A SYSTEMATIC MAPPING STUDY ON CURRENT RESEARCH TOPICS IN SMART CONTRACTS

International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 5, October 2017
DOI:10.5121/ijcsit.2017.9511 151
A SYSTEMATIC MAPPING STUDY ON CURRENT
RESEARCH TOPICS IN SMART CONTRACTS
Maher Alharby1,2
and Aad van Moorsel1
1
School of Computing Science, Newcastle University, Newcastle, UK
2
College of Computer Science and Engineering, Taibah University, Medina, KSA
ABSTRACT
An appealing feature of blockchain technology is smart contracts. A smart contract is executable code that
runs on top of the blockchain to facilitate, execute and enforce an agreement between untrusted parties
without the involvement of a trusted third party. In this paper, we conduct a systematic mapping study to
collect all research that is relevant to smart contracts from a technical perspective. The aim of doing so is
to identify current research topics and open challenges for future studies in smart contract research. We
extract 24 papers from different scientific databases. The results show that about two thirds of the papers
focus on identifying and tackling smart contract issues. Four key issues are identified, namely, codifying,
security, privacy and performance issues. The rest of the papers focuses on smart contract applications or
other smart contract related topics. Research gaps that need to be addressed in future studies are provided.
KEYWORDS
Blockchain, Smart contracts, Systematic mapping study, Survey
1. INTRODUCTION
Transactions between parties in current systems are usually conducted in a centralised form,
which requires the involvement of a trusted third party (e.g., a bank). However, this could result
in security issues (e.g., single point of failure) and high transaction fees. Blockchain technology
has emerged to tackle these issues by allowing untrusted entities to interact with each other in a
distributed manner without the involvement of a trusted third party. Blockchain is a distributed
database that records all transactions that have ever occurred in a network. Blockchain was
originally introduced for Bitcoin (a peer-to-peer digital payment system), but then evolved to be
used for developing a wide range of decentralised applications. An appealing application that can
be deployed on top of blockchain is smart contracts.
A smart contract is executable code that runs on the blockchain to facilitate, execute and enforce
the terms of an agreement between untrusted parties. It can be thought of as a system that releases
digital assets to all or some of the involved parties once the pre-defined rules have been met [1].
Compared to traditional contracts, smart contracts do not rely on a trusted third party to operate,
resulting in low transaction costs. There are different blockchain platforms that can be utilised to
develop smart contracts, but Ethereum is the most common one. This is because Ethereum’s
language supports Turing-completeness feature that allows creating more advanced and
customised contracts. Smart contracts can be applied to different applications (e.g., smart
properties, e-commerce and music rights management).
The main aim of this study is to identify the research topics that have been carried out about
blockchain-based smart contracts and current challenges that need to be addressed in future
studies. To achieve this aim, we selected a systematic mapping study as the methodology for our
study. We followed the systematic mapping process presented in [2] to search for relevant papers
in scientific databases and to produce a map of current smart contract research. The produced

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map could help researchers identify gaps for future studies. The focus of our study is to only
explore smart contract studies from a technical point of view.
The structure of this paper is as follows. Section 2 discusses background information about
blockchain and smart contracts technologies. It also discusses several smart contract platforms
and potential applications. Section 3 describes the research methodology adopted for our study.
Section 4 presents the results of searching and screening for relevant papers and the results of
classifying smart contract topics. Section 5 discusses the results and answers the research
questions of the study. Section 6 concludes the paper.
2. BACKGROUND
This section presents general background information about blockchain and smart contracts
technologies. It also discusses some blockchain platforms that support the development of smart
contracts. Finally, it provides some potential use cases for smart contracts.
2.1. BLOCKCHAIN TECHNOLOGY
A blockchain is a distributed database that records all transactions that have ever occurred in the
blockchain network. This database is replicated and shared among the network’s participants. The
main feature of blockchain is that it allows untrusted participants to communicate and send
transactions between each other in a secure way without the need of a trusted third party.
Blockchain is an ordered list of blocks, where each block is identified by its cryptographic hash.
Each block references the block that came before it, resulting in a chain of blocks. Each block
consists of a set of transactions. Once a block is created and appended to the blockchain, the
transactions in that block cannot be changed or reverted. This is to ensure the integrity of the
transactions and to prevent double-spending problem.
Cryptocurrencies have emerged as the first generation of blockchain technology.
Cryptocurrencies are basically digital currencies that are based on cryptographic techniques and
peer-to-peer network. The first and most popular example of cryptocurrencies is Bitcoin. Bitcoin
[3] is an electronic payment system that allows two untrusted parties to transact digital money
with each other in a secure manner without going through a middleman (e.g., a bank).
Transactions that occurred in the network are verified by special nodes (called miners). Verifying
a transaction means checking the sender and the content of the transaction. Miners generate a new
block of transactions after solving a mathematical puzzle (called Proof of Work) and then
propagate that block to the network. Other nodes in the network can validate the correctness of
the generated block and only build upon it if it was generated correctly. However, Bitcoin has
limited programming capabilities to support complex transactions. Bitcoin, thus, does not support
the creation of complex distributed applications on top of it.
Other blockchains such as Ethereum have emerged as the second generation of blockchain to
allow building complex distributed applications beyond the cryptocurrencies. Smart contracts,
which will be discussed in the following section, are considered as the main element of this
generation [4]. Ethereum blockchain is the most popular blockchain for developing smart
contracts. Ethereum is a public blockchain with a built-in Turing-complete language to allow
writing any smart contract and decentralised application.
There are two types of blockchain, namely, public and private blockchain [5]. In a public
blockchain, any anonymous user can join the network, read the content of the blockchain, send a
new transaction or verify the correctness of the blocks. Examples of public blockchains are
Bitcoin, NXT and Ethereum. In a private blockchain, only users with permissions can join the
network, write or send transactions to the blockchain. A company or a group of companies are

