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Enterprise Open Source Software is continuously gaining acceptance in business organizations. This is essentially due to the understanding of the potential benefits deriving from the adoption of OSS project solution. Indeed, Open Source Software solutions offer great opportunities for cost reduction and quality improvement, especially for small and medium enterprises that typically have to address major difficulties due to the limited resources. In this direction it is relevant understand and gain knowledge regarding the evolution of such software over systems the time. This paper report results of an empirical study aimed at analyzing the evolution of most relevant ERP open source system during their lifetime.
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Procedia Computer Science 64 ( 2015 ) 924 931
1877-0509 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of SciKA - Association for Promotion and Dissemination of Scientific Knowledge
doi: 10.1016/j.procs.2015.08.609
ScienceDirect
Available online at www.sciencedirect.com
Conference on ENTERprise Information Systems / International Conference on Project
MANagement / Conference on Health and Social Care Information Systems and Technologies,
CENTERIS / ProjMAN / HCist 2015 October 7-9, 2015
Understanding Enterprise Open Source Software Evolution
Lerina Aversano*, Marco Di Brino, Daniela Guardabascio, Marcello Salerno and
Maria Tortorella
Department of Engineering University of Sannio
P.zza Roma 21, 82100 Benevento, Italy
Abstract
Enterprise Open Source Software is continuously gaining acceptance in business organizations. This is essentially due to the
understanding of the potential benefits deriving from the adoption of OSS project solution. Indeed, Open Source Software
solutions offer great opportunities for cost reduction and quality improvement, especially for small and medium enterprises that
typically have to address major difficulties due to the limited resources. In this direction it is relevant understand and gain
knowledge regarding the evolution of such software over systems the time. This paper report results of an empirical study aimed
at analyzing the evolution of most relevant ERP open source system during their lifetime.
© 2015 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of SciKA - Association for Promotion and Dissemination of Scientific Knowledge.
Keywords: Software evolution; Empirical study; Open Source Software; Enterprise Resource Planning.
1. Introduction
Enterprise Resource Planning Open Source software promises significant benefits to organizations. They include
lowering costs, reducing inventories, increasing productivity, improving operational efficiency and achieving
competitive advantages. In this context, it is relevant to gain a deep knowledge regarding the way these software
* Corresponding author. Tel.: +39 0824 305551.
E-mail address: aversano@unisannio.it
© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of SciKA - Association for Promotion and Dissemination of Scientific Knowledge
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Lerina Aversano et al. / Procedia Computer Science 64 ( 2015 ) 924 – 931
systems are evolving during their lifecycle. Specifically, this issue has been more generally addressed in the software
engineering research area but it still needs a deep analysis with reference to the ERP Open Source Software.
It is widely recognized that the software systems continue to evolve after the first version has been distributed.
Numerous studies indicate that the costs associated with software maintenance and evolution are at least 50%, and
sometimes more than 90% of the total costs associated with a software system. As a consequence, both managers
and developers must understand the factors that drive software evolution and take proactive steps that facilitate
changes and ensure that the software systems do not decay. On the other hand, even adopters need to understand if
the systems are adequately maintained during their evolution.
Currently there is the availability of repositories of large open source applications with lifetimes that exceed 20
years. Then, the empirical study presented in this paper aims to leverage software evolution data contained in
historic program versions, and to obtain a clearer image of the software evolution process. To this end, the complete
release histories of the major ERP open source systems, such as OpenBravo, Odoo, Dolibarr, Adempiere and so on,
have been analyzed. The remainder of this paper is organized as follows. Section 2 analyses existing research work
related to software evolution. Section 3 provides a description of the design of the empirical study. Section 4
describes the results of the evaluation of ERP OSS projects. Concluding remarks are given in the last section.
2. Related work on software evolution
The development of a theory of software evolution is a relevent research and several empirical studies of
software evolution have been proposed in the literature. However, it is encouraging to see that the empirical study
on the Open Source evolution has recently become a topic of interest.
M. Lehman and colleagues have proposed the main reference studies on software evolution over a 30-year period
dating back to the mid-1970. The studies have given rise to eight laws of software evolution, as formulated and
refined by Lehman and colleagues1,2,3. These laws are the result of careful and challenging empirical studies of the
evolution of large-scale software systems found in a variety of corporate-based settings.
