Evaluating how developers use general-purpose web-search for code retrieval
Open accessAbstract
Search is an integral part of a software development process. Developers often use search engines to look for information during development, including reusable code snippets, API understanding, and reference examples. Developers tend to prefer general-purpose search engines like Google, which are often not optimized for code related documents and use search strategies and ranking techniques that are more optimized for generic, non-code related information.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Developers spend a significant amount of time searching and foraging for information and organizing and digesting the information they find.
“Consequently, developers spend a significant amount of time searching and foraging for the information they need and organizing and digesting the information they find [30,31,34,44,48,57].”
From Using an LLM to Help With Code Understanding (2024) · cites this paper as [57]
Cites
Analysis of a very large web search engine query log
Silverstein, C. D., Marais, H., Henzinger, M. R., & Moricz, M. (1999) · ACM SIGIR Forum · doi:10.1145/331403.331405 · Cited by 1,153 · see citing works
(2009) · doi:10.1145/1518701.1518944 · Cited by 447 · see citing works
Thummalapenta, S., & Xie, T. (2007) · doi:10.1145/1321631.1321663 · Cited by 394 · see citing works
Using structural context to recommend source code examples
Holmes, R., & Murphy, G. C. (2005) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/1062455.1062491 · Cited by 382 · see citing works
McMillan, C., Grechanik, M., Poshyvanyk, D., Xie, Q., & Fu, C. (2011) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/1985793.1985809 · Cited by 313 · see citing works
Reiss, S. P. (2009) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1109/icse.2009.5070525 · Cited by 309 · see citing works
Are deep neural networks the best choice for modeling source code?
Hellendoorn, V. J., & Devanbu, P. (2017) · Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering · doi:10.1145/3106237.3106290 · Cited by 292 · see citing works
How developers search for code: a case study
Sadowski, C., Stolee, K. T., & Elbaum, S. G. (2015) · doi:10.1145/2786805.2786855 · Cited by 243 · see citing works
Self-citationSourcerer: mining and searching internet-scale software repositories
Linstead, E. J., Bajracharya, S. K., Ngo, T. C., Rigor, P., Lopes, C. V., & Baldi, P. (2008) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-008-0118-x · Cited by 237 · see citing works
Supporting reuse by delivering task-relevant and personalized information
Ye, Y., & Fischer, G. (2002) · Proceedings/Proceedings - International Conference on Software Engineering · doi:10.1145/581339.581402 · Cited by 236 · see citing works
Bajracharya, S. K., Ngo, T. C., Linstead, E. J., Dou, Y., Rigor, P., Baldi, P., & Lopes, C. V. (2006) · Companion to the ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA Companion) · doi:10.1145/1176617.1176671 · Cited by 220 · see citing works
What do developers search for on the web?
Xia, X., Bao, L., Lo, D., Kochhar, P. S., Hassan, A. E., & Xing, Z. (2017) · Empirical Software Engineering · doi:10.1007/s10664-017-9514-4 · Cited by 174 · see citing works
Automatic Query Reformulations for Text Retrieval in Software Engineering
Haiduc, S., Bavota, G., Marcus, A., Oliveto, R., Lucia, A. D., & Menzies, T. (2013) · Cited by 165 · see citing works
Raghothaman, M., Wei, Y., & Hamadi, Y. (2016) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/2884781.2884808 · Cited by 165 · see citing works
Solving the Search for Source Code
Stolee, K. T., Elbaum, S. G., & Dobos, D. (2014) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/2581377 · Cited by 122 · see citing works
Self-citationHow Well Do Search Engines Support Code Retrieval on the Web?