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usually responsible for giving users such permissions prior to joining the network. Examples of
private blockchains are Everledger, Ripple and Eris.
2.2. SMART CONTRACTS
A smart contract is executable code that runs on the blockchain to facilitate, execute and enforce
the terms of an agreement. The main aim of a smart contract is to automatically execute the terms
of an agreement once the specified conditions are met. Thus, smart contracts promise low
transaction fees compared to traditional systems that require a trusted third party to enforce and
execute the terms of an agreement. The idea of smart contracts came from Szabo in 1994 [6].
However, the idea did not see the light till the emergence of blockchain technology. A smart
contract can be thought of as a system that releases digital assets to all or some of the involved
parties once arbitrary pre-defined rules have been met [1]. For instance, Alice sends X currency
units to Bob, if she receives Y currency units from Carl.
Many different definitions of a smart contract have been discussed in the literature. In [7], the
author classified all definitions into two categories, namely, smart contract code and smart legal
contract. Smart contract code means “code that is stored, verified and executed on a blockchain”
[7]. The capability of this smart contract depends entirely on the programming language used to
express the contract and the features of the blockchain. Smart legal contract means code to
complete or substitute legal contracts. The capability of this smart contract does not depend on
the technology, but instead on legal, political and business institutions. The focus of this study
will be on the first definition, which is smart contract code.
Figure 1. Smart contract system [8].
A smart contract has an account balance, a private storage and executable code. The contract’s
state comprises the storage and the balance of the contract. The state is stored on the blockchain
and it is updated each time the contract is invoked. Figure 1 depicts the smart contract system.
Each contract will be assigned to a unique address of 20 bytes. Once the contract is deployed into
the blockchain, the contract code cannot be changed. To run a contract, users can simply send a
transaction to the contract’s address. This transaction will then be executed by every consensus
node (called miners) in the network to reach a consensus on its output. The contract’s state will
then be updated accordingly. The contract can, based on the transaction it receives, read/write to
its private storage, store money into its account balance, send/receive messages or money from
users/other contracts or even create new contracts.
There are two types of smart contracts, namely, deterministic and non-deterministic smart
contracts [9]. A deterministic smart contract is a smart contract that when it is run, it does not
require any information from an external party (from outside the blockchain). A non-deterministic
smart contract is a contract that depends on information (called oracles or data feeds) from an

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external party. For example, a contract that requires the current weather information to be run,
which is not available on the blockchain.
2.3. PLATFORMS FOR SMART CONTRACTS
Smart contracts can be developed and deployed in different blockchain platforms (e.g., Bitcoin,
Ethereum and NXT). Different platforms offer distinctive features for developing smart contracts.
Some platforms support high-level programming languages to develop smart contracts. We will
only focus on three public platforms in this section.
• Bitcoin [3] is a public blockchain platform that can be used to process cryptocurrency
transactions, but with a very limited compute capability. Bitcoin uses a stack-based
bytecode scripting language. The ability of creating a smart contract with rich logic using
Bitcoin scripting language is very limited [10]. In Bitcoin, a simple logic that requires
multiple signatures to sign a single transaction before confirming the payment is possible.
However, writing contracts with complex logic is not possible due to the limitations of
Bitcoin scripting language. Bitcoin scripting language, for example, neither supports
loops nor withdrawal limits [1]. To implement a loop, the only possible way is by
repeating the code many times, which is inefficient.
• Ethereum [1,11] is a public blockchain platform that can support advanced and
customized smart contracts with the help of Turing-complete programming language.
Ethereum platform can support withdrawal limits, loops, financial contracts and gambling
markets. The code of Ethereum smart contracts is written in a stack-based bytecode
language and executed in Ethereum Virtual Machine (EVM). Several high-level
languages (e.g., Solidity, Serpent and LLL) can be used to write Ethereum smart
contracts. The code of those languages can then be compiled into EVM bytecodes to be
run. Ethereum currently is the most common platform for developing smart contracts.
• NXT is a public blockchain platform that includes built-in smart contracts as templates
[10]. NXT only allows developing smart contracts using those templates. It does not,
however, allow customized smart contracts due to the lack of Turing-completeness in its
scripting language.
2.4. SMART CONTRACT APPLICATIONS
There are various possible applications where smart contracts can be applied to. Some of these
applications are as follows:
• Internet of Thing and smart property [12]: there are billions of nodes that are sharing data
between each other through the Internet. A potential use case of blockchain-based smart
contracts is to allow those nodes to share or access different digital properties without a
trusted third party. There are various companies that investigate this use case. For
example, Slock.it is a German company that utilises Ethereum-based smart contracts for
renting, selling or sharing anything (e.g, selling a car) without the involvement of a
trusted third party.
• Music rights management [13]: a potential use case is to record the ownership rights of a
music in the blockchain. A smart contract can enforce the payment for music owners
once a music is used for commercial purposes. It also ensures the payment is being
distributed between the music's owners. Ujo is a company that investigates the use of
blockchain-based smart contracts in the music industry.
• E-commerce: a potential use case is to facilitate the trade between untrusted parties (e.g.,
seller and buyer) without a trusted third party. This would result in reduction of trading

