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Version history for the LLNCS LaTeX2e class
date filename version action/reason/acknowledgements
----------------------------------------------------------------------------
29.5.96 letter.txt beta naming problems (subject index file)
thanks to Dr. Martin Held, Salzburg, AT
subjindx.ind renamed to subjidx.ind as required
by llncs.dem
history.txt introducing this file
30.5.96 llncs.cls incompatibility with new article.cls of
1995/12/20 v1.3q Standard LaTeX document class,
\if@openbib is no longer defined,
reported by Ralf Heckmann and Graham Gough
solution by David Carlisle
10.6.96 llncs.cls problems with fragile commands in \author field
reported by Michael Gschwind, TU Wien
25.7.96 llncs.cls revision a corrects:
wrong size of text area, floats not \small,
some LaTeX generated texts
reported by Michael Sperber, Uni Tuebingen
16.4.97 all files 2.1 leaving beta state,
raising version counter to 2.1
8.6.97 llncs.cls 2.1a revision a corrects:
unbreakable citation lists, reported by
Sergio Antoy of Portland State University
11.12.97 llncs.cls 2.2 "general" headings centered; two new elements
for the article header: \email and \homedir;
complete revision of special environments:
\newtheorem replaced with \spnewtheorem,
introduced the theopargself environment;
two column parts made with multicol package;
add ons to work with the hyperref package
07.01.98 llncs.cls 2.2 changed \email to simply switch to \tt
25.03.98 llncs.cls 2.3 new class option "oribibl" to suppress
changes to the thebibliograpy environment
and retain pure LaTeX codes - useful
for most BibTeX applications
16.04.98 llncs.cls 2.3 if option "oribibl" is given, extend the
thebibliograpy hook with "\small", suggested
by Clemens Ballarin, University of Cambridge
20.11.98 llncs.cls 2.4 pagestyle "titlepage" - useful for
compilation of whole LNCS volumes
12.01.99 llncs.cls 2.5 counters of orthogonal numbered special
environments are reset each new contribution
27.04.99 llncs.cls 2.6 new command \thisbottomragged for the
actual page; indention of the footnote
made variable with \fnindent (default 1em);
new command \url that copys its argument
2.03.00 llncs.cls 2.7 \figurename and \tablename made compatible
to babel, suggested by Jo Hereth, TU Darmstadt;
definition of \url moved \AtBeginDocument
(allows for url package of Donald Arseneau),
suggested by Manfred Hauswirth, TU of Vienna;
\large for part entries in the TOC
16.04.00 llncs.cls 2.8 new option "orivec" to preserve the original
vector definition, read "arrow" accent
17.01.01 llncs.cls 2.9 hardwired texts made polyglot,
available languages: english (default),
french, german - all are "babel-proof"
20.06.01 splncs.bst public release of a BibTeX style for LNCS,
nobly provided by Jason Noble
14.08.01 llncs.cls 2.10 TOC: authors flushleft,
entries without hyphenation; suggested
by Wiro Niessen, Imaging Center - Utrecht
23.01.02 llncs.cls 2.11 fixed footnote number confusion with
\thanks, numbered institutes, and normal
footnote entries; error reported by
Saverio Cittadini, Istituto Tecnico
Industriale "Tito Sarrocchi" - Siena
28.01.02 llncs.cls 2.12 fixed footnote fix; error reported by
Chris Mesterharm, CS Dept. Rutgers - NJ
28.01.02 llncs.cls 2.13 fixed the fix (programmer needs vacation)
17.08.04 llncs.cls 2.14 TOC: authors indented, smart \and handling
for the TOC suggested by Thomas Gabel
University of Osnabrueck
07.03.06 splncs.bst fix for BibTeX entries without year; patch
provided by Jerry James, Utah State University
14.06.06 splncs_srt.bst a sorting BibTeX style for LNCS, feature
provided by Tobias Heindel, FMI Uni-Stuttgart
16.10.06 llncs.dem 2.3 removed affiliations from \tocauthor demo
11.12.07 llncs.doc note on online visibility of given e-mail address
15.06.09 splncs03.bst new BibTeX style compliant with the current
requirements, provided by Maurizio "Titto"
Patrignani of Universita' Roma Tre
30.03.10 llncs.cls 2.15 fixed broken hyperref interoperability;
patch provided by Sven Koehler,
Hamburg University of Technology
15.04.10 llncs.cls 2.16 fixed hyperref warning for informatory TOC entries;
introduced \keywords command - finally;
blank removed from \keywordname, flaw reported
by Armin B. Wagner, IGW TU Vienna
15.04.10 llncs.cls 2.17 fixed missing switch "openright" used by \backmatter;
flaw reported by Tobias Pape, University of Potsdam
27.09.13 llncs.cls 2.18 fixed "ngerman" incompatibility; solution provided
by Bastian Pfleging, University of Stuttgart
04.09.17 llncs.cls 2.19 introduced \orcidID command
10.03.18 llncs.cls 2.20 adjusted \doi according to CrossRef requirements;
TOC: removed affiliation numbers
splncs04.bst added doi field;
bold journal numbers
samplepaper.tex new sample paper
llncsdoc.pdf new LaTeX class documentation
12.01.22 llncs.cls 2.21 fixed German and French \maketitle, bug reported by
Alexander Malkis, Technical University of Munich;
use detokenized argument in the definition of \doi
to allow underscores in DOIs
05.09.22 llncs.cls 2.22 robust redefinition of \vec (bold italics), bug
reported by Alexander Malkis, TUM

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Dear llncs user,
The files in this directory belong to the LaTeX2e package
for Springer's Lecture Notes in Computer Science (LNCS) and
other proceedings book series.