Other studies have also been conducted and found to yield consistent growth models. The data is summarized as
a set of growth curves3. In plotting these growth curves as graphs, the size of the system (e.g., measured in terms of
number of modules) after the first release is analyzed with reference to the sequence number of the software release.
The analysis suggests that, during its evolution, a system tracks a growth curve that can be approximated either as
linear or inverse-square model8 within phases of the lifetime of an application, separated by transitions. The
combined patterns can be interpreted as “S” curves, with phases of growth in size followed by less rapid growth
(even stagnation) and transitions to another growth phase. Thus, these data/curves explicate conformity to the first
(continual change), second (increasing complexity) and sixth (continual growth) laws, in that they suggest continual
adaptation via incremental growth, and the system complexity controls the growth rate in a constant/bounded (linear
or inverse-square) manner. The third, fourth and fifth laws have been refined to take into account the new
observations. The seventh law addressing quality could not be directly observed within the data, but may conform to
the observations made by Lehman and colleagues regarding these systems. The eighth law (feedback system) is a
synthesis of the other laws. The support to each of the other laws strengthens the eight. In general, in the most recent
studies by Lehman and colleagues, their data set and diversity of data substantiates and supports the original or
refined versions of the laws.
However, it is unclear whether such a data set is a representative sample of the different kinds of software
systems, or whether the laws can be interpreted as providing theoretical guidance for what kinds of software systems
to study.
Other empirical studies have been conducted and published4,6,7. Here, the attention is directed to the Enterprise
software systems category that has been analyzed. This is mainly intended to see if this study of ERP software
category can confirm, refute, or otherwise extend and refine the laws and theory of software evolution.
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3. Design of the study
The study described in this paper followed the same procedure for each analyzed system. First of all, the publicly
available official releases have been downloaded, starting from the most recent one and going back as far as it was
possible. Then, the metrics to be considered for the analysis have been identified. Specifically it has been decided to
observe the evolution of: SLOC- Source Lines of Code, commits, contributors and number of download. These
metrics, indeed, allow a comparison of different point of views, such as: the developers point of view and final user
point of view. Therefore, the metrics evaluated for each system have been collected. The proposed empirical study
concerned several ERP Open Source Software Systems without considering the programming language. In selecting
the software systems, few criteria have been adopted. First, since we are interested in long- term software evolution,
the systems had to have a long release history. Second, the ERP systems had to be sizable, so we could understand
the issues appearing in the evolution of realistic, multi-developer software. Third, the ERP systems had to be
actively maintained. Finally, the ERP systems had to have a high number of download.
Table 1 presents the download data for ERP Open Source Systems. Specifically, the second and third columns
present the number of download, and data of the last updated release, respectively.
Table 1. ERP Open Source Software selected.
Project Download 2014 Last Update
Viger CRM 370.869 19-02-2015
SugarCRM 214.612 15-12-2014
Dolibarr ERP – CRM 188.635 27-12-2014
Openbravo 101.708 24-02-2015
xTuple ERP: Postbooks 96.092 23-03-2015
Adempiere ERP 83.720 02-03-2015
Project Open 60.475 07-03-2015
CiviCRM 55.491 17-03-2015
Web ERP 41.342 06-02-2015
EPESI 25.914 16-03-2015
Opentaps 24.606 01-11-2013
Opencrx 20.116 24-02-2015
Jfire 17.628 25-04-2013
Vienna Advantage 15.554 05-03-2015
LedgerSMB 12.847 17-01-2015
MyIT CRM 8.119 21-01-2012
We aimed to analyze complete lifespans for each application, from the first publicly available release to the latest
release as of March 2015.
A first aspect observed in the study regards the fact that the selected projects are all recently updated, with few
exceptions among the less popular projects. This data confirms the point of view that the most successful products in
open source software are those that have an active community behind, following the project and frequently updating
it.
A second interesting finding concerns the fact that the two most common systems are purely CRM solutions,
which have a very significant number of downloads, also in relation to the most popular ERP solutions.
For gathering the data from the project repository, the Openhub.net has been used. It is an online platform that
deals with the automated retrieval of information from the repository of all the most important open source projects.
These data were integrated with data from two extraction metrics tools, which are Statsvn and Gitstats.