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costs. Smart contracts can only release the payment to the seller once the buyer is
satisfied with the product or service they received [14].
There are other possible applications such as e-voting, mortgage payment, digital right
management, motor insurance, distributed file storage, identity management and supply chain.
3. RESEARCH METHODOLOGY
We selected the systematic mapping study presented in [2] as the research methodology for our
study to explore studies related to smart contracts. The results of this systematic mapping study
would allow us to identify and map research areas related to smart contracts. In addition, it would
allow us to identify research gaps that need to be considered for future studies. The process for
the systematic mapping study falls into five steps as depicted in Figure 2.
Figure 2. Steps of the systematic mapping study [2].
Definition of research questions:
This step is to identify the research questions the study is aiming to answer. For our study, we
defined the following research questions:
RQ1. What are the current research topics on smart contracts?
RQ2. What are the current smart contract applications?
RQ3. What are the research gaps that need to be addressed in future studies?
Conducting the search:
This step is to search and to find all scientific papers that are related to the research topic, which
is smart contracts. For our study, we decided to select the term ‘smart contract’ as the main
keyword to search for papers. We selected this term because we wanted to narrow down the focus
of our study to only cover smart contract related works. After identifying the keyword for the
searching process, we selected the scientific databases to conduct our search. We selected IEEE
Explore, ACM Digital Library, ScienceDirect, Springer, Ebsco and Scopus. Our focus was to
only include high quality papers published in conferences, journals, workshops, symposiums and
books.
Screening for relevant papers:
This step is to search for papers that are relevant to our research questions. We followed the same
approach as in [15] to look for relevant papers. We first tried to exclude papers that were
irrelevant to our study based on their titles. If we were unable to decide on a paper, we would go a
step further by examining its abstract. We also used exclusion criteria to screen each paper. We
excluded: (1) non-English papers, (2) papers without full text available, (3) papers that utilised
smart contracts in fields other than computer science, (4) redundant papers and (5) articles,
newsletters and grey literature.

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Key-wording using abstracts:
This step is to classify all relevant papers using the key-wording technique described in [15]. We
first read the abstract of each paper to identify the most important keywords and the main
contribution. Those keywords were then used to classify papers into various categories. After
classifying all papers, we read the papers and made changes to the classification when necessary.
Data extraction and mapping process:
This process is to gather all the required information to address the research questions of this
study. We gathered different data items from each paper. These data items embrace the main aims
and contributions of papers.
4. STUDY RESULTS
This section discusses the results of the systematic mapping study that we conducted on smart
contracts. We first discuss the results of searching and screening for relevant papers. Then, we
discuss the results of the classification process.
4.1 SEARCHING AND SCREENING RESULTS
Searching and screening for relevant papers are two steps of the systematic mapping study that
we discussed in Section 3. The results of these steps are as follows. In the searching phase, we
looked for all papers using the term ‘smart contract’ in different scientific databases. We gathered
154 papers in total (as on 5 May 2017). In the screening phase, we first excluded irrelevant papers
based on their titles and/or their abstracts (we excluded 109 irrelevant papers). There are two
reasons why we had a high number of excluded papers. First, many papers were irrelevant to our
study, since our focus was to explore smart contracts from a technical perspective. For instance,
many papers discussed the topic from an economic or legal point of view. Another reason is that
some excluded papers were about cryptocurrencies or blockchain in general, which do not
contribute to our research questions. After that, 17 papers were removed as they were duplicates,
resulting in 28 papers. Among the 28 papers, four papers were excluded as they only discuss
general information about smart contract and how it works, without providing any useful
contribution. Thus, we only selected 24 papers to conduct our systematic mapping study.
4.2 CLASSIFICATION RESULTS
By applying the Key-wording technique that we discussed in Section 3, we classified the papers
into two categories, namely, smart contract issues and other smart contract related topics. We
found about two thirds of the papers fall into smart contract issues category. We classified those
issues into four categories, namely, codifying, security, privacy and performance issues.
Codifying issues mean challenges that are related to the development of smart contracts. Security
issues mean bugs or vulnerabilities that an adversary might utilise to launch an attack. Privacy
issues mean issues related to disclosing contracts information to the public. Performance issues
mean issues that affect the ability of blockchain systems to scale. Table 1 summaries the
identified issues and the proposed solutions. For other smart contract related topics category,
there are nine papers that developed smart contract applications or reported about other topics
(e.g., the combination of smart contract and The Internet of Thing).