It consists of the following files:
readme.txt this file
history.txt the version history of the package
llncs.cls the LaTeX2e document class
samplepaper.tex a sample paper
fig1.eps a figure used in the sample paper
llncsdoc.pdf the documentation of the class (PDF version)
splncs04.bst current LNCS BibTeX style with alphabetic sorting

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\@writefile{toc}{\contentsline {title}{Search for Structurally Similar Projects of Software Systems}{1}{}\protected@file@percent }
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\bibcite{aleksey2020approach}{1}
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\bibcite{beniwal2021npmrec}{3}
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\gdef \@abspage@last{5}

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\begin{thebibliography}{1}
\providecommand{\url}[1]{\texttt{#1}}
\providecommand{\urlprefix}{URL }
\providecommand{\doi}[1]{https://doi.org/#1}
\bibitem{aleksey2020approach}
Aleksey~Alekundrovich, F., Yurevich, G.G., Aleksey~Michailovich, N.,
Nudezhda~Glebovna, Y.: Approach to the search for software projects similar
in structure and semantics based on the knowledge extracted from existed
projects. In: Computational Science and Its Applications--ICCSA 2020: 20th
International Conference, Cagliari, Italy, July 1--4, 2020, Proceedings, Part
I. pp. 718--733. Springer (2020)
\bibitem{ali2011overview}
Ali, A.M.E.T., Abdulla, H.M.D., Snasel, V.: Overview and comparison of
plagiarism detection tools. In: Dateso. pp. 161--172 (2011)
\bibitem{beniwal2021npmrec}
Beniwal, R., Dahiya, S., Kumar, D., Yadav, D., Pal, D.: Npmrec: Npm packages
and similar projects recommendation system. In: Data Analytics and
Management: Proceedings of ICDAM. pp. 701--710. Springer (2021)
\bibitem{chae2013software}
Chae, D.K., Ha, J., Kim, S.W., Kang, B., Im, E.G.: Software plagiarism
detection: a graph-based approach. In: Proceedings of the 22nd ACM
international conference on Information \& Knowledge Management. pp.
1577--1580 (2013)
\bibitem{nadezhda2019approach}
Nadezhda, Y., Gleb, G., Pavel, D., Vladimir, S.: An approach to similar
software projects searching and architecture analysis based on artificial
intelligence methods. In: Proceedings of the Third International Scientific
Conference “Intelligent Information Technologies for Industry”(IITI18)
Volume 1 3. pp. 341--352. Springer (2019)
\bibitem{nguyen2018crosssim}
Nguyen, P.T., Di~Rocco, J., Rubei, R., Di~Ruscio, D.: Crosssim: exploiting
mutual relationships to detect similar oss projects. In: 2018 44th Euromicro
conference on software engineering and advanced applications (SEAA). pp.
