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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Measuring Enterprise Application Software Interoperability Capability</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Andrius Valatavičius</string-name>
          <email>andrius.valatavicius@mii.vu.lt</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Saulius Gudas</string-name>
          <email>saulius.gudas@mii.vu.lt</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Institute of Data Science and Digital Technologies, Vilnius University</institution>
          ,
          <addr-line>Akademijos 4, Vilnius</addr-line>
        </aff>
      </contrib-group>
      <fpage>104</fpage>
      <lpage>113</lpage>
      <abstract>
        <p>Building automated solutions that ensure enterprise application interoperability requires measuring the capability of the application interoperability. The paper presents an enterprise application software (EAS) interoperability capability evaluation method. The background of the method is a more in-depth look into evaluation potentiality of interoperability by comparing edit distance of web service operations gathered for each enterprise application software. To evaluate the capability of interoperability of few enterprise application software systems (SuiteCRM, ExactOnline, NMBRS, Prestashop) web service operations and objects was compared using edit distance calculations. The edit distances have been calculated to gather data for evaluation potentiality of the interoperability solution.</p>
      </abstract>
      <kwd-group>
        <kwd>Enterprise application interoperability</kwd>
        <kwd>Measurement of interoperability capability</kwd>
        <kwd>Distance calculation</kwd>
        <kwd>Autonomic interoperability component</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Dynamic nature of the business processes causes many problems with the already
developed enterprise architecture and business process models, as well as with
implemented (legacy) applications. Most common scenario when changes in business
forces to replace outdated legacy software by one or multiple new software designed
for some specific business process (i.e., bookkeeping software, enterprise resource
planning system or e-commerce software). Changes in legacy software cause the
problem of EAS integrity and interoperability. Enterprise application software (EAS)
interoperability evaluation methods are highly needed. The value chain can be
optimized when software applications are integrated and interoperable, and this reduces
data inconsistencies and business process redundancies. There are some theoretical
works concerning enterprise application interoperability measurement, but seemingly
no deterministic or probabilistic methods are used in the domain. Most approaches
use empirical observations, questionnaires, objective information, rather than detailed
computational analysis of EAS web service properties.</p>
      <p>
        Some research interoperability evaluation scope is broader and not explained by
deterministic evaluation of EAS interoperability cases [
        <xref ref-type="bibr" rid="ref1 ref10">1, 10</xref>
        ]. The measurement of
applications interoperability potentiality should give the essential indicators for
improving interoperability. We have experimented with few edit distance formulas
(Levenshtein, Jaro-Winkler, Jaccard, and Longest Common Subsequence) for
evaluation of the operation names similarity of different applications. In our approach
interoperability should be evaluated on the stage of architectural design of the
interoperability solution by comparing names of the web service operation using
existing edit distance methods.
      </p>
      <p>We propose that interoperability capability evaluation should be carried out at the
stage of the web service architecture analysis by comparing names of the web service
operations. Applications interoperability capability is measured by comparing the
names of the different web service transaction operations of the (integrated) systems:
if the Transaction1 identifier is the same as the Transaction2 identifier, then the
estimate is 100%. This research is limited to enterprise applications developed using
service-oriented architecture and focuses on EAS that use web services over SOAP,
and RESTful protocol for data transfer. When REST web service meta-data
description is not standardized, it is more complicated to extract meta-data for
interoperability evaluation. The interoperability capability of software systems
(SuiteCRM, ExactOnline, NMBRS, PrestaShop) has been measured experimentally
by comparing web service operations using edit distance calculations. The primary
assumption in this research paper, that interoperability should be evaluated by
comparing web service meta-data (i.e., operation names, objects, object field names,
object types, and finally object values) using edit distance calculations. The EAS
interoperability measurement serves as a basis for improving interoperability methods.</p>
      <p>This paper is structured as follows. In the second section, we provide the basic
concepts of interoperability capability evaluation. In the third section, we present
related works and test out provided solutions within our environment setup. In the
fourth section, the architecture of interoperability evaluation system is laid out. In the
fifth section, the experiment environment is described, and interoperability capability
measurement experiment is explained. The interoperability capability evaluation
autonomic component is laid out in the seventh section. Finally, conclusions, cover the
brief overview of results and summarize the experiment.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Basic Concepts</title>
      <p>
        Interoperability is the ability of different computer systems, applications or services to
communicate, share and exchange data [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ]. Therefore, for EAS to be interoperable,
they must be designed using SOA (Service-oriented architecture). The central
principle of SOA is to have a system design that it would be internally a black-box
providing description about its inputs and outputs so that user of such system would be able
to interact with it [12 - 330p]. Such interactive systems can use each other's input and
output to become interoperable, but there are several barriers. EAS interoperability
barriers are defined in European integration framework [
        <xref ref-type="bibr" rid="ref1 ref8">8, 1</xref>
        ].