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Open HUB, formerly known as Ohloh, is a suite of web services providing an online community platform, with
the goal of keeping track of the development of open source software systems. It was founded in 2004 by two
former Microsoft manager, and more than 650,000 projects have been tracked in September 2014. Open HUB
provides statistics about the projects, their licenses and software metrics: such information is made available thanks
to a preliminary work of automatic retrieval of information from the versioning systems.
StatSVN is a tool written entirely in Java that allows the easy retrieval of information from the Subversion
repository. It generates a set of charts and tables that describe the progress of the development process within the
repository, such as the activities of the various contributors, changes to files and other useful metrics to analyze the
work done on the repository in the course of his life.
Gitstats is a generator of statistics for Git repository. It analyses the repository and produces as output a series of
tables and graphs available as HTML files.
4. Results
The data in Openhub allowed to easily retrieve a lot of information of interest to the selected projects. Wishing to
proceed to a first analysis of the sample, the data collected in Table 2 allow to make important considerations,
especially if integrated with those already presented in Table 1. First of all, it can be observed as most popular ERP
software systems, with the exception of Dolibarr, are large systems which have a significantly high number of
SLOC (> 2.000.000). Consistent with this data, such systems are those that tend to exhibit greater activity on the
repositories with a number of contributors greater than 80 and a number of commits greater than 10.000. However,
there are some anomalous data, such as that relating to commits SugarCRM, far lower than that of most of the
projects analyzed and the already mentioned Dolibarr ERP solution that appears to be the most downloaded but it
presents a number of SLOC less than 500.000 . Figure 1 depict the trend of the lines of code of most popular ERP
systems.
Fig. 1. Total lines of code excluding comments and blank lines
Regarding the number of contributors, the study aimed at understanding if the activities is evenly distributed
among all contributors or whether there are contributors who perform a significant amount of work, more than
others on a given repository. To explore this aspect, a fuller analysis of some projects with tools StatSVN and
GitStats has been executed, depending on the VCS used, and it has been seen that, for many analyzed projects, the
number of developers significantly active on the repository was a very small fraction of the total of the developers.
In particular, the number of commits were analyzed, together with the minimum number of contributors who had
made at least 80% of the number of commits in the repository. The obtained results are shown in Table 3. The
analysis involved two projects not indexed on SourceForge but fairly popular in the field of open source applications
Enterprise: ErpNExt and Apache OFBiz.
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Table 2. Data related to all the repository history for the ERP and CRM
Table 3. Main contributors of the projects
Tables 2 and 3 show that in all the analyzed cases, the number of developers that have carried out 80% of
commits on the repository is a very small fraction of the total number, often below 10%. This allows us to assert that
in the analyzed Enterprise Open Source Projects the work is done mainly by few developers, who are also the ones
that tend to work more on the ongoing project, while a significant number of contributors gives a limited support to
the repository.
For a more complete analysis and to understand which of the projects presented an ongoing activity over time,
data relating to activities executed in the past 12 months have recovered from OpenHub.net. Table 4 shows these
data. The projects with a greater popularity are those that have a higher activity in the last 12 months, with a
Project SLOC Contributors Commits
CRM Systems
Vtiger CRM 2.007.507 23 8195
Sugar CRM 903.670 11 53
CiviCRM 2.190.005 511 49.384
Myit CRM 132.344 4 85
ERP Systems
Dolibarr 320.194 139 45.126
Openbravo 7.195.468 129 29.337
Postbooks 2.305.663 90 28.627
Adempiere 4.090.334 84 8.098
Project Open 2.450.200 41 14.523
webERP 677.877 28 18.503
EPESI 610.358 14 7.184
opentaps 1.352.015 29 10.788
opencrx 3.648.970 8 6.981
Jfire 870.254 27 19.419
Vienna Advantage 1.057.690 2 106
LedgerSMB 124.009 20 6.426
Project Total Number of contributors Main contributors (80% of
commits)
Adempiere 66 6
Dolibarr 60 3
SugarCRM 7 2
EPESI 12 3
ErpNext 26 3
LedgerSB 21 2
CiviCRM 183 16
Postbooks 34 4
OFBiz 28 8
VTiger CRM 29 9
WebERP 26 3
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significant number of contributors and commits: such projects are stable in terms of annual trend or increasing.
Conversely, little or no activity exists in the last 12 months for the less popular projects.
These data are also made explicit by the trend that almost always commits a stable trend or growth projects and
popular and in decline for those less downloaded. Generally, projects prevail with a decreasing number of commits.