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Table 1. Smart contract issues and the proposed solutions.
Codifying issues
From the literature, we found four issues that might face developers during writing smart
contracts, namely, the difficulty of writing correct contracts, the inability to modify or terminate
contracts, the lack of support to identify under-optimised contracts and the complexity of
programming languages.
The first one is the difficulty of writing correct smart contracts [8,16,1718]. Correctness of smart
contracts in this context means contracts that are functioning as intended by their developers. The
reason why it is important to have correct smart contracts is because those contracts have valuable
currency units [8,16]. Thus, if a smart contract was not executed as intended, some of its currency
units would disappear. An example that illustrates this is the Distributed Autonomous
Organisation (DAO) attack, which led to over 60 million US dollars being moved into an
adversary account [23].
In an attempt to tackle this issue, three solutions were identified from the literature. The first
solution is to semi-automate the creation of smart contracts [18] to ease the process of writing
smart contracts. Semi-automation means the translation of human-readable contract
representations to smart contract rules. The second solution is to provide developers with
guidelines to aid them write correct contracts. Delmolino et al. [8], released online materials (e.g.,
a tutorial) to help developers write correct smart contracts. The last solution is the adoption of
formal verification techniques to detect unintended behaviours of smart contracts [16,17]. This

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can help developers recognise those behaviours before posting their contracts to the blockchain.
Bhargavan et al. [16] utilised formal methods to analyse and verify the correctness of smart
contracts, while Bigi et al. [17] went a step further by combining formal methods with game
theory techniques to validate smart contracts.
The second issue is the inability to modify or terminate smart contracts [19]. Due to the
immutability feature of blockchain, smart contracts cannot be changed or terminated after
deploying it into the blockchain. This is different from legal law which allows the rules to be
modified or terminated. In an attempt to tackle this issue, Marino et al. [19] presented a set of
standards to allow smart contracts to be changed or terminated. Such standards are taken from
legal contracts and then defined to fit in the context of smart contracts. Those standards were then
applied to Ethereum-based smart contracts to prove their success. For details about those
standards and how can be applied to Ethereum-based smart contracts, we refer the reader to [19].
The third one is the lack of support to identify under-optimised smart contracts [20]. To run a
smart contract, each computational or storage operation in the contract costs some money. An
under-optimised smart contract is a contract that contains unnecessary or expensive operations.
Such operations result in a high cost at the user's side. In an attempt to tackle this issue, Chen et
al. [20] identified seven programming patterns (e.g., unnecessary and expensive operations in a
loop) in smart contracts which lead to unnecessary extra costs. They also proposed ways to
enhance the optimisation of those patterns to reduce the overall cost of executing smart contracts.
They proposed and developed a tool called ‘GASPER' to detect contracts that suffer from those
patterns. They used the tool to examine current Ethereum smart contracts and found most of them
suffer from such patterns.
The last issue is the complexity of smart contract programming languages [21]. Current smart
contracts are based on procedural languages such as Solidity. In a procedural language, the code
is executed as a sequence of steps. Thus, programmers must specify what should be done and
how to do it. This makes the task of writing smart contracts in those languages cumbersome and
error prone [21]. In an attempt to tackle this issue, Idelberger et al. [21] proposed to utilise logic-
based languages instead of procedural languages. In logic-based languages, programmers do not
necessarily have to specify the sequence of steps for a contract. This will ease the complexity of
writing smart contracts. However, algorithms for logic-based languages are expensive and
inefficient.
Security issues
From the literature, we found six security issues, namely, transaction-ordering dependency,
timestamp dependency, mishandled exception, criminal activities, re-entrancy and untrustworthy
data feeds. In addition to these issues, Atzei et al. [29] surveyed several vulnerabilities in
Ethereum smart contracts.
The first issue is transaction-ordering dependency [22,23]. This problem occurs when two
dependent transactions that invoke the same contract are included in one block. The order of
executing transactions relies on the miner. However, an adversary can successfully launch an
attack if those transitions were not executed in the right order. For example, assume there is a
puzzle contract that incentives the user who solves the puzzle. A malicious owner is listening to
the solutions provided by the users. Once a user submitted a correct solution to the puzzle (Tu),
the malicious owner sends a transaction (To) to update the contract’s reward (e.g., reduce the
reward) right away. Those two transactions (To and Tu) might be included in the same block by
chance. If the miner executed To before Tu, the user would get a lower reward and the malicious
owner would succeed in his attack [23]. To tackle this issue, Natoli et al.[22] suggested the use of
Ethereum-based functions (e.g., SendIfReceived) to enforce the order of transactions. Similarly,
Luu et al.[23] suggested using a guard condition such that “a contract code either returns the
expected output or fails". A tool called ‘OYENTE' developed by [23] can be used to detect
contracts that are vulnerable to transaction-ordering dependency.

