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A Blockchain-based Trustworthy and Secure Review
System for Decentralized e-Portfolio Platforms
Mpyana Mwamba Merlec
Dept. of Computer Science and Eng.
Korea University
Seoul, South Korea
mlecjm@korea.ac.kr
Nday Kabulo Sinai
Dept. of Computer Science and Eng.
Korea University
Seoul, South Korea
sinai@korea.ac.kr
Hoh Peter In
Dept. of Computer Science and Eng.
Korea University
Seoul, South Korea
hoh in@korea.ac.kr
Abstract—E-portfolios have emerged as powerful tools in the
education and professional development fields, enabling learners
to showcase their skills, achievements, and credentials in a
digital format. However, ensuring the security, authenticity and
reliability of e-portfolio artifacts and credentials remains a
challenge. Existing review systems face challenges such as lack
of transparency, vulnerability to manipulation, and reliance on
centralized trust. Therefore, this paper proposes B-TrustReview,
a trustworthy and secure review system for decentralized e-
portfolio platforms that leverages blockchain and smart con-
tracts. By leveraging blockchain’s decentralized and tamper-
resistant nature, the system enhances the security, transparency,
and reliability of reviews. Every review is securely recorded on
the blockchain, creating an auditable and transparent record
of evaluations. Smart contracts govern the execution of the
review process, automating the validation and verification of
reviews based on predefined criteria. This automation reduces
reliance on intermediaries and minimizes the risk of biased or
manipulated reviews fostering transparency, accountability, and
credibility in evaluating e-portfolios. Moreover, it enables secure
and efficient transactions, ensuring the confidentiality of user
data and protecting against unauthorized access.
Index Terms—Blockchain, Decentralized review system, Elec-
tronic portfolio (e-portfolio), Reputation system, Smart contract
I. INTRODUCTION
E-portfolios have emerged as powerful tools in the field
of education and professional development, enabling learners
to showcase their skills, achievements, and credentials in a
digital format [1]–[6]. These platforms facilitate the creation,
publication, and management of e-portfolios, providing a
comprehensive view of an individual’s capabilities [4]–[7].
Review systems play a vital role in assessing and validating
the quality, credibility, and achievements of users’ e-portfolios
[6]–[9]. These systems allow stakeholders, such as educators,
peers, and employers, to contribute comments, ratings, and
recommendations. Review systems aim to improve e-portfolio
content, support self-reflection, and assist decision-making
processes, while allowing to build online reputation [7]–[13].
However, existing review and reputation management systems
within e-portfolio platforms face significant limitations that
hinder their effectiveness and impact [8]–[16]. These limita-
tions include centralized trust, fake reviews, lack of verifiabil-
ity, limited transparency, vulnerability to manipulation, privacy
concerns, limited user incentives, and scalability challenges.
To address these limitations, there is a growing need for
a trustworthy and secure review system that can enhance the
credibility, transparency, and reliability of e-portfolio reviews
[8]–[10]. Blockchain technology has opened up new possi-
bilities for building decentralized systems that can provide
robust trust and security mechanisms [17]–[23], [25]. With
the emergence of blockchain-enabled decentralized e-portfolio
platforms [26]–[39], learners have gained the ability to exer-
cise complete ownership and control over their e-portfolios.
Thus, potential employers seek to independently verify the
credentials and artifacts presented in these e-portfolios without
relying on trusted third parties. However, ensuring trustwor-
thiness, transparency, security, and auditability within these
platforms remains a challenge.
In this paper, we propose “B-TrustReview”, a blockchain-
based trustworthy and secure review system for decentral-
ized e-portfolio platforms. The system aims to address the
aforesaid limitations of existing review systems by leveraging
the capabilities of blockchain technology, smart contracts, and
cryptographic techniques. By leveraging the decentralized and
tamper-resistant nature of blockchain, the system enhances the
security, transparency, and reliability of the review process,
and ensures the integrity of review data. Every review is
securely recorded on the blockchain, creating an auditable and
transparent record of evaluations. Cryptography techniques
including digital signatures and zero-knowledge proofs (ZKP),
are used to preserve user privacy and ensure that reviews
are tamper-proof and originated from genuine sources. Smart
contracts govern the execution of the review process, au-
tomating the validation and verification of reviews based on
predefined criteria. This automation reduces reliance on trusted
intermediaries and minimizes the risk of biased or manipulated
reviews fostering transparency, accountability, and credibility
in evaluating e-portfolios. It also enables secure and efficient
transactions, ensuring the confidentiality of user data and
protecting against unauthorized access. The implementation
and evaluation of the proposed system proved its effectiveness
and scalability. This paper extends our previous work [26].