Sim, S. E., Umarji, M., Ratanotayanon, S., & Lopes, C. V. (2011) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/2063239.2063243 · Cited by 99 · see citing works
Analyzing and mining a code search engine usage log
Bajracharya, S. K., & Lopes, C. V. (2012) · Empirical Software Engineering · doi:10.1007/s10664-010-9144-6 · Cited by 90 · see citing works
Learning to rank code examples for code search engines
Niu, H., Keivanloo, I., & Zou, Y. (2016) · Empirical Software Engineering · doi:10.1007/s10664-015-9421-5 · Cited by 86 · see citing works
Using an information retrieval system to retrieve source code samples
Sindhgatta, R. (2006) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/1134285.1134448 · Cited by 57 · see citing works
Thesaurus-based automatic query expansion for interface-driven code search
Lemos, O. A. L., de Paula, A. C., Zanichelli, F. C., & Lopes, C. V. (2014) · International Conference on Mining Software Repositories (MSR) · doi:10.1145/2597073.2597087 · Cited by 54 · see citing works
Lemos, O. A. L., Bajracharya, S. K., & Ossher, J. (2007) · Companion to the ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA Companion) · doi:10.1145/1297846.1297944 · Cited by 44 · see citing works
An exploratory study on reuse at google
Bauer, V., Eckhardt, J., Hauptmann, B., & Klimek, M. (2014) · doi:10.1145/2593850.2593854 · Cited by 28 · see citing works
Applying a semantic layer in a source code search tool
Dur�ão, F. A., Vanderlei, T. A., de Almeida, E. S., & Meira, S. R. D. L. (2008) · ACM Symposium on Applied Computing · doi:10.1145/1363686.1363952 · Cited by 27 · see citing works
Understanding the impact of support for iteration on code search
Martie, L., van der Hoek, A., & Kwak, T. (2017) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3106237.3106293 · Cited by 26 · see citing works
Hucka, M., & Graham, M. J. (2018) · Journal of Systems and Software · doi:10.1016/j.jss.2018.03.047 · Cited by 21 · see citing works
Web usage patterns of developers
Corley, C. S., Lois, F., & Quezada, S. (2015) · 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME) · doi:10.1109/icsm.2015.7332489 · Cited by 10 · see citing works
Self-citationMost popular programming languages 2019
Stropkovics, K. (2019) · Cited by 10 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Using an LLM to Help With Code Understanding
Nam, D., Macvean, A., Hellendoorn, V., Vasilescu, B., & Myers, B. (2024) · Proceedings of the IEEE/ACM 46th International Conference on Software Engineering · doi:10.1145/3597503.3639187 · Cited by 345 · see citing works
“Researchers have also studied challenges developers face [14, 23, 32, 58, 72, 74], including difficulties in effective search-query writing and information foraging, and built tools to support developers overcome such challenges [3, 42, 52].”
BackgroundKabir, S., Udo-Imeh, D. N., Kou, B., & Zhang, T. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642596 · Cited by 160 · see citing works
Improving Code Search with Co-Attentive Representation Learning
Shuai, J., Xu, L., Liu, C., Yan, M. L., Xia, X., & Lei, Y. (2020) · International Conference on Program Comprehension · doi:10.1145/3387904.3389269 · Cited by 123 · see citing works
Retrieval Augmented Code Generation and Summarization
Parvez, M. R., Ahmad, W., Chakraborty, S., Ray, B., & Chang, K.-W. (2021) · Findings of the Association for Computational Linguistics: EMNLP 2021 · doi:10.18653/v1/2021.findings-emnlp.232 · Cited by 141 · see citing works
Self-citationOpportunities and Challenges in Code Search Tools
Liu, C., Xia, X., Lo, D., Gao, C., Yang, X., & Grundy, J. (2021) · ACM Computing Surveys · doi:10.1145/3480027 · Cited by 91 · see citing works
Code Search: A Survey of Techniques for Finding Code