388--395. IEEE (2018)
\bibitem{nguyen2020automated}
Nguyen, P.T., Di~Rocco, J., Rubei, R., Di~Ruscio, D.: An automated approach to
assess the similarity of github repositories. Software Quality Journal
\textbf{28}, 595--631 (2020)
\end{thebibliography}

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@inproceedings{nguyen2018crosssim,
title={CrossSim: exploiting mutual relationships to detect similar OSS projects},
author={Nguyen, Phuong T and Di Rocco, Juri and Rubei, Riccardo and Di Ruscio, Davide},
booktitle={2018 44th Euromicro conference on software engineering and advanced applications (SEAA)},
pages={388--395},
year={2018},
organization={IEEE}
}
@article{nguyen2020automated,
title={An automated approach to assess the similarity of GitHub repositories},
author={Nguyen, Phuong T and Di Rocco, Juri and Rubei, Riccardo and Di Ruscio, Davide},
journal={Software Quality Journal},
volume={28},
pages={595--631},
year={2020},
publisher={Springer}
}
@inproceedings{nadezhda2019approach,
title={An approach to similar software projects searching and architecture analysis based on artificial intelligence methods},
author={Nadezhda, Yarushkina and Gleb, Guskov and Pavel, Dudarin and Vladimir, Stuchebnikov},
booktitle={Proceedings of the Third International Scientific Conference “Intelligent Information Technologies for Industry”(IITI18) Volume 1 3},
pages={341--352},
year={2019},
organization={Springer}
}
@inproceedings{beniwal2021npmrec,
title={NPMREC: NPM Packages and Similar Projects Recommendation System},
author={Beniwal, Rohit and Dahiya, Sonika and Kumar, Deepak and Yadav, Deepak and Pal, Deepanshu},
booktitle={Data Analytics and Management: Proceedings of ICDAM},
pages={701--710},
year={2021},
organization={Springer}
}
@inproceedings{aleksey2020approach,
title={Approach to the Search for Software Projects Similar in Structure and Semantics Based on the Knowledge Extracted from Existed Projects},
author={Aleksey Alekundrovich, Filippov and Yurevich, Guskov Gleb and Aleksey Michailovich, Namestnikov and Nudezhda Glebovna, Yarushkina},
booktitle={Computational Science and Its Applications--ICCSA 2020: 20th International Conference, Cagliari, Italy, July 1--4, 2020, Proceedings, Part I},
pages={718--733},
year={2020},
organization={Springer}
}
@inproceedings{ali2011overview,
title={Overview and comparison of plagiarism detection tools.},
author={Ali, Asim M El Tahir and Abdulla, Hussam M Dahwa and Snasel, Vaclav},
booktitle={Dateso},
pages={161--172},
year={2011}
}
@inproceedings{chae2013software,
title={Software plagiarism detection: a graph-based approach},
author={Chae, Dong-Kyu and Ha, Jiwoon and Kim, Sang-Wook and Kang, BooJoong and Im, Eul Gyu},
booktitle={Proceedings of the 22nd ACM international conference on Information \& Knowledge Management},
pages={1577--1580},
year={2013}
}

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% This is samplepaper.tex, a sample chapter demonstrating the
% LLNCS macro package for Springer Computer Science proceedings;
% Version 2.21 of 2022/01/12
%
\documentclass[runningheads]{llncs}
%
\usepackage[T1]{fontenc}
% T1 fonts will be used to generate the final print and online PDFs,
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\begin{document}
%
\title{Search for Structurally Similar Projects of Software Systems}
%
%\titlerunning{Abbreviated paper title}
% If the paper title is too long for the running head, you can set
% an abbreviated paper title here
%
\author{Aleksey Filippov\inst{1}\orcidID{0000-0003-0008-5035} \and
Julia Stroeva\inst{1}\orcidID{0009-0003-8026-235X}}
%
\authorrunning{A. Filippov, J. Stroeva}
% First names are abbreviated in the running head.
% If there are more than two authors, 'et al.' is used.
%
\institute{Department of Information Systems, Ulyanovsk State
Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, Russia}
%
\maketitle % typeset the header of the contribution
%
\begin{abstract}
The authors have developed an approach to the search for structurally similar projects of software systems. Teachers can use the proposed approach to search for borrowings in the works of students. The concept behind this proposal is that it can to locate projects that students have used as parts of a current project.
The authors propose a new algorithm for determining the similarity between the structures of software projects. The proposed algorithm is based on finding similar structural elements in the source code of the program in an abstract syntax trees analyzing.
The authors developed a software system to evaluate the proposed algorithm. The current version of the system only supports Java programs. However, the system operates with its own representation of the abstract syntax tree, which allows you to add support for new programming languages.