The rest of the paper is organized as follows. Section II
elaborates on the research background and related works. Sec-
tion III presents the proposed system design and architecture.
Section IV covers the implementation and evaluation details.
675979-8-3503-1327-7/23/$31.00 ©2023 IEEE ICTC 2023
Section V concludes the paper and suggests future research
directions.
II. BACKGROUND AND RELATED WORK
This section provides the research background and recent
efforts towards secure and trustworthy review schemes for
decentralized e-portfolio systems.
A. E-Portfolio and Review Systems
E-portfolios are digital repositories that enable learners
to document and present their accomplishments, skills, and
experiences [1]–[3]. They provide a comprehensive view of
an individual’s learning journey and serve as a reflective
tool for self-assessment and goal setting. E-portfolios offer
several benefits, such as fostering lifelong learning, promoting
critical thinking and reflection, facilitating career develop-
ment, and supporting assessment and evaluation processes
[4]–[7]. Research in the e-portfolio domain has focused on
various aspects [2]–[7], including design principles, peda-
gogical approaches, assessment strategies, and technical im-
plementations. An overview of e-portfolios is given in [1]–
[4], discussing their purpose, benefits, and designs [5], [6].
Studies in [4], [7] have explored the impact of e-portfolios
on student engagement, learning outcomes, and professional
development. Challenges of balancing the two faces of e-
portfolios are studied [3], focusing on the tension between
showcasing achievements and supporting critical reflection.
These studies provide foundational knowledge on e-portfolios,
setting the stage for developing online portfolio platforms.
Review systems play a crucial role in assessing and validat-
ing the quality, credibility, and achievements of individuals’
e-portfolios [8], [9]. These systems facilitate the evaluation
process for potential employers, educators, and peers, allow-
ing them to make informed decisions based on the reviews
associated with e-portfolios to their online reputation [6], [8]–
[10]. E-portfolio review systems provide features for users
to provide feedback, comments, and evaluations on various
aspects of an e-portfolio, including the content, presentation,
organization, and overall quality [1], [4], [6].
The literature on review systems emphasizes the importance
of reliable and trustworthy feedback mechanisms [8]–[15]. In
[8], they analyzed the credibility of online review platforms.
The impact of online review features on user behavior is
studied in [9]. The reputation competition and review fraud on
online platforms are explored in [10]–[13]. Authors in [14]–
[16] examined different review methods, including rubrics,
peer assessment, and expert evaluation, to ensure fairness,
validity, and consistency. In [21], [22], they have explored
the role of review systems in fostering a supportive learning
community, enhancing social interaction, and improving the
quality of e-portfolio content. These studies shed light on the
factors influencing the credibility, trustworthiness, and manip-
ulation of online reviews. Reputation management schemes
are required to establish the credibility and trustworthiness
of e-portfolios and their owners [21]–[25]. These systems
assign reputation scores based on the quality of e-portfolios,
as determined by the reviews and evaluations received. Review
and reputation scores provide potential employers and stake-
holders with an assessment of an individual’s competence and
achievements, aiding in the evaluation process [23].
However, traditional e-portfolio review systems have several
limitations that need to be addressed. These include centralized
trust, lack of verifiability, limited transparency, vulnerability
to manipulation, privacy concerns, and limited user incen-
tives [8]–[22]. These limitations can undermine the reliability,
credibility, and fairness of the review process. To overcome
these challenges, there is a need for innovative approaches
that leverage emerging technologies like blockchain, smart
contracts, and cryptography to ensure trustworthy, transparent,
and secure e-portfolio review systems [21]–[28].
B. Blokchain and Smart Contracts
Blockchain is a decentralized and immutable ledger tech-
nology that enables secure and transparent transactions [17],
[18]. It operates on a peer-to-peer network, where each par-
ticipant has a copy of the ledger, ensuring transparency and
immutability of data. Blockchain achieves this by leveraging
cryptography algorithms that secure the transactions and link
them together in blocks, forming a chain of blocks [18].