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The second issue is timestamp dependency [23]. This problem occurs when a contract uses the
block timestamp as a condition to trigger and execute transactions (e.g., sending money). For
instance, a game-based contract that takes the block timestamp as a random seed to select the
winner. The block timestamp is usually set as the current local time by the miner who generated
the block. However, an issue with the timestamp is that a dishonest miner could vary its value by
about 15 minutes from the current time, while the block is still accepted by the blockchain
system. As the timestamp of a block is not guaranteed to be accurate, contracts that rely on
timestamp value are vulnerable to threats by dishonest miners. To tackle this issue, Luu et al.[23]
suggested using the block number as a random seed for contracts instead of using the block
timestamp. This is because the value of the block number is fixed (miners cannot vary the block
number value). To detect contracts that are vulnerable to timestamp dependency, ‘OYENTE’ tool
presented in [23] can be used.
The third issue is mishandled exception vulnerability [23]. This problem occurs when a contract
(caller) calls another contract (callee) without checking the value returned by the callee. When
calling another contract, an exception (e.g., run out of gas) sometimes raised in the callee
contract. This exception, however, might/might not be reported to the caller depending on the
construction of the call function. Having not reported an exception might lead to threats as in the
KingOfTheEther (KoET) contract [23]. In KoET, an adversary might send a transaction that
results in an exception in order to buy the throne from the current king for free. To tackle this
issue, Luu et al.[ 23] highlighted the importance of checking the value returned by the callee. In
the KoET example, the code can be improved to not release the throne till the payment from the
adversary is completed successfully without any exception. The ‘OYENTE' tool proposed by [23]
can be used to detect mishandled exception vulnerability in smart contracts.
The fourth issue is re-entrancy vulnerability [23]. This problem occurs when an attacker utilises a
recursive call function to conduct multiple repetitive withdrawals, while their balances are only
deduced once. In June 2016, an attacker utilised the re-entrancy vulnerability in the Decentralised
Autonomous Organisation (DAO) to steal over 60 million US dollars [23]. Luu et al. [23]
developed a tool called ‘OYENTE’ to detect this vulnerability.
The fifth issue is criminal activities. Jules et al. [24] highlighted the feasibility of constructing
three different types of criminal activities in smart contract systems, namely, “leakage/sale of
secret documents, theft of private keys and calling-card crimes, a broad class of physical-world
crimes (murder, arson, etc.)" [24]. These crimes can be implemented efficiently in the Ethereum
blockchain by utilising cryptographic techniques as follows. Leakage of secret documents can be
achieved with the support of Serphent (an Ethereum scripting language). Theft of private keys can
be achieved using Succinct Non-interactive ARgument of Knowledge (SNARKs) cryptographic
primitives. Authenticated data feeds, which is data from an external party, can facilitate the
calling-card crimes. The authors of [24], however, did not attempt to tackle those crime activities,
but instead, they highlighted the importance of constructing safeguards against such activities.
The last issue is the lack of trustworthy data feeds (oracles) [25]. As we explained in Section 2.2,
some smart contracts require information (data feeds) from outside the blockchain. The problem
is that there is no guarantee that the information provided by an external source is trustworthy. In
an attempt to tackle this issue, Zhang et al. [25] built a Town Crier (TC) solution that acts as a
trusted third party between external sources and smart contracts to provide authenticated data
feeds for smart contracts. Figure 5 explains the architecture of TC solution. The TC solution
consists of a TC contract that resides on the blockchain and a TC server that resides outside the
blockchain. To send a data feeds request, a user contract can send a request to the TC contract,
which will then be forwarded to the TC server. The server then communicates with external data
sources via HTTPS to get the data feeds. Upon getting the required data feeds, the server will
forward those feeds to the TC contract, which will then be forwarded to the user contract.

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Figure 4. Architecture of TC solution [25].
Privacy issues
From the literature, we found two privacy issues, namely, the lack of transactional privacy and
the lack of data feeds privacy.
The first issue is the lack of transactional privacy [26,27]. In blockchain systems, all transactions
and users’ balances are publicly available to be viewed. This lack of privacy could limit the
adoption of smart contracts as many people consider financial transactions (e.g., stock trading) as
confidential information [26]. To tackle this issue, Kosba et al.[26] built a tool called ‘Hawk’ that
allows developers to write privacy-preserving smart contracts without the need of implementing
any cryptography. The tool is responsible for compiling smart contract code to privacy-preserving
one. Watanabe et al.[27] proposed to encrypt smart contracts before deploying them to the
blockchain. Only participants, who are involved in a contract, can access the contract’s content by
using their decryption keys.
The second issue is the lack of data feeds privacy [25]. When a contract requires data feeds to
operate, it sends a request to the party that provides those feeds. However, this request is exposed
to the public as anyone in the blockchain can see it. To tackle this issue, Zhang et al. [25] extend
their Town Crier (TC) tool to support private requests. A contract can encrypt the request using
the TC’s public key, before sending the request. Upon receiving the encrypted request, the TC
can decrypt it using its private key. Thus, this would guarantee that the content of the request is
kept secret from other users/contracts in the blockchain.
Performance issues
From the literature, we only found one performance issue, which is the sequential execution of
smart contracts [28]. In blockchain systems, smart contracts are executed sequentially (e.g., one
contract at a time). However, this would affect the performance of the blockchain systems
negatively as the number of smart contracts that can be executed per second will be limited. With
the growing number of smart contracts in the future, the blockchain systems will not be able to
scale. Vukolić [28] suggested to execute smart contracts in parallel as long as they are
independent (e.g., “do not update the same variables” [28]). By doing so, the performance of
blockchain systems would be improved as more contracts can be executed per second.
Other topics
Apart from smart contract issues, we found nine papers from the literature that propose smart
contract applications or discuss other smart contract related topics.
There are three smart contract applications proposed in the literature, which are as follows:
• Trading and fair exchange: Bogner et al. [30] developed a smart contract application on
top of the Ethereum blockchain to allow untrusted participants to share everyday objects
(e.g., rent devices). Carrillo et al. [33] developed an application that allows two untrusted
parties (e.g., consumer and provider) to negotiate and then establish an agreement as a
contract.

