Security, Performance, and Applications of Smart Contracts: A Systematic Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Blockchain is the promising technology of recent years, which has attracted remarkable attention in both academic studies and practical industrial applications. The smart contract is a programmable transaction that can perform a sophisticated task, execute automatically, and store on the blockchain. The smart contract is the key component of the blockchain, which has made blockchain a technology beyond the scope of the cryptocurrencies and applicable for a variety of applications such as healthcare, IoT, supply chain, digital identity, business process management, and more. Although in recent years the progress toward improving blockchain technology with the focus on the smart contract has been impressive, there is a lack of reviewing the smart contract topic. This paper systematically reviews the key concepts and proposes the direction of recent studies and developments regarding the smart contract. The research studies are presented in three main categories: 1) security methods and tools; 2) performance improvement approaches; and 3) decentralized applications based on smart contracts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it