Additionally, blockchain offers robust security through cryp-
tography algorithms, making it resistant to tampering and
fraud. Smart contracts, on the other hand, are self-executing
agreements that are written into code and automatically exe-
cute predefined actions when certain conditions are met [17]–
[20]. These contracts eliminate the need for intermediaries
and provide automation, efficiency, and accuracy in executing
transactions. Smart contracts are deployed on the blockchain
and operate in a transparent and deterministic manner. They
facilitate automated and secure transactions, eliminating the
need for trust in traditional contractual relationships.
C. Blokchain-based e-Portfolio Review Systems
The integration of blockchain technology into e-portfolio
and review systems has recently gained attention for address-
ing challenges related to trust, security, and data integrity [23]–
[27]. Blockchain provides a decentralized and tamper-proof
ledger that ensures the authenticity and immutability of e-
portfolio artifacts and reviews. It removes the need for inter-
mediaries, reduces risks of data manipulation, and enhances
the transparency and credibility of the review process [19]–
[24]. Decentralized e-portfolio platforms empower learners
to have complete ownership, control, and management over
their e-portfolios [25]–[30]. They also aim to enable potential
employers to independently verify e-portfolio artifacts and
credentials without having to rely on trusted third parties [26].
The literature on blockchain-based e-portfolios and review
systems is still evolving, with limited empirical studies and
practical implementations. In [23], they explored the use
of blockchain for educational record reputation and reward
systems, highlighting the advantages of distributed systems in
enhancing trust and recognition. A blockchain-based architec-
ture is presented in [24] for ensuring the integrity and trans-
676
parency of learning trace repositories. An hybrid access control
approach for enhanced security and privacy blockchain-based
e-portfolio platform is proposed in [28]. A decentralized
peer-review model is introduced in [31], which leverages
blockchain to enhance the credibility and transparency of the
review process. A decentralized reputation system-based on
blockchain is presented in [32] for e-commerce environments,
aiming to mitigate issues related to trust and reliability in
online reviews. In [33], they present a scientific publishing
platform powered by blockchain enabling transparent and im-
mutable peer review processes. Decentralized approaches for
scientific publication and peer review are introduced in [34]–
[37], utilizing blockchain and IPFS to enhance transparency
and trust. In [34], they emphasize on shared governance and
collaboration among researchers. Singh et al. [34] focused
on ensuring the integrity and trustworthiness of the review
process. In [37], they tackled the transparency and privacy
issues in academic publication systems.
In [38], they discussed challenges and strategies for rep-
utation management in the age of the World Wide Web. In
[39], they focused on ranking reputation and quality in online
rating systems, proposing methods to improve the accuracy
and fairness of reputation rankings. The potential benefits
and challenges associated with online reputation systems are
discussed in [40]. Zhou et al. [41], [42] proposed a reputation
ranking method based on rating patterns and rating deviation
to enhance the accuracy and reliability of review reputation
systems. In [43], they developed a product recommendation
system using deep learning-based recurrent neural networks to
improve the accuracy and effectiveness of recommendations.
These studies collectively contributed to the understanding
of e-portfolio and reputation management, and blockchain
technology in the context of review systems. They provide
insights into the challenges and opportunities associated with
developing trustworthy, transparent, and secure review systems
for blockchain-based decentralized e-portfolio platforms.
III. SYSTEM DESIGN AND ARCHITECTURE
This section describes the system design and architecture.
A. System Architecture
Fig. 1 depicts the proposed B-TrustReview system architec-
ture for blockchain-based decentralized e-portfolio platforms.
The description of e-portfolio management process in black
color can be found in [26]. The flow in brown color depicts the
e-portfolio review management process. After an e-portfolio
has been submitted for evaluation to an evaluator, who uses
the system to find reviewers matching with the portfolio field,
and send them review requests (1). Upon accepting the request,
reviewers receive e-portfolio and artifact details for review (3)
and will submit the review report (4) that needs to be approved
by the evaluator (5) for the reviewers to receive their rewards
(6). Considering given reviews, the evaluator completes the
e-portfolio assessment and issues digitally signed evaluation
proof verifiable credentials. Upon receiving the evaluation
proof, (7) the holder can publish e-portfolio credentials for
Present e-portfolio
credentials
Verify e-portfolio
credentials
Request
Response
Evaluators
Holders
Verifiers
1
1
2
6
5
4
10
7
8
On-chain
Off-chain
Smart contract
Profile(s)
Reviewers
Verifiable E-Portfolio
Repository
Recruitment Platforms
Connection
E-Portfolio Platform
Blockchain Network
B-TrustReview
1
3
2
4
6
7
9
31
5
64
4
Fig. 1. Overview of the proposed B-TrustReview, a blockchain-based trust-
worthy and secure review system for decentralized e-portfolio platforms [2].