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• Identity management: Al-Bassam et al. [31] built a system called `SCPKI' on top of the
Ethereum blockchain to overcome the limitations (e.g, centralisation and lack of
transparency) of the Public Key Infrastructure. This system allows entities to manage
their identities in a transparent way without the involvement of a trusted third party such
as central authorities.
• Internet of Thing: Huh et al. [32] used Ethereum smart contracts to define and manage
the behaviours of a few devices under specified conditions. For example, an air
conditioner that switches to energy saving mode when the usage of electricity reaches
170 KW.
In addition to smart contract applications, there are different topics that were discussed in the
literature. In [12], the authors discussed how the combination of blockchain-based smart contracts
with the Internet of Thing could be powerful in terms of facilitating the sharing of services. In [9],
the authors discussed the possibility of applying blockchain-based smart contracts for licensing
management. For example, the use of smart contracts to control the license of software products.
In [14], the authors investigated the possibility of creating complex smart contracts without
relying on scripts. In [34], the authors proposed a new consensus method called ‘credibility’ for
contracts management (e.g., digital right management) to avoid the limitations of existing
consensus methods. In [35], the authors proposed a semantic index approach to search for
information in the Ethereum blockchain.
5. DISCUSSION
This section discusses the study results and answers the research questions that we defined in
Section 3.
RQ1: What are the current research topics on smart contracts?
The results of this systematic mapping study showed that most of the current research on smart
contracts is about identifying and tackling smart contract issues. Four different issues were
identified, namely, codifying, security, privacy and performance issues. Codifying and security
issues were among the most discussed issues. This is because smart contracts store valuable
currency units and any security breach or coding error could result in losing money. The
identified codifying issues are the difficulty of writing correct codes, the inability to modify or
terminate contracts, the lack of support to identify under-optimised contracts and the complexity
of programming languages. The identified security issues are transaction-ordering dependency,
timestamp dependency, mishandled exception, re-entrancy, untrustworthy data feeds and criminal
activities. The identified privacy issues are the lack of transactional privacy and the lack of data
feeds privacy. The identified performance issue is the sequential execution of smart contracts.
Although there are some proposed solutions to tackle these issues, some of them are only abstract
ideas without including any concrete evaluation. A few others are still not tackled yet. For
example, the solution proposed by [21] is only a suggestion to use alternative programming
languages without any implementation. Criminal activities identified by [24] are still not
overcome yet.
Other research proposed smart contract applications or studied other smart contract related topics.
The proposed applications are trading and fair exchange, identity management and Internet of
Thing. The studied topics are combining smart contracts with the Internet of Thing and licensing
management, studying scripting languages for smart contracts, proposing new consensus methods
and proposing an indexing approach to search for useful information in blockchain systems.

162
RQ2: What are the current smart contract applications?
Smart contract applications are solutions that have been developed on top of blockchain
technology. We identified some smart contract applications developed on top of the Ethereum
blockchain. Those applications are to allow untrusted participants to share everyday objects,
establish an agreement as a contract, manage their identities and control the behaviours of the
Internet of Thing devices. Furthermore, we identified other applications that were built as a smart
contract tool on top of the blockchain to detect or tackle codifying, security and privacy issues.
Some of these tools are ‘GASPER’, ‘OYENTE’, ‘HAWK’ and ‘Town Crier’.
RQ3: What are the research gaps that need to be addressed in future studies?
From this systematic mapping study, we identified a number of research gaps in smart contract
research that can be studied by future research. The methodologies used to identify those gaps are
as follows. First, observing issues or limitations from the papers included in this study (e.g., gaps
number 2, 3 and 5). Second, recognising issues that were highlighted by the papers included in
this study, but still are not solved yet (e.g., gaps number 1 and 4).
The first one is the lack of studies on scalability and performance issues. The sequential execution
of smart contracts affects the ability of blockchain systems to scale as we discussed in Section
4.2. With the growing number of smart contracts in the future, this issue will increase further. The
author of [28] described a very high-level solution, which is parallel execution of contracts,
without any concrete evaluation. Parallel execution of contracts faces a challenge in how to
execute contracts that depend on each other at the same time. It is, therefore, essential to conduct
research on identifying and tackling performance issues to ensure the ability of blockchain to
scale.
The second gap is that almost all current research is discussing smart contracts on the Ethereum
blockchain, although there are some other blockchains (e.g., NXT and Eris) that can support the
creation of smart contracts. Different blockchains have distinctive features and advantages. Thus,
future research might investigate different implementations of blockchain to deploy and run smart
contracts.
The third gap is the small number of smart contract applications. Although the concept of smart
contract has gained a lot of attention, there are only a few applications developed by the literature.
This is because smart contract concept is still in its infancy stage. Banasik et al.[14] claimed that
smart contracts are not widely common in practice. For future research, therefore, researchers
could consider studying various potential applications such as e-commerce and cloud storage.
The fourth gap is the lack of research on tackling criminal activities in smart contracts. The author
of [24] only identified three types of criminal activities that can be conducted on smart contracts
without proposing any solution to them. Thus, future research could focus on identifying more
types of criminal activities and proposing solutions to overcome them.
The last gap is the lack of high quality peer-reviewed research on smart contracts. Most of the
research is conducted as blog articles or grey literature without providing great contributions.
There is, therefore, a need for high quality publications on smart contracts.
6. CONCLUSION
Blockchain technology is a distributed database that records all transactions that have ever
occurred in the network. The main feature of blockchain is that it allows untrusted parties to
communicate between each other without the need of a trusted third party. Different distributed
applications beyond cryptocurrencies can be deployed on top of blockchain. One of these
applications is smart contracts, which are executable codes that facilitate, execute and enforce an
agreement between untrusted parties. Ethereum is currently the most common blockchain
platform for developing smart contracts, although there are some other available platforms.