\keywords{source code \and structure analysis \and structurally similar projects \and hashing.}
\end{abstract}
%
%
%
\section{Introduction}
Currently, the most practical work of students in information technology includes laboratory and coursework. These classes help students understand the theoretical information from their lectures.
Typically, student work is a small program that solves typical problems. In most cases, these works contain few files or a few lines of code. The architecture and algorithms of such programs are also simple.
The teacher needs to spend many time to check all the work. The teacher usually notices when the student has borrowed a program source code. Students in such cases do not change the structure of the borrowed source code, but rename variables or change types of loops (from \textit{for} to \textit{while}), etc.
The software system proposed in this article allows you to analyze the structure of projects and provide information about their structural similarity. The indicator of the uniqueness of the current project structure is used to evaluate the uniqueness of the project in comparison with other projects.
\section{State of the art}
There are no universal methods for analyzing the source code of software systems at the moment. Certain methods of analysis are used to solve various problems.
There is a group of methods for analyzing source code, which is based on obtaining and analyzing abstract syntax trees (AST). An AST is an abstract representation of the grammatical structure of a source code. It expresses the structure of a program in some programming language as a tree structure. Each AST node is an operator or a set of operators of the analyzed source code. The compiler generates an AST because of the parsing step. Unlike a parse tree, an AST does not have nodes or edges for syntax rules that do not affect the semantics of the program (for example, grouping brackets).
It can also analyze projects using call graph generation tools, such as \textit{CodeViz} or \textit{Egypt}. It is possible to use some functions of reverse engineering tools, such as IDA Pro.
AST-based approaches can find structurally similar projects. However, such approaches have high computational complexity \cite{nguyen2018crosssim}. Many existing approaches analyze a larger number of parameters than is necessary to solve the problem of this study \cite{aleksey2020approach,beniwal2021npmrec,nadezhda2019approach,nguyen2018crosssim,nguyen2020automated}: project dependencies, the number of stars in the repository, the contents of the documentation, etc.
The paper \cite{ali2011overview} presents an analysis of approaches and software tools for searching for borrowings in the text and source code. However, there is no mention of software tools for searching for borrowings in the source code.
In the article \cite{chae2013software}, the authors analyze borrowings in the source code according to the sequences of using external programming interfaces and the frequency of such calls. This method is not suitable for solving the problem of this study because of the educational orientation of the analyzed source code.
Thus, it is necessary to develop an approach to the search for structurally similar projects, which are focused on working with simple software systems and with a high speed of analysis.
\section{The Proposed Algorithm for Analyzing the Structure of the Source Code}
The source code of the software system in the proposed algorithm is the main source of data for identifying structural features.
We formed an AST to analyze the source code. There are various libraries and tools for all existing programming languages for the formation of AST. Thus, using your own representation of the AST allows you to add support for new programming languages to the system without changing the analysis algorithms.
We will use the following AST model:
\begin{equation*}
AST = \langle N,R \rangle,
\end{equation*}
where $N = \lbrace N_{1}, N_{2},\ldots, N_{n}\rbrace$ is the set of nodes AST;
$N_{i} = \langle name, data \rangle$ is an i-th AST node containing the node name, node data;
R is the set of relations between AST nodes.
We developed an algorithm to highlight the structure of the project in analyzing the source code, which comprises the following steps:
\begin{enumerate}
\item Form an ASD for the project.
\item Select nodes with type “Class”:
\begin{equation*}
N^{Class} = \lbrace N_{i} \in N | F \left( N_{i}.data \right) = \text{'Class'} \rbrace,
\end{equation*}
\item Find nodes with the “Class field” type in the found classes:
\begin{equation*}
N^{Vars} = \lbrace N_{i}^{Class} \in N^{Class} | F \left( N_{i}^{Class}.data \right) = \text{'Field'} \rbrace,
\end{equation*}
\item Find nodes with the “Methods” type in the found classes:
\begin{equation*}
N^{Methods} = \lbrace N_{i}^{Class} \in N^{Class} | F \left( N_{i}^{Class}.data \right) = \text{'Method'} \rbrace,
\end{equation*}
\item Find nodes with type “Method Argument” in the found methods:
\begin{equation*}
N^{MethodsArgs} = \lbrace N_{i}^{Methods} \in N^{Methods} | F \left( N_{i}^{Methods}.data \right) = \text{'Arg'} \rbrace,
\end{equation*}
\item Find nodes with the type “Operator” in the found methods:
\begin{equation*}
N^{MethodsOps} = \lbrace N_{i}^{Methods} \in N^{Methods} | F \left( N_{i}^{Methods}.data \right) = \text{'Operator'} \rbrace,
\end{equation*}
\item Create based on previously got sets of AST for the analyzed source code, considering the set of relations R.