potential recruiters or independent versifiers (7)–(8) to be able
to access and verify their integrity and authenticity.
Fig. 2 depicts the system architecture of the proposed
trustworthy and secure review system for blockchain-based
decentralized e-portfolio platforms, organized as follows.
1) Blockchain-based TrustReview System: It is a core mod-
ule that ensures trustworthiness and security of the review sys-
tem in a blockchain-based decentralized e-portfolio platform.
•Reviwer Matcher matches reviewers with relevant e-
portfolios based on their expertise, skills, and interests.
It ensures that reviewers are certified in the domain to
enhance the credibility and quality of the reviews.
•Review Registrator is responsible for receiving and
recording reviews submitted by reviewers. It securely
stores reviews as transactions on the blockchain, ensuring
immutability and transparency.
•Review Validator performs a validation process to ensure
the accuracy and reliability of reviews. It verifies the
identity of reviewers and validates the authenticity of
reviews using cryptographic methods and identity man-
agement mechanisms. It checks for consistency, quality,
and conformity to predefined criteria or guidelines.
•Review Verifier checks the authenticity and integrity of
reviews. It employs cryptographic techniques, such as
digital signatures or zero-knowledge proofs, to ensure
that reviews are tamper-proof and originated from gen-
uine sources. So, verifiers can independently verify and
validate the review data, fostering trust among users.
•Reputation Manager tracks and maintains the reputation
of reviewers based on their past reviews and interac-
tions within the e-portfolio platform. Reputation scores
or ratings can be calculated based on factors such as
review quality, consistency, and feedback from other
677
Blockchain-based Decentralized e-Portfolio Platform
Blockchain-based TrustReview System
Incentive ManagerReview Registrator Review Validator
User Profile
Manager
Reputation
Manager
Review Verifier
Owner(s) Verifier(s)
Evaluator(s)
Reviewer(s)
e-Portfolio
Manager
Security & Privacy
Manager
Reviewer Matcher
0
Smart Contract (SC)
Blockchain Node
State Database
P2P Storage (IPFS) Node
Fig. 2. System architecture of the proposed blockchain-based trustworthy and
secure review system for decentralized e-portfolio platforms.
users. It helps users assess the reliability and credibility
of reviewers, promoting trust in the review system.
•Incentive Manager: encourages active participation and
quality contributions by providing incentives to reviewers.
It can offer rewards, tokens, or other forms of recognition
to incentivize users to submit honest and helpful reviews.
It is critical for motivating users to engage in the review
process and maintain the overall integrity of the system.
2) Blockchain-based Decentralized E-Portfolio Platform:
It provides features for managing user profiles, e-portfolios,
and ensuring security and privacy within the platform.
•E-Portfolio manager enables users to create, publish,
and manage their e-portfolios. Encrypted artifacts of
registered e-portfolios are securely stored in repositories
powered by InterPlanetary File Systems (IPFS)1. Smart
contracts are leveraged for ownership and access con-
trol management. E-Portfolio manager provides a user-
friendly interface for users to showcase their achieve-
ments, skills, and experiences. It ensures the integrity
and availability of e-portfolio data, facilitating seamless
interactions between users and potential employers.
•User profile manager manages the membership enroll-
ments, decentralized identifiers (DID) [44], user profiles,
roles, and credentials. It allows users to create and
manage their profiles within the e-portfolio platform. It
securely stores user information and handles authentica-
tion and authorization processes. It also ensures that only
authorized users can access and modify their profile data,
safeguarding user privacy and security.