Table 4. Activities in the various repositories over the past 12 months
Fig. 2 Number of commits made to the project source code each month.
The number of contributors, and its evolution in time, differs significantly between the different projects: the only
project that maintain a number of contributors constant in time is OpenBravo, which is also the largest system in
terms of SLOC among those analyzed: this could highlight how large projects are more easily followed by a number
Project Contributors
last 12months
Commits last
12 months
Changed
Files
Added
Lines
Removed
Lines
Commits
trends
CRM
Vtiger CRM 1 13 8.861 998.308 705.824 Increasing
Sugar CRM 1 1 192 3.373 1.636 Decreasing
CiviCRM 266 9.518 8.613 1.056.75 3 799.878 Stable
ERP
Dolibarr 78 5.089 5.911 822.700 600.261 Stable
OpenBravo 41 3.664 3.295 3.051.76 6 877467 Increasing
Postbooks 39 3.745 7.580 7.198.54 3 1.481.96 5 Stable
Adempiere 10 483 8.663 7.393.06 8 3.364.02 7 Stable
Project Open 6 1.087 661 39.604 19.396 Stable
webERP 9 1.029 1.274 130.246 85.057 Decreasing
EPESI 5 534 904 61.665 35.309 Increasing
opentaps 0 0 0 0 0 Decreasing
opencrx 1 4 1.454 73.144 49.826 Decreasing
Jfire 0 0 0 0 0 Decreasing
Vienna Advantage 0 0 0 0 0 Decreasing
LedgerSMB 8 1.356 571 56.003 64.533 Increasing
930 Lerina Aversano et al. / Procedia Computer Science 64 ( 2015 ) 924 – 931
of people who tends to remain constant over time. Instead, other projects, such as Vtiger and PostBooks, present a
decreasing number of contributors.
In the case of projects like Dolibarr, WebERP and CiviCRM, the number of contributors presents a constant
increasing. In the case of Dolibarr, it is interesting to note that, although the system is among the smallest in terms of
SLOC, it presents a growing number of contributors. Considering the fact that this system is extremely popular, it
can be assumed that the project evolves, probably supported by the positive feedback from the high number of users
who downloaded this system (see Table 1).
To explore this aspect, Figure 3 shows the number of downloads for Dolibarr over the years. It is interesting to
note that the trend of contributors reflects in a certain way the download trend. This indicates that the two
phenomena are somehow connected. Indeed, in the software development, open source community of developers
and final users have a strong mutual influence and this confirms in some way the previous observation.
Dually, the number of contributors of projects such as Adempiere is decreasing over time and the number of
downloads follows a similar trend, as shown in Figure 3 which highlights the evolution of contributors and
downloads of Adempiere.
Fig. 3. Dolibarr and ADempiere: number of contributors and download
Analyzing the results obtained with StatSVN, it has been possible to observe a direct analogy with the research
on software evolution of Godfrey5. Indeed, the analyzed systems tend to concentrate the greatest number of changes
to a few files. Specifically, the number of files with a particularly high number of revision, is limited, and the
number of revisions for files rapidly decreases. In addition, these changes are often related to the management of
orders, that would lead to think that these files are the ones that contribute most significantly to the activities on the
repository, undergoing frequent changes.
The order management functionality is definitely reference as a core business for the ERP systems and
consequently it is likely that it is more susceptible to changes.
5. Conclusions
This paper proposes an analysis and comparison of some popular open source ERP and CRM solutions. The
results of this study highlighted some important aspects summarized in the following.
(a) Dolibarr contributors (b) Dolibarr downloads
(c) ADempiere contributors (d) ADempiere downloads
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The most successful projects are those that have a more intense activity in the last 12 months.
The development work is not uniformly distributed among the various contributors, as few contributors tend to
make the large part of the work.
The study also showed that for some projects the number of contributors is connected to the popularity of the
project, confirming that in the open source community the final users represents a motivation to concrete
improvement of the software product, thanks to the direct interaction with the developers.
There is a limited set of files that are subject to significant changes made over time on a project, specifically these
are the files belonging to the core business functions of Enterprise systems such as order management.
Only a small subset of the analyzed projects presents a growing number of commits in the last year analyzed.