Grazia, L. D., & Pradel, M. (2022) · ACM Computing Surveys · doi:10.1145/3565971 · Cited by 68 · see citing works
Using bug descriptions to reformulate queries during text-retrieval-based bug localization
Chaparro, O., Florez, J. M., & Marcus, A. (2019) · Empirical Software Engineering · doi:10.1007/s10664-018-9672-z · Cited by 50 · see citing works
Multimodal Representation for Neural Code Search
Gu, J. H., Chen, Z., & Monperrus, M. (2021) · IEEE International Conference on Software Maintenance (ICSM) · doi:10.1109/icsme52107.2021.00049 · Cited by 49 · see citing works
Automatic query reformulation for code search using crowdsourced knowledge
Rahman, M. M., Roy, C. K., & Lo, D. (2019) · Empirical Software Engineering · doi:10.1007/s10664-018-9671-0 · Cited by 46 · see citing works
Self-citationChatbot4QR: Interactive Query Refinement for Technical Question Retrieval
Zhang, N., Huang, Q., Xia, X., Zou, Y., Lo, D., & Xing, Z. (2020) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2020.3016006 · Cited by 45 · see citing works
Googling for Software Development: What Developers Search For and What They Find
Hora, A. (2021) · International Conference on Mining Software Repositories (MSR) · doi:10.1109/msr52588.2021.00044 · Cited by 39 · see citing works
I Know What You Are Searching for: Code Snippet Recommendation from Stack Overflow Posts
Gao, Z., Xia, X., Lo, D., Grundy, J., Zhang, X., & Xing, Z. (2022) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3550150 · Cited by 37 · see citing works
CodeMatcher: Searching Code Based on Sequential Semantics of Important Query Words
Liu, C., Xia, X., Lo, D., Liu, Z., Hassan, A. E., & Li, S. (2021) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3465403 · Cited by 42 · see citing works
Exploring Web Search Engines to Find Architectural Knowledge
Soliman, M., Wiese, M., Li, Y., Riebisch, M., & Avgeriou, P. (2021) · IEEE International Conference on Software Architecture (ICSA) · doi:10.1109/icsa51549.2021.00023 · Cited by 22 · see citing works
Guided pattern mining for API misuse detection by change-based code analysis
Nielebock, S., Heumüller, R., Schott, K. M., & Ortmeier, F. (2021) · Automated Software Engineering · doi:10.1007/s10515-021-00294-x · Cited by 19 · see citing works
Analyzing Web Search Behavior for Software Engineering Tasks
Rao, N., Bansal, C., Zimmermann, T., Awadallah, A. H., & Nagappan, N. (2020) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata50022.2020.9378083 · Cited by 19 · see citing works
How Graduate Computing Students Search When Using an Unfamiliar Programming Language
Bai, G. R., Kayan, J., & Stolee, K. T. (2020) · International Conference on Program Comprehension · doi:10.1145/3387904.3389274 · Cited by 17 · see citing works
Self-citationAddressing Compiler Errors: Stack Overflow or Large Language Models?Preprint
Widjojo, P., & Treude, C. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4529345 · Cited by 16 · see citing works
Debugging with Stack Overflow: Web Search Behavior in Novice and Expert Programmers
Li, A. D. R., Endres, M., & Weimer, W. R. (2022) · IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET) · doi:10.1109/icse-seet55299.2022.9794240 · Cited by 14 · see citing works
Fischer, F., Stachelscheid, Y., & Großklags, J. (2021) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/3460120.3484763 · Cited by 13 · see citing works
Search4Code: Code Search Intent Classification Using Weak Supervision
Rao, N., Bansal, C., & Guan, J. (2021) · International Conference on Mining Software Repositories (MSR) · doi:10.1109/msr52588.2021.00077 · Cited by 15 · see citing works
Characterizing top ranked code examples in Google
Hora, A. (2021) · Journal of Systems and Software · doi:10.1016/j.jss.2021.110971 · Cited by 11 · see citing works
How to formulate specific how-to questions in software development?
