited by 18,035
Binary Codes capable of currecting deletions, insertions, and reversals
Levenshtein, V. I. (1965) · Soviet physics. Doklady · Cited by 10,358
Possible generalization of Boltzmann-Gibbs statistics
Tsallis, C. (1988) · Journal of Statistical Physics · doi:10.1007/bf01016429 · Cited by 9,589
Grossman, P. (2009) · Discrete Mathematics for Computing · doi:10.1007/978-0-230-37405-8_1 · Cited by 8,834
Case study research: Design and methods
McCorcle, M. D., & Bell, E. L. (1986) · Evaluation and Program Planning · doi:10.1016/0149-7189(86)90052-2 · Cited by 5,884
Empirical evaluation of the tarantula automatic fault-localization technique
Jones, J. A., & Harrold, M. J. (2005) · Proceedings of the 20th IEEE/ACM International Conference on Automated Software Engineering · doi:10.1145/1101908.1101949 · Cited by 1,238
Do, H., Elbaum, S., & Rothermel, G. (2005) · Empirical Software Engineering · doi:10.1007/s10664-005-3861-2 · Cited by 1,146
AnO(ND) difference algorithm and its variations
Myers, E. W. (1986) · Algorithmica · doi:10.1007/bf01840446 · Cited by 893
Research works printed but not linked: 2
- A.V. Miranskyy, M.S. Gittens, N.H. Madhavji, C.A. Taylor, Usage of long execution sequences for test case prioritization, in: Supplemental Proceedings of the 18th IEEE International Symposium on Software Reliability Engineering, 2007.
- Yin, 2003, vol. 5
Cited by
Local Shannon entropy measure with statistical tests for image randomness
Wu, Y., Zhou, Y., Saveriades, G., Agaian, S., Noonan, J. P., & Natarajan, P. (2013) · Information Sciences · doi:10.1016/j.ins.2012.07.049 · Cited by 722
“Shannon entropy [8,47] has been widely used in image encryption for years as a common measure for information and uncertainty [17,21,36,39].”
MethodPreda, V., Dedu, S., & Gheorghe, C. (2015) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2015.05.092 · Cited by 30
Performance testing of LiDAR exploitation software
Varela-González, M., González-Jorge, H., Riveiro, B., & Arias, P. (2012) · Computers & Geosciences · doi:10.1016/j.cageo.2012.12.001 · Cited by 21
CROW: Code Diversification for WebAssembly
Cabrera-Arteaga, J., Floros, O., Pérez, O. L. V., Baudry, B., & Monperrus, M. (2021) · Workshop on Measurements, Attacks, and Defenses for the Web (MADWeb) · doi:10.14722/madweb.2021.23004 · Cited by 21
Multi-Level Formation of Complex Software Systems
Li, H., Hao, L., & Chen, R. (2016) · Entropy · doi:10.3390/e18050178 · Cited by 13
Metadata
- Authors
- Miranskyy, A. V., Davison, M., Reesor, R. M., & Murtaza, S. S.
- Affiliations
- Western University (CA)
- Corresponding author
- Miranskyy, A.V.
- Venue
- Information Sciences
- Publisher
- Elsevier BV
- Published
- 2012-10
- Volume
- 203
- Pages
- 59-72
- ISSN
- 0020-0255 (ISSN-L)
- OpenAlex
- W1970716157
- Cited by
- 27
- References
- 40
- Citations by year
- 2025: 1 · 2023: 1 · 2022: 2 · 2021: 4 · 2020: 1 · 2019: 2 · 2017: 2 · 2016: 7 · 2015: 2 · 2014: 2 · 2013: 1 · 2012: 2
- FWCI
- 6.08
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Information Sciences (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Software › Software Testing and Debugging Techniques
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Keywords
- execution paths, entropy measures, trace classification, software defects, Shannon entropy, Rényi entropy, Tsallis entropy, rare events, software testing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