•Security and privacy manager provides robust security
measures and privacy controls within the e-portfolio
platform. It safeguards user data, enforces access control
policies, and protects against unauthorized access or data
1https://ipfs.tech/
Algorithm 1 E-portfolio review registration
Setup: Smart contract parameters: [Ca,A
a]
Input: Pf
id,R
id ={Review attributes},msg.sender,Pk,S
k
Output: Transaction execution state
1: Collect completed e-portfolio reviews from RM TDB:
SELECT*FROM RM TDB WHERE Pf[id].rv status = “Completed”
2: while (Rid,Pf
id)do
3: Check whether Rid exists in the blockchain:
4: R←sc.getReviewInfo(Rid)
5: if (msg.sender ∈A)∧(R=NULL)then
6: R[id]←sc.newReview(sign(Rid,Pf
id), Pk,S
k)
7: if err =NULL then
8: return errorMessage(err.Text)
9: else
10: Emit sc.newReview(msg.sender,Rid,R
Rv,t)
11: Save Thin RM TDB (Review Management Transactional DB)
12: end if
13: else
14: return “Not authorized or Rid already exists”
15: end if
16: end while
Algorithm 2 E-portfolio review approval and proof generation
Setup: Smart contract parameters: [Ca,A
a]
Input: Rid,msg.sender,Pk,S
k
Output: Transaction execution state
1: Collect submitted review state: sc.getReview(rv status = “Subimtted”)
2: while (Rid)do
3: if (msg.sender ∈A)∧(R[id].rv status =“Approved”) then
4: if Rid satisfies review policy requirements then
5: rv status ←“Approved”
6: R[id]←sc.reviewUpdate(sign(Rid,rv status,t),P
k,S
k)
7: sc.sendReward(Rid,R
Rv,Γ,t)
8: sc.generateReviewProof(Rid,Pid ,R
Rv,t)
9: if err =NULL then
10: return errorMessage(err.Text)
11: else
12: Emit sc.reviewApproved(msg.sender,Rid,Pid,R
Rv,t)
13: Save Thin the RMS TDB transactional database
14: end if
15: else
16: return “Rid is rejected”
17: end if
18: else
19: return “Not authorized or Rid already approved”
20: end if
21: end while
breaches. It ensures that user information is handled in
compliance with privacy regulations, like GDPR [19] and
industry best practices, enhancing the security and privacy
of the e-portfolio platform.
I V. I MPLEMENTATION AND EVALUATION
Algorithm 1 depicts the e-portfolio review on-chain reg-
istration procedure, which receives portfolio identifier Pf
id,
review identifier Rid and attributes, sender address, public Pk
and private Skkeys as input. Upon a calling, the function
starts by verifying if the review status is completed in the
RM TDB and checking if the sender is authorized and Rid
does not exist in the blockchain, then it signs the transaction,
saves the review record on blockchain and the transaction
hash in RM TDB. The e-portfolio review approval and proof
generation procedure is described in Algorithm 2, which gets
Rid, sender address, public Pkand private Skkeys as inputs.
678
Algorithm 3 E-portfolio review proof evaluation
Setup: Smart contract parameters: [Ca,A
a]
Input: Rid,Pid ,msg.sender
Output: True/False
1: while (Rid,P
id)do
2: Check whether Rid and Pid exist in the blockchain:
3: R←sc.getReviewInfo(Rid)
4: if (msg.sender ∈A)∧(R=NULL)∧R.Pid =Pid then
5: sc.verifyReviewProof(Rid,Pid)
6: if Pid and Rid are genuine then
7: return True
8: else
9: return False
10: end if
11: else
12: return “Not authorized or Rid and Pid don’t match.”
13: end if
14: end while
Upon a calling, the function checks if the sender address is
allowed and the review status is not approved yet, then updates
the status as “Approved”, signs the transaction, updates the
review state in blockchain. Next, it sends the reward token Γ
to reviewer RRv and issues evaluation proof Pid, and saves the
transaction hash in RM TDB. The review proof verification
procedure is given in Algorithm 3. It gets Rid and Pid as
inputs to verify whether the given proof is authentic and valid
or not.