2.1
      </p>
      <p>
        Interoperability Barriers and Areas
The problem of interoperability solutions is divided into barriers and areas. European
integration framework (EIF) identifies interoperability barriers (technical, semantical,
organizational and legal) [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ]. Interoperability areas [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]: data, services, processes, and
business.
      </p>
      <p>We focus mainly on evaluating interoperability capability of EAS in areas of
services and data by tackling semantical barriers. The Interoperability area of data:
covers different issues of the heterogeneous data integration from diverse sources with
different schemas. The Interoperability area of services: covers different issues of the
heterogeneous data encapsulated by web-services of applications that designed and
implemented independently.
2.2</p>
      <p>Other Interoperability Problems
Multiple problems arise when trying to achieve EAS interoperability in a dynamic
business environment. Most of EAS are also dynamic – their schema changes over
time. The schema is a formal data structure description in a language understandable
by database management system or the application using it. Structural changes in
EAS impact business process and previous business process models become invalid.
There are no methods to autonomically evaluate the potential of interoperability
between EAS over the period.</p>
      <p>
        To ensure EAS can be interoperable integration expert needs to perform schema
alignment [
        <xref ref-type="bibr" rid="ref15 ref20 ref21 ref23 ref7">7, 15, 20, 21, 23</xref>
        ]. In the next step, the expert must ensure record linkage
and data fusion [
        <xref ref-type="bibr" rid="ref11 ref3">3, 11</xref>
        ]. The expert then orchestrates jobs – the timing of each data
migration component and ensures the choreography of application services and data
objects – sequence and order in which applications would exchange data.
2.3
      </p>
      <p>
        Edit Distance to Evaluate EAS Object Similarity
Interoperability potential should be evaluated using EAS web service architectural
design by comparing web service operations and objects and other meta-data. We
used four edit distance [
        <xref ref-type="bibr" rid="ref17">17</xref>
        ] formulas for object comparison: Levenshtein,
JaroWinkler, Jaccard and Longest Common Subsequence for the similarity of operations
evaluation. Using these calculations, we estimate interoperability capabilities of
multiple EAS.
      </p>
      <p>
        Levenshtein edit distance. Calculates edit distance by a minimum number of single
character edits required to change one word into the other. Levenshtein algorithm was
the first known method developed to compare string distances in 1965 [
        <xref ref-type="bibr" rid="ref13">13</xref>
        ]. For each
character pair from two strings take the minimum amount of changes required to
make the strings identical.
      </p>
      <p>Jaro - Winkler edit distance. Calculates how many transpositions in a string
required to make strings similar. A transposition is when characters of two strings are
exchanged until strings become similar.</p>
      <p>Longest common subsequence edit distance. Takes the sum of characters by
calculating some subsequences that are matched and are longest in the other string.</p>
      <p>Jaccard edit distance. For a given character of each string, a character matrix is
formed where characters for each set represent the total number of characters have the
same value.
3</p>
    </sec>
    <sec id="sec-3">
      <title>Related Works</title>
      <p>
        Various application interoperability methods are applied to maintain interoperability
of enterprise applications. Most researchers of integration subject use advanced
methods such as agent technologies [
        <xref ref-type="bibr" rid="ref18">18</xref>
        ], and ontology-based technologies [
        <xref ref-type="bibr" rid="ref14 ref22">14, 22</xref>
        ].
However sophisticated methods of the process integration already exist [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ], just not being
applied in the application area. In dynamic environment business processes often
needs optimizing, similar as to [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ] examples of business process integration [
        <xref ref-type="bibr" rid="ref19 ref2">2, 19</xref>
        ].
      </p>
      <p>
        Some researchers underlie the guidelines of measurements and give propositions of
what methods should be used for interoperability capability evaluation. One of the
favorite inspirers for this research Kasunic [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ] proposed to evaluate systems
interoperability using three views: Technical, Operational and Systems. A similar approach
to the business and information systems alignment measurement introduced in [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ].