Liu, M., Peng, X., Marcus, A., Treude, C., Xie, J., Xu, H., & Yang, Y. (2022) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3540250.3549160 · Cited by 12 · see citing works
Supporting Code Search with Context-Aware, Analytics-Driven, Effective Query Reformulation
Rahman, M. M. (2019) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1109/icse-companion.2019.00088 · Cited by 11 · see citing works
Self-citationMartins, M. D. R., & Gerosa, M. A. (2020) · Brazilian Symposium on Software Engineering · doi:10.1145/3422392.3422462 · Cited by 10 · see citing works
How Do Developers Search for Architectural Information? An Industrial Survey
de Dieu, M. J., Liang, P., & Shahin, M. (2022) · IEEE International Conference on Software Architecture (ICSA) · doi:10.1109/icsa53651.2022.00014 · Cited by 9 · see citing works
Toward Optimal Selection of Information Retrieval Models for Software Engineering Tasks
Rahman, M. M., Chakraborty, S., Kaiser, G. E., & Ray, B. (2019) · IEEE Working Conference on Source Code Analysis and Manipulation · doi:10.1109/scam.2019.00022 · Cited by 8 · see citing works
Self-citationDebugging with stack overflow: web search behavior in novice and expert programmers
Li, A., Endres, M., & Weimer, W. (2022) · Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Software Engineering Education and Training · doi:10.1145/3510456.3514147 · Cited by 8 · see citing works
Automated Code Editing With Search-Generate-Modify
Liu, C., Cetin, P., Patodia, Y., Ray, B., Chakraborty, S., & Ding, Y. (2024) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2024.3376387 · Cited by 12 · see citing works
Self-citationSemantic code search using Code2Vec: A bag-of-paths model
Arumugam, L. (2020) · UWSpace (University of Waterloo) · Cited by 8 · see citing works
Developers’ information seeking in Question & Answer websites through a gender lens
Sedhain, A., Diwanji, V., Solomon, H., Leon, S., & Kuttal, S. K. (2024) · Journal of Computer Languages · doi:10.1016/j.cola.2024.101267 · Cited by 7 · see citing works
DiffTech: Differencing Similar Technologies From Crowd-Scale Comparison Discussions
Wang, H., Chen, C., Xing, Z., & Grundy, J. (2021) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2021.3059885 · Cited by 7 · see citing works
Code search engines for the next generation
Kessel, M., & Atkinson, C. (2024) · Journal of Systems and Software · doi:10.1016/j.jss.2024.112065 · Cited by 7 · see citing works
Simplifying Deep-Learning-Based Model for Code Search.Preprint
Liu, C., Xia, X., Lo, D., Liu, Z., Hassan, A. E., & Li, S. (2020) · arXiv (Cornell University) · Cited by 7 · see citing works
SE Factual Knowledge in Frozen Giant Code Model: A Study on FQN and Its Retrieval
Huang, Q. Y., Liao, D., Xing, Z., Yuan, Z., Lu, Q., Xu, X., & Lu, J. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2024.3436883 · Cited by 8 · see citing works
An Empirical Study of Software Exceptions in the Field using Search Logs
Hassan, F., Bansal, C., Nagappan, N., Zimmermann, T., & Awadallah, A. H. (2020) · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement · doi:10.1145/3382494.3410692 · Cited by 6 · see citing works
Reusable Component Retrieval: A Semantic Search Approach for Low-Resource Languages
Bibi, N., Rana, T. A., Maqbool, A., Alkhalifah, T., Khan, W. Z., Bashir, A. K., & Zikria, Y. B. (2022) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3564604 · Cited by 6 · see citing works
10 Years Later: Revisiting How Developers Search for Code
Stolee, K. T., Welp, T., Sadowski, C., & Elbaum, S. G. (2025) · Proceedings of the ACM on software engineering. · doi:10.1145/3715774 · Cited by 5 · see citing works
Self-citationUnderstanding the Role of Images on Stack Overflow
Wang, D., Xiao, T., Treude, C., Kula, R. G., Hata, H., & Kamei, Y. (2023) · International Conference on Mining Software Repositories (MSR) · doi:10.1109/msr59073.2023.00059 · Cited by 5 · see citing works
Robbes, R., Lungu, M. F., & Janes, A. (2019) · IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER) · doi:10.1109/icse-nier.2019.00033 · Cited by 5 · see citing works
How do Programmers Use the Internet? Discovering Domain Knowledge from Browsing and Coding Behaviors
Watanabe, K., Matsuda, Y., Nakamura, Y., Arakawa, Y., & Ishimaru, S. (2022) · IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) · doi:10.1109/ithings-greencom-cpscom-smartdata-cybermatics55523.2022.00034 · Cited by 4 · see citing works
