The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Smart Contract Development: Challenges and Opportunities
Abstract
Smart contract, a term which was originally coined to refer to the automation of legal contracts in general, has recently seen much interest due to the advent of blockchain technology. Recently, the term is popularly used to refer to low-level code scripts running on a blockchain platform. Our study focuses exclusively on this subset of smart contracts. Such smart contracts have increasingly been gaining ground, finding numerous important applications (e.g., crowdfunding) in the real world. Despite the increasing popularity, smart contract development still remains somewhat a mystery to many developers largely due to its special design and applications. Are there any differences between smart contract development and traditional software development? What kind of challenges are faced by developers during smart contract development? Questions like these are important but have not been explored by researchers yet. In this paper, we performed an exploratory study to understand the current state and potential challenges developers are facing in developing smart contracts on blockchains, with a focus on Ethereum (the most popular public blockchain platform for smart contracts). Toward this end, we conducted this study in two phases. In the first phase, we conducted semi-structured interviews with 20 developers from GitHub and industry professionals who are working on smart contracts. In the second phase, we performed a survey on 232 practitioners to validate the findings from the interviews. Our interview and survey results revealed several major challenges developers are facing during smart contract development: (1) there is no effective way to guarantee the security of smart contract code; (2) existing tools for development are still very basic; (3) the programming languages and the virtual machines still have a number of limitations; (4) performance problems are hard to handle under resource constrained running environment; and (5) online resources (including advanced/updated documents and community support) are still limited. Our study suggests several directions that researchers and practitioners can work on to help improve developers’ experience on developing high-quality smart contracts.
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
How Many Interviews Are Enough?: An Experiment with Data Saturation and Variability
Guest, G., Bunce, A., & Johnson, L. (2006) · Field Methods · doi:10.1177/1525822x05279903 · Cited by 20,808
The weirdest people in the world?
Henrich, J., Heine, S. J., & Norenzayan, A. (2010) · Behavioral and Brain Sciences · doi:10.1017/s0140525x0999152x · Cited by 12,641
Saturation in qualitative research: exploring its conceptualization and operationalization
Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2018) · Quality & Quantity · doi:10.1007/s11135-017-0574-8 · Cited by 12,033 · cited 1×
“It is often taken to indicate that further data collection or analysis are unnecessary based on the data that have been collected or analyzed hitherto [124].”
BackgroundAre We There Yet? Data Saturation in Qualitative Research
Fusch, P., & Ness, L. (2015) · The Qualitative Report · doi:10.46743/2160-3715/2015.2281 · Cited by 4,460
Cloud Computing: Issues and Challenges
Dillon, T., Wu, C., & Chang, E. (2010) · 2010 24th IEEE International Conference on Advanced Information Networking and Applications · doi:10.1109/aina.2010.187 · Cited by 1,369
Validation and Verification of Smart Contracts: A Research Agenda
Magazzeni, D., McBurney, P., & Nash, W. (2017) · Computer · doi:10.1109/mc.2017.3571045 · Cited by 184
Cited by
Wu, Y., Dai, H.-N., & Wang, H. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3025916 · Cited by 323
Integrating BIM and Blockchain across construction lifecycle and supply chains
Celik, Y., Petri, I., & Rezgui, Y. (2023) · Computers in Industry · doi:10.1016/j.compind.2023.103886 · Cited by 104
Zhang, Q., Yang, D., & Qin, J. (2023) · Journal of theoretical and applied electronic commerce research · doi:10.3390/jtaer18010021 · Cited by 22
Automated Smart Contract Vulnerability Detection using Fine-tuned Large Language Models
Yang, Z., Man, G., & Yue, S. (2023) · Proceedings of the 2023 6th International Conference on Blockchain Technology and Applications · doi:10.1145/3651655.3651658 · Cited by 10
Metadata
- Authors
- Zou, W., Lo, D., Kochhar, P. S., Le, X.-B. D., Xia, X., Feng, Y., Chen, Z., & Xu, B.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2021-10-01
- Volume
- 47
- Issue
- 10
- Pages
- 2084-2106
- ISSN
- 0098-5589 (ISSN-L)
- 1939-3520
- 2326-3881
- OpenAlex
- W2975871742
- Cited by
- 727
- References
- 6
- FWCI
- 48.42
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Smart Contract Development: Challenges and Opportunities. https://app.cochat.ai/papers/10.1109/tse.2019.2942301
- The paper
- Zou, W., Lo, D., Kochhar, P. S., Le, X.-B. D., Xia, X., Feng, Y., Chen, Z., & Xu, B. (2021). Smart Contract Development: Challenges and Opportunities. IEEE Transactions on Software Engineering. https://doi.org/10.1109/tse.2019.2942301
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.