Codes in Table 1 represent the usage of standards above inadequate (R), marginal (Y),
or adequate (G), for the EAS (S1 – ExactOnline, S2 – PrestaShop, S3 – SuiteCRM,
S4 NMBRS). Technical view table (see Table 1, a) indicates that chosen EAS are not
using strong standards. Such method requires a lot of investigation and manual input,
also understanding the technical aspects required for interoperability.
      </p>
      <p>
        The enterprise application software (EAS) interoperability measurement (between
services) is the basis for improving interoperability methods. Some known
interoperability evaluation methods are described by these researchers: Scorecard –
DoD in [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ], I – Score in [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ], and Comparison by functionality in [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ].
      </p>
      <p>These EAS interoperability evaluation methods are not sufficient because the
assessments obtained through questionnaires and expert judgment. We strive to develop
a method that evaluates the characteristics of the systems that is integrated - without
using human input like tests, questionnaires, and experiences. The aim is to use only
characteristics of software: metadata and systems network service architectures.</p>
    </sec>
    <sec id="sec-4">
      <title>Experiment Results</title>
      <p>This research is limited to enterprise applications developed using service-oriented
architecture and mostly focus on software that uses web services and SOAP and
RESTful protocol for data transfer which meta-data is usually described using
standardized documents. Web service operations are compared from four software system
applications for the enterprise: PrestaShop, ExactOnline, NMBRS, and SuiteCRM.
Each application has some distinct roles and aspects in an enterprise:
1. PrestaShop. E-Commerce software system – provides a platform to create a
website to sell products, also deals with the warehouse management by tracking a
remaining number of products.
2. ExactOnline. ERP software system. Accounting and industry software – has more
than one integrated tool such as enterprise resource management ERP, CRM,
accounting.
3. NMBRS. HR-Payroll software system – helps manage and calculate payrolls and
debts.
4. SuiteCRM. It is a customer relationship management software that helps manage
customer relationships by allowing plan meetings look for opportunities, deal with
customers.</p>
      <p>Some meta-data were automatically extracted from these services (therefore can be
automated), other EAS require more efforts to do the extraction, but with careful
rethinking, the meta-data extraction can be automated as well. Using the meta-data of
web services, we counted for each system how many distinct objects are covered by
operations of web services (Fig. 1).
There are 608 distinct objects in considered EAS used in the experiment. On average
EAS has 153 operation entities per system provided by their web service. The
experiment results are the analysis of similarity for each operation name in each EAS
system. If the edit distance for each operation name is high enough, this indicates that
majority of operations are similar in that pair of EAS packages. The Results evaluated
by the outcomes of the edit distance calculations and presented in the form of matrix
M1 – M6 of the using similarity percentage for each EAS object in comparison to
other EAS object. The heatmap of possible interoperability (Fig. 2) shows the edit
distance of operations. The matrixes are repeated multiple times in Fig. 2 because it
represents the same data combination, say Source1 X Source2 = Source2 X Source1.
Consider the matrix M1 of the ExactOnline to NMBRS interoperability evaluation.
Dark gray spots indicate &gt; 85 % operation similarity compared to other operations
(light gray). Dark gray area in matrix also indicate higher probability of operations
being similar (above 50%), (Fig. 2). For example ExactOnline web service object
„AbsenceRegistrations“ matches NMBRS web service object „Absence“ by 60%
using ensemble of edit distance calculation.