An Empirical Study on Code Search Pre-trained Models: Academic Progresses vs. Industry Requirements
Chi, K., Li, C., Ge, J., & Luo, B. (2024) · Asia-Pacific Symposium on Internetware · doi:10.1145/3671016.3672580 · Cited by 3 · see citing works
A Privacy-Aware Browser Extension to Track User Search Behavior for Programming Course Supplement
Makhlouf, J., Arakawa, Y., & Watanabe, K. (2022) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-030-94822-1_51 · Cited by 3 · see citing works
Using clarification questions to improve software developers’ Web search
Imran, M. M., & Damevski, K. (2022) · Information and Software Technology · doi:10.1016/j.infsof.2022.107021 · Cited by 2 · see citing works
Supporting Source Code Search with Context-Aware and Semantics-Driven Query Reformulation
Rahman, M. M. (2019) · HARVEST (University of Saskatchewan) · Cited by 2 · see citing works
Self-citationA Survey of the Full Process of Code Search Based on Deep Learning
Fang, M., Hu, H., Hu, F., & Liu, J. (2025) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.70277 · Cited by 1 · see citing works
Slicing Based Code Recommendation for Type Based Instance Retrieval
Sun, R., Liu, H., & Li, L. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-22888-0_11 · Cited by 1 · see citing works
Dantas, C. E. C., & Maia, M. D. A. (2021) · IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW) · doi:10.1109/asew52652.2021.00034 · Cited by 1 · see citing works
Analyzing Web Search Strategy of Software Developers to Modify Source Codes
Nakasai, K., Tsunoda, M., & Matsumoto, K. (2021) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.2021mpl0004 · Cited by 1 · see citing works
Understanding Query Intention in Search Queries of Learners in Blended Learning Environments
Natarajan, V., & Shanmuganathan, S. (2022) · IEEE International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA) · doi:10.1109/icccmla56841.2022.9989024 · Cited by 1 · see citing works
تأثير استخلاص الشفرة البرمجية من الإنترنت على مهارات وطرق وسلوك المبرمج
Mohammed, A. O. M., Abdelnabi, Z. A., & Abdalla, A. (2021) · AL-MUKHTAR JOURNAL OF SCIENCES · doi:10.54172/mjsc.v36i2.66
Web search of software developers—Characteristics and tips
Szabó, B. (2022) · Frontiers in Education · doi:10.3389/feduc.2022.908712
Code Search Method Based on Multimodal Representation
Chen, X., & Wu, J. (2022) · IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) · doi:10.1109/qrs-c57518.2022.00078
Semi-Automatic, Inline and Collaborative Web Page Code Curations
Rutishauser, R., Meyer, A. N., Holmes, R., & Fritz, T. (2023) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1109/icse48619.2023.00159
The Influence of Search Engine Ranking Quality on the Performance of DevelopersPreprint
Rocha, A. M., Maia, M. D. A., & Dantas, C. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4633780
A Code Search Method Incorporating Code Annotations
Li, Q., Liu, J., & Zhang, X. (2024) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-54521-4_18
Supporting Web-Based API Searches in the IDE Using Signatures
Bradley, N., Fritz, T., & Holmes, R. (2024) · International Conference on Software Engineering · doi:10.1145/3597503.3639089
The Influence of Search Engine Ranking Quality on the Performance of Programmers
Rocha, A. M., Dantas, C., & Maia, M. D. A. (2025) · Journal of Software Engineering Research and Development · doi:10.5753/jserd.2025.4494
- Authors
- Rahman, M. M., Barson, J., Paul, S., Kayani, J., Lois, F. A., Quezada, S. F., Parnin, C., Stolee, K. T., & Ray, B.
- Affiliations
- University of Virginia
- University of Virginia (US)
- Clemson University (US)
- North Carolina State University
- Codealike, Argentina
- North Carolina State University (US)
- Venue
- Proceedings of the 15th International Conference on Mining Software Repositories
- Publisher
- ACM
- Published
- 2018-05-28
- Pages
- 465-475
- OpenAlex
- W2793121700
- Cited by
- 62
- References
- 27
- Citations by year
- 2025: 3 · 2024: 12 · 2023: 4 · 2022: 14 · 2021: 14 · 2020: 8 · 2019: 7
- FWCI
- 5.69
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Mining Software Repositories (MSR) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (CCF-16-19123,CNS-16-18771)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Keywords
- code search, search strategies, search engine ranking
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