Goerli2testnet was used as the blockchain network. Goerli
is an Ethereum [17] test network using Proof of Authority
(PoA) consensus. The smart contracts were implemented in
Solidity language. Incentive Manager utilizes ERC20 tokens
[45] to provide incentives to reviewers. ERC20 tokens are
cryptographic tokens that follow a set of standards that are
established on the Ethereum blockchain network. The In-
centive Manager rewards reviewers with ERC20 tokens for
their contributions, encouraging active involvement and high-
quality reviews. These tokens can be exchanged, redeemed, or
traded within the platform, creating an incentivized ecosystem
for reviewers. ZoKrates3was adopted as ZKP protocol for
e-portfolio evaluation proof generation and verification. It is
a toolbox for zkSNARKs [46] implementation on Ethereum.
Nodejs, React, Hardhat, and Web3.js were used to built our
decentralized application (Dapp) and Firebase4was used as
transactional database. Metamask5was used for managing
public-private key pairs and signing transactions.
TABLE I
B-TRUST REVIEW SMART CONTRACTS DEPLOYMENT COST
No Smart contract Deployment Cost
Gas used (Gwei) ETH USD†
(1) PortfolioProjectMgr.sol 4,566,672 0.004566 8.5
(2) BTrustReviewMgr.sol 2,397,899 0.002397 4.4
(3) BTR TokenMgr.sol 1,344,365 0.001344 2.5
(4) ProofVerifier.sol 1,182,965 0.001183 2.2
†ETH Price: 1 ETH = $ 1,875.79 (2023.06.29) – https://coinmarketcap.com/
2https://goerli.net/
3https://github.com/Zokrates/ZoKrates/tree/0.8.4
4https://firebase.google.com/
5https://metamask.io/
TABLE II
B-TRUST REVIEW SMART CONTRACTS OPERATIONAL COST
No Core contract set functions Operational Cost
Gas used (Gwei) ETH USD†
(1) uploadAndSumbitProject 188,329 0.000188 0.35
(2) newEvaluator 68,776 0.000069 0.13
(4) newReviewer 68,775 0.000069 0.13
(3) newProjectReview 124,400 0.000124 0.23
(4) approveReview 161,550 0.000162 0.30
(5) sendReward 182,320 0.000182 0.34
(6) issueProof 227,980 0.000228 0.43
†ETH Price: 1 ETH = $ 1,875.79 (2023.06.29) – https://coinmarketcap.com/
The evaluation of Solidity smart contract deployment and
operational costs is important to understand the resource
requirements and financial implications of deploying and exe-
cuting contracts. Gas usage, representing computational effort
for deploying and running smart contracts on the Ethereum
blockchain, is used to measure costs. It is essential for ensuring
network security and efficiency. Table I provides the deploy-
ment cost assessment of core smart contracts measured in
Gwei, with corresponding Ether (ETH) and USD values. Smart
contract (1) required 4,566,672 gas, which is equal to 0.004566
ETH or approximately 8.5 USD. Similarly, contract (2) had a
deployment cost of 2,397,899 gas, equivalent to 0.002397 ETH
or around 4.4 USD. Contracts (3) and (4) also incurred gas
costs, with their respective ETH and USD values provided in
Table I. In Table II, we assessed the operation costs of main
setter functions of the proposed system that store the data on
blockchain. Unlike storage, reading (getter) functions do not
cost gas fees, as they do not change the ledger state. Based on
the results of the experiment, the system requires on average
122,362 gas, corresponding to 0.000085 ETH, approximately
0.16 USD operational cost. Evaluating contract costs helps
with budgeting, optimization, and financial planning, allowing
estimation of expenses and optimization of contract design.
V. C ONCLUSION AND FUTURE WORK
In this paper, we proposed a blockchain-enabled trustwor-
thy, transparent, secure, and auditable review system (called
“B-TrustReview”) for decentralized e-portfolio platforms. By
leveraging blockchain technology, smart contracts, and cryp-
tography techniques, the system addresses the limitations
of existing review systems and establishes a reliable and
transparent ecosystem. The findings highlight the potential of
blockchain in revolutionizing e-portfolio platforms, providing
enhanced control, accountability, and credibility. Future re-
search can focus on privacy-preserving robust recommendation
mechanisms, scalability enhancements, and real-world imple-
mentation to advance the practicality and effectiveness of the
proposed review system.
ACKNOWLEDGMENT
This work was supported in part by Korea University and
the Institute of Information & Communications Technology
Planning & Evaluation (IITP) grant funded by the Korea
government (MSIT) (No.2021-0-00177, High Assurance of
Smart Contract for Secure Software Development Life Cycle).
679
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