In Fig. 2 visible calculations only from one method (Levenshtein), but similar
calculations were carried out for other methods as well (Jaccard, Jaro-Winkler, Longest
common subsequence). We evaluate each of (M1- M6) using the ensemble edit
distance – a combination of all four edit distance calculations, the separate test shows
their similarity by Source X Source2. Light gray cells represent the pairs of objects
that are not similar (values &lt; 50%), Darker gray cells represent more similar pairs
(values &gt;= 50 %). In the visible figure (Fig. 2) web service operations are limited by
top 20 records of Levenshtein distance and merely represent partial scope of the
research done. By comparing results from each edit distance calculations, we can draw
some conclusions: Jaro – Winkler and Longest common subsequence algorithms tend
to evaluate more similar objects around 50 percent; Levenshtein (a) separates more
but does not tend to give very high scores for seemingly similar operations. Jaccard
(c) can separate very distinct operations (much more green area) from very closely
similar operations. Though for similar operations scores are not so high as described
in further examination of the methods.</p>
      <p>For results ensemble method (average of all similarity scores from edit distance
algorithms) was selected to evaluate overall results. Assuming that objects by their
same name are semantically similar, the results of the operations interoperability
show that in ExactOnline (E) and NMBRS (N) there exist operation objects that are
similar. Here is a brief list of example of similarity evaluation: E Addresses – N
Address (85%), E BankAccounts – N BankAccount (91%), E CostCenters – N
CostCenter (90%), E Costunits – N CostUnit (88%), E Departments – N Department
(90%), E Employees – N Employee (88%) and E Schedules – N Schedule (88 %). But
there also operation objects that are confused: E Contacts – N Contract (76%), E
Contacts – N ContractPerson (72%) and E Contacts – N ContractV2 (70%) – these
might actually share some similar data (as names or pointers to the right object), but
need to evaluate from data structure perspective for this operation. Exact online with
NMBRS has 24 operations with result higher than 65%. We could improve by
determining thresholds by enriching objects with schema data and semantic meaning
evaluation trying to avoid mismatching. As can be seen from all objects in ExactOnline
(285) and in NMBRS (130) has only 24 operation objects with possible
interoperability application with similarity score &gt; 65%. Further, compared Exact Online (E) and
PrestaShop (P) where similarity results are above or equal to 70 %. We can see that
full similarity (100%) between few objects is achieved: Addresses; Contacts;
Currencies; Employees; Warehouses. However, one confusion is found at (74%): E Projects
– P products (74%).</p>
      <p>Exact online with PrestaShop has 18 operations with result higher than 70 %. As
can be seen, ExactOnline 285 PrestaShop 72 operations has only 18 operations
possible interoperability with score &gt; 70 % (see Table 2.). Other results are overviewed as
follows and presented in Table 2. The experiment confirms that it is possible to
evaluate the interoperability capability, i.e., identify the pairs of specific operations that
potentially can be interoperable.
20
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      <p>In Fig. 3 the similarity of sources using different edit distance calculations is
depicted, where combinations of each EAS (EAS1 x EAS2) represented in letters E
(ExactOnline), N (NMBRS), P (PrestaShop), S (SuiteCRM) see Fig. 3. Almost all edit
distance algorithms determine the same similarity between the EAS (Fig. 3), except
Jaccard method found PrestaShop and SuiteCRM more similar than ExactOnline than
NMBRS.
The scoring amplitudes are different for each edit distance method because of the
difference of the edit distance calculations implemented by these methods. The lower
the percentage - the more procedures tried to compare. Ultimately the score is lower
because of the different amounts of procedures can be identified as similar by each
edit distance method.
5</p>
    </sec>
    <sec id="sec-5">
      <title>Further Work</title>
      <p>This research is an experimental part of an investigation on autonomic solutions for
application integration in the dynamic business environment using in-depth domain
knowledge. Comprehensive research is still in progress, and this experimental part
reveals essential knowledge on how autonomic component can evaluate whether its
managed application systems are interoperable. What is more, this research provides
the basis for supporting Business Process alignment to Application Processes and may
impact the quality of application interoperability when using business process models.
The idea is that after measuring whether software systems are interoperable, we can,
in theory, measure the alignment to business processes and see which operation fall
outside of business process model.</p>
    </sec>
    <sec id="sec-6">
      <title>Conclusions</title>
      <p>The goal of this research was a preliminary evaluation of the interoperability
capability of different EAS. The lack of automated and deterministic models in the EAS
interoperability capability evaluation inspired to look for interoperability
measurements that can be calculated and not impacted by human input such as surveys. An
attempt to compare the software systems was implemented using extracted meta-data
from API interfaces. This meta-data consisted of operations from which 608 distinct
objects per all EAS were identified. On average 153 objects per single EAS package.</p>
      <p>The measurements of the capability of interoperability were implemented using the
edit distance calculation methods: Jaccard, Jaro-Winkler, Levenshtein, and Longest
Common Subsequence. Methods have a different level of precision estimating not
such similar strings (below 60%).</p>
      <p>The outcome suggests drilling down to characteristics of EAS web-service can be
helpful for determining similar objects which could be integrated. However, this
approach does not include analysis for data structures which could provide even better
results and help evaluate the possible schema – matching issues.</p>
      <p>
        Other methods could be used for analyzing the potential of interoperability such as
text data clustering, NLP methods and Latent Dirichlet allocation [
        <xref ref-type="bibr" rid="ref24">24</xref>
        ]. These and
other methods could add up to the total evaluation score.
      </p>
      <p>The obtained data and use this meta-data for further research in automation and
evaluation of interoperability solutions. This goal was achieved successfully and can
be applied in control loop or as knowledge for autonomic interoperability component.</p>
    </sec>
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