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3. Lehman, M. M.,"On Understanding Laws, Evolution, and Conservation in the Large-Program Life Cycle". Journal of Systems and Software
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... Out of 98 primary studies, Linux, Apache, Mozilla and Eclipse open source projects are commonly selected by 15, 15, 13 and 8 studies as shown in Table 10. The major motivation for the selection of open source case studies is their free availability and continuous [73,120,121,126] Conference (ICSE) [40,60,76,82,83] Conference (SEAA) [74] Conference (CSMR) [36,38,49,59,109,112] Conference (WCE) [75] Conference (SEN) [37,114] Conference (PMSE) [77] Journal (IEE Software) [105,106] Journal (JIPS) [78] Conference (ESME) [43,72,113] Conference (WASET) [79] Journal (JSS) [44,99] Conference (MSR) [80] Journal (IST) [45,65] Conference (SSM) [81] Workshop (IWMSR) [48,53] Conference (ESEM) [85] Workshop (IWPSE) [33,107,110,129] Conference (OOPL) [95] Conference (Testing) [46] Workshop (FSE) [96] Journal (Software Quality) [47] Journal (IJOSSP) [97] Conference (ICSTE) [50] Journal (ESE) [98] Conference (WCRE) [51] Conference (IWPSE) [100] Conference (ICPC) [52] Conference (EIS) [101] Conference (OSS) [55] Conference (EAIT) [102] Conference (ICSEA) [56] Journal (ToSEM) [104] Conference (CSSP) [57] Conference (ICSM) [108] Journal (TMIS) [58] Conference (WCSMR) [109] Journal (SCP) [64] Conference (ISSDM) [111] Conference (ICACT) [66] Journal (IJHIT) [118] Conference (ICEMIS) [119] Conference (ISSRE) [127] Conference (ICACCI) ...
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The paper presents interpretations of some recently discovered laws of evolution and conservation in the largeprogram life cycle.Program development and maintenance processes are managed and implemented by people; thus in the long term they could be expected to be unpredictable, dependant on the judgments, whims, and actions of programming process participants (e.g., managers, programmers, and product users). Yet, observed, measured, and modeled regularities suggest laws that are closer to biological laws or those of modern physics than to those currently formulated in other areas subject to human influence (e.g., economics and sociology).After a brief discussion of the first four laws, to highlight underlying phenomena and natural attributes of the program evolution process, the paper concentrates on a fifth law and shows how, and why, this law represents a conservation phenomenon: the Conservation of Familiarity.
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Most studies of software evolution have been performed on systems developed within a single company using traditional management techniques. With the widespread availability of several large software systems that have been developed using an “open source” development approach, we now have a chance to examine these systems in detail, and see if their evolutionary narratives are significantly different from commercially developed systems. The paper summarizes our preliminary investigations into the evolution of the best known open source system: the Linux operating system kernel. Because Linux is large (over two million lines of code in the most recent version) and because its development model is not as tightly planned and managed as most industrial software processes, we had expected to find that Linux was growing more slowly as it got bigger and more complex. Instead, we have found that Linux has been growing at a super-linear rate for several years. The authors explore the evolution of the Linux kernel both at the system level and within the major subsystems, and they discuss why they think Linux continues to exhibit such strong growth
Article
Terms-Software evolution,The difference equation determining evolutionary growth of (some) software systems is generalized to a differential one. A hypothetical geometric model is derived and its possible uses are illustrated.
Article
By classifying programs according to their relationship to the environment in which they are executed, the paper identifies the sources of evolutionary pressure on computer applications and programs and shows why this results in a process of never ending maintenance activity. The resultant life cycle processes are then briefly discussed. The paper then introduces laws of Program Evolution that have been formulated following quantitative studies of the evolution of a number of different systems. Finally an example is provided of the application of Evolution Dynamics models to program release planning.
Value Derived from Open Source is a Function of Maturity Levels
  • P Carbone
Carbone, P., "Value Derived from Open Source is a Function of Maturity Levels, " in OCRI Conference -Alchemy of open source business, 2007.
Evolution and growth in large software projects
  • J J Amor
  • J M Gonzalez-Barahona
  • Herraiz I Robles
Amor, J. J., Gonzalez-Barahona J. M., and Herraiz I. Robles, G., "Evolution and growth in large software projects," in Proceedings of the 8th International Workshop on Principles of Software Evolution, Lisbona, Portugal, 2005, pp. 165-174.