\item Save the resulting AST in a graph database (GDB) to facilitate data handling.
\end{enumerate}
Figure \ref{fig1} shows an example of the source code and the ASD got for it.
\begin{figure}
\includegraphics[width=\textwidth]{SourceCodeAndAST.png}
\caption{Sample source code and its AST.} \label{fig1}
\end{figure}
GDB is a non-relational type of database based on the topographic structure of the network. Graphs represent sets of data as nodes, edges, and properties. Relational databases provide a structured approach to data. GDBs are more flexible and focused on fast data acquisition, considering various types of links between them.
We used Neo4j as the GDB, since this system has a high speed of operation even with a large amount of stored data.
\section{The Proposed Algorithm for Determining the Structural Similarity of Software Projects}
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\section{State of the art}
\subsection{A Subsection Sample}
Please note that the first paragraph of a section or subsection is
not indented. The first paragraph that follows a table, figure,
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\paragraph{Sample Heading (Fourth Level)}
The contribution should contain no more than four levels of
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% \begin{figure}
% \end{figure}
\begin{table}
\caption{Table captions should be placed above the
tables.}\label{tab1}
\begin{tabular}{|l|l|l|}
\hline
Heading level & Example & Font size and style\\
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Title (centered) & {\Large\bfseries Lecture Notes} & 14 point, bold\\
1st-level heading & {\large\bfseries 1 Introduction} & 12 point, bold\\
2nd-level heading & {\bfseries 2.1 Printing Area} & 10 point, bold\\
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\end{table}
\begin{itemize}
\item
\end{itemize}
\begin{enumerate}
\item
\end{enumerate}
\noindent Displayed equations are centered and set on a separate
line.
\begin{equation*}
N^{Class} = \lbrace N_{i} \in N | F \left( N_{i}.data \right) = \text{'Class'} \rbrace,
\end{equation*}
Please try to avoid rasterized images for line-art diagrams and
schemas. Whenever possible, use vector graphics instead (see
Fig.~\ref{fig1}).
% \begin{figure}
% \includegraphics[width=\textwidth]{fig1.eps}
% \caption{A figure caption is always placed below the illustration.
% Please note that short captions are centered, while long ones are
% justified by the macro package automatically.} \label{fig1}
% \end{figure}
\begin{theorem}
This is a sample theorem. The run-in heading is set in bold, while
the following text appears in italics. Definitions, lemmas,
propositions, and corollaries are styled the same way.
\end{theorem}
%
% the environments 'definition', 'lemma', 'proposition', 'corollary',
% 'remark', and 'example' are defined in the LLNCS documentclass as well.
%
\begin{proof}
Proofs, examples, and remarks have the initial word in italics,
while the following text appears in normal font.
\end{proof}
For citations of references, we prefer the use of square brackets and consecutive numbers. Citations using labels or the author/year convention are also acceptable. The following bibliography provides a sample reference list with entries for journal
articles~\cite{Reviewer-Recommender}, an LNCS chapter~\cite{ref_lncs1}, a
book~\cite{ref_book1}, proceedings without editors~\cite{ref_proc1},
and a homepage~\cite{ref_url1}. Multiple citations are grouped
\cite{ref_article1,ref_lncs1,ref_book1},
\cite{ref_article1,ref_book1,ref_proc1,ref_url1}.
\subsubsection{Acknowledgements} Please place your acknowledgments at
the end of the paper, preceded by an unnumbered run-in heading (i.e.
3rd-level heading).
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% ---- Bibliography ----
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% References will then be sorted and formatted in the correct style.
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\bibliographystyle{splncs04}
\bibliography{samplepaper}
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% Author, F.: Article title. Journal \textbf{2}(5), 99--110 (2016)
% \bibitem{ref_lncs1}
% Author, F., Author, S.: Title of a proceedings paper. In: Editor,
% F., Editor, S. (eds.) CONFERENCE 2016, LNCS, vol. 9999, pp. 1--13.
% Springer, Heidelberg (2016). \doi{10.10007/1234567890}
% \bibitem{ref_book1}
% Author, F., Author, S., Author, T.: Book title. 2nd edn. Publisher,
% Location (1999)
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% on Proceedings, pp. 1--2. Publisher, Location (2010)
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