163
To understand current topics on smart contracts, we decided to conduct a systematic mapping
study. The main aim of this systematic mapping study was to identify and map research areas
related to smart contracts. By doing so, we were able identify research gaps that need to be
addressed in future studies. The focus of this study was on smart contracts from a technical point
of view. Thus, we excluded studies with different perspectives (e.g., papers with an economic
perspective). We extracted 24 papers from different databases. We found that most papers
identifying and tackling issues on smart contracts. We grouped these issues into four categories,
namely, codifying, security, privacy and performance issues. The rest of the papers focuses on
proposing smart contract applications or discussing other smart contract related topics.
In this paper, we presented a few research gaps in smart contract research that need to be
addressed in future studies. The identified gaps are the lack of studies on scalability and
performance issues, the lack of studies on deploying smart contracts on different blockchain
platforms other than Ethereum, the small number of the proposed smart contract applications, the
lack of studies on criminal activities in smart contracts and the lack of high quality research on
smart contracts. These identified gaps could be studied by researchers as future works.
REFERENCES
[1] V. Buterin, “A next-generation smart contract and decentralized application platform.,"
Available online at: https://github.com/ethereum/wiki/wiki/White-Paper/ [Accessed 19/02/2017].
[2] K. Petersen, R. Feldt, S. Mujtaba, and M. Mattsson, “Systematic mapping studies in software
engineering," in Proceedings of the 12th International Conference on Evaluation and Assessment in
Software Engineering, EASE'08, pp. 68-77, BCS Learning & Development Ltd., 2008.
[3] S. Nakamoto, “Bitcoin: A peer-to-peer electronic cash system," 2008.
[4] X. Xu, C. Pautasso, L. Zhu, V. Gramoli, A. Ponomarev, A. B. Tran, and S. Chen, “The blockchain as
a software connector," in 2016 13th Working IEEE/IFIP Conference on Software Architecture
(WICSA), pp. 182-191, IEEE, 2016.
[5] V. Buterin, “On public and private blockchains," Available online at:
https://blog.ethereum.org/2015/08/07/on-public-and-private-blockchains/ [Accessed 01/03/2017].
[6] N.Szabo, “Formalizing and securing relationships on public networks.," Available online at:
http:// rstmonday.org/ojs/index.php/fm/article/view/548/4691 [Accessed 15/02/2017].
[7] J. Stark, “Making sense of blockchain smart contracts," Available online at:
http://www.coindesk.com/making-sense-smart-contracts/ [Ac-cessed 06/03/2017].
[8] K. Delmolino, M. Arnett, A. Kosba, A. Miller, and E. Shi, “Step by step towards creating a safe smart
contract: Lessons and insights from a cryptocurrency lab," in International Conference on Financial
Cryptography and Data Security, pp. 79-94, Springer, 2016.
[9] V. Morabito, “Smart contracts and licensing," in Business Innovation Through Blockchain, pp. 101-
124, Springer, 2017.
[10] A. Lewis, ”A gentle introduction to smart contracts," Available online at:
https://bitsonblocks.net/2016/02/01/a-gentle-introduction-to-smart-contracts/ [Accessed 25/02/2017].
[11] G. Wood, “Ethereum: A secure decentralised generalised transaction ledger," Ethereum Project
Yellow Paper, 2014.
[12] K. Christidis and M. Devetsikiotis, “Blockchains and smart contracts for the internet of things," IEEE
Access, vol. 4, pp. 2292-2303, 2016.
[13] W. Egbertsen, G. Hardeman, M. van den Hoven, G. van der Kolk, and A. van Rijsewijk, “Replacing
paper contracts with ethereum smart contracts," 2016.
[14] W. Banasik, S. Dziembowski, and D. Malinowski, “Efficient zero-knowledge contingent payments in
cryptocurrencies without scripts," in European Symposium on Research in Computer Security, pp.
261-280, Springer, 2016.
[15] J. Yli-Huumo, D. Ko, S. Choi, S. Park, and K. Smolander, “Where is current research on blockchain
technology?|a systematic review," PloS one, vol. 11, no. 10, p. e0163477, 2016.
[16] K. Bhargavan, A. Delignat-Lavaud, C. Fournet, A. Gollamudi, G. Gonthier, N. Kobeissi, N.
Kulatova, A. Rastogi, T. Sibut-Pinote, N. Swamy, et al., “Formal verification of smart contracts:
Short paper," in Proceedings of the 2016 ACM Workshop on Programming Languages and Analysis
for Security, pp. 91-96, ACM, 2016.

