Evidence map›Paper›PMID 36679436›Full record

ArticleSensors (Basel, Switzerland)2023

A Recommender System for Robust Smart Contract Template Classification.

Sandi Gec, Vlado Stankovski, Dejan Lavbič, Petar Kochovski

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
3.7field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 8 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Sandi GecFaculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia.ORCID 0000-0003-2331-4523
Vlado StankovskiFaculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia.ORCID 0000-0001-9547-787X
Dejan LavbičFaculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia.ORCID 0000-0003-2390-4160
Petar KochovskiFaculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia.ORCID 0000-0003-4345-2069
University of Ljubljana · SI

Funding

European Commission 957338Research Agency of the Republic of Slovenia P2-0426
6 · The paper itself

Abstract

IoT environments are becoming increasingly heterogeneous in terms of their distributions and included entities by collaboratively involving not only data centers known from Cloud computing but also the different types of third-party entities that can provide computing resources. To transparently provide such resources and facilitate trust between the involved entities, it is necessary to develop and implement smart contracts. However, when developing smart contracts, developers face many challenges and concerns, such as security, contracts' correctness, a lack of documentation and/or design patterns, and others. To address this problem, we propose a new recommender system to facilitate the development and implementation of low-cost EVM-enabled smart contracts. The recommender system's algorithm provides the smart contract developer with smart contract templates that match their requirements and that are relevant to the typology of the fog architecture. It mainly relies on OpenZeppelin, a modular, reusable, and secure smart contract library that we use when classifying the smart contracts. The evaluation results indicate that by using our solution, the smart contracts' development times are overall reduced. Moreover, such smart contracts are sustainable for fog-computing IoT environments and applications in low-cost EVM-based ledgers. The recommender system has been successfully implemented in the ONTOCHAIN ecosystem, thus presenting its applicability.

Indexed as

AlgorithmsEcosystemCloud ComputingDocumentationTrustclassificationclusterinheritancerecommender systemsmart contract

Identifiers

PMID36679436
PMCPMC9866539
OpenAlexW4313648680

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.