164
[17] G. Bigi, A. Bracciali, G. Meacci, and E. Tuosto, “Validation of decentralised smart contracts through
game theory and formal methods," in Programming Languages with Applications to Biology and
Security, pp. 142-161, Springer, 2015.
[18] C. K. Frantz and M. Nowostawski, “From institutions to code: Towards automated generation of
smart contracts," in 2016 IEEE 1st International Workshops on Foundations and Applications of Self*
Systems (FAS*W), pp. 210-215, IEEE, 2016.
[19] B. Marino and A. Juels, “Setting standards for altering and undoing smart contracts," in International
Symposium on Rules and Rule Markup Languages for the Semantic Web, pp. 151-166, Springer,
2016.
[20] T. Chen, X. Li, X. Luo, and X. Zhang, “Under-optimized smart contracts devour your money," in
2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering
(SANER), pp. 442-446, IEEE, 2017.
[21] F. Idelberger, G. Governatori, R. Riveret, and G. Sartor, “Evaluation of logic-based smart contracts
for blockchain systems," in International Symposium on Rules and Rule Markup Languages for the
Semantic Web,167-183, Springer, 2016.
[22] C. Natoli and V. Gramoli, “The blockchain anomaly," in 15th International Symposium on Network
Computing and Applications (NCA), 310-317, IEEE, 2016.
[23] L. Luu, D.-H. Chu, H. Olickel, P. Saxena, and A. Hobor, “Making smart contracts smarter," in
Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security,
CCS '16, pp. 254-269, ACM, 2016.
[24] A. Juels, A. Kosba, and E. Shi, “The ring of gyges: Investigating the future of criminal smart
contracts," in Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications
Security, CCS '16, pp. 283-295, ACM, 2016.
[25] F. Zhang, E. Cecchetti, K. Croman, A. Juels, and E. Shi, “Town crier: An authenticated data feed for
smart contracts," in Proceedings of the 2016 ACM SIGSAC Conference on Computer and
Communications Security, CCS '16, pp. 270-282, ACM, 2016.
[26] A. Kosba, A. Miller, E. Shi, Z. Wen, and C. Papamanthou, “Hawk: The blockchain model of
cryptography and privacy-preserving smart contracts," in 2016 IEEE Symposium on Security and
Privacy (SP),839-858, IEEE, 2016.
[27] H. Watanabe, S. Fujimura, A. Nakadaira, Y. Miyazaki, A. Akutsu, and J. J. Kishigami, “Blockchain
contract: A complete consensus using blockchain," in 2015 IEEE 4th Global Conference on
Consumer Electronics (GCCE), pp. 577-578, IEEE, 2015.
[28] M. Vukolić, “Rethinking permissioned blockchains," in Proceedings of the ACM Workshop on
Blockchain, Cryptocurrencies and Contracts, BCC '17, pp. 3-7, ACM, 2017.
[29] N. Atzei, M. Bartoletti, and T. Cimoli, “A survey of attacks on ethereum smart contracts (sok)," in
International Conference on Principles of Security and Trust, pp. 164-186, Springer, 2017.
[30] A. Bogner, M. Chanson, and A. Meeuw, “A decentralised sharing app running a smart contract on the
ethereum blockchain," in Proceedings of the 6th International Conference on the Internet of Things,
pp. 177-178, ACM, 2016.
[31] M. Al-Bassam, “Scpki: A smart contract-based pki and identity system," in Proceedings of the ACM
Workshop on Blockchain, Cryptocurrencies and Contracts, BCC '17, pp. 35-40, ACM, 2017.
[32] S. Huh, S. Cho, and S. Kim, “Managing IoT devices using blockchain platform," in 2017 19th
International Conference on Advanced Communication Technology (ICACT), pp. 464-467, IEEE,
2017.
[33] P. N. Carrillo, C. I. Peña, and J. L. d. L. Rosa, “Eurakos next: a cryptocurrency based on smart
contracts," in Ebook: Artificial Intelligence Research and Development, vol. 288 of Frontiers in
Artificial Intelligence and Applications, pp. 221-226, 2016.
[34] H. Watanabe, S. Fujimura, A. Nakadaira, Y. Miyazaki, A. Akutsu, and J. Kishigami, “Blockchain
contract: Securing a blockchain applied to smart contracts," in 2016 IEEE International Conference
on Consumer Electronics (ICCE), pp. 467-468, IEEE, 2016.
[35] A. Third and J. Domingue, “Linked data indexing of distributed ledgers," in Proceedings of the 26th
International Conference on World Wide Web Companion, WWW '17 Companion, pp. 1431-1436,
2017.

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