A Web Services Based Framework For Uniform Integration Of Command-Line Bioinformatics Software Tools

International Journal of Web Services Practices, Vol. 4 No.1(2009), pp. 36-43
ISSN 1738-6535 © Web Services Research Foundation
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
Abstract—Life scientists use a variety of bioinformatics
software tools to perform tasks such as annotation of DNA and
protein sequences. Most of these tools are command-line driven
and handle various data types (nucleotide, protein, etc.) and data
formats (Fasta, Genbank, GCG, etc.). As many bioinformatics
software tools are generally involved in analysis tasks, scientists
are more and more requiring that these heterogeneous
bioinformatics tools be integrated in a uniform way. They are also
requiring graphical user interfaces of these tools, and the ability to
compose workflows without much programming effort. In this
paper, we propose a Web services based framework that meets the
above requirements.
Index Terms—Web services, data and tools integration,
biological workflows.
I. INTRODUCTION
IFE science data and application integration and
interoperability are one of the most challenging problems
facing bioinformatics today. Indeed, to enable the discovery of
new biological insights and to create a global perspective from
which unifying principles in biology can be discerned,
scientists have to interpret many types of information from a
variety of sources. These sources include nucleotide and amino
acid sequences, protein domains, protein structures, and gene
expression profiles.
The structure of biological data has its own characteristics
which make it apart from data in other domains. Biological data
exists in the form of terabytes of nucleotide sequence data,
microarray and other image data, and various other forms of
data that result from both experimental and “in silico” research
efforts. Due to this huge amount of data, it is often impossible,
without the support of additional hardware and software
facilities, to interpret and to understand this data.
Manuscript received March 15, 2009.
Elarbi Badidi is an Assistant Professor of computer science at the College of
Information Technology (CIT) of United Arab Emirates University, Maqam
Campus, PO. Box 17551, Al-Ain, UAE. (Phone: 971-3713-5552; Fax: 971– 3
–762 6309; e-mail: ebadidi@ uaeu.ac.ae).
M. Vall Mohamed Salem, is an Assistant Professor of computer science at
the University of Wollongong in Dubai, UAE (e-mail: salem@uow.edu.au).
Salah Bouktif is an Assistant Professor of computer science at the College of
Information Technology (CIT) of United Arab Emirates University, Maqam
Campus, PO. Box 17551, Al-Ain, UAE. (Phone: 971-3713-5523; Fax: 971– 3
–762 6309; e-mail: salahb@ uaeu.ac.ae).
Larbi Esmahi is an Associate Professor at the School for Computing &
Information Systems, Athabasca University, Athabasca, Alberta, Canada
(e-mail: larbie@athabascau.ca).
While genomic data have a well-known representation as
sequences taken from the {A,C,G,T} alphabet, there is no clear
model for data representing the expression products of genes:
proteins and higher forms of organisms e.g., cells and the
multitude of forms they assume in response to environmental
challenges.
To accomplish tasks, such as annotation and manipulation of
DNA and protein sequences, and comparison of genes and
genomes across species, life scientists have to use a variety of
bioinformatics analysis software tools. These tools may use
various data types (nucleotide, protein, taxonomy, etc.) and
data formats (Fasta, Staden, Embl, Genbank, etc.). Most of
them are originally stand-alone, command-line driven, with
textual input and output. Moreover, the types and styles of their
inputs and outputs are similarly variable as there is no
standardization for parameters usage. The lack of graphical
user interfaces (GUI) makes them cumbersome for the end
user.
Another major bottleneck is that most of these software
applications are incompatible with one another as they use
different file formats. As a consequence, the output of one tool
cannot be used as an input for another, without data format
conversion. A further complication is that the user has to define
a multitude of parameters and options according to the
particular data or aim of the analysis. There is no standard way
to describe their input parameters and output results. In this
paper, we use the terms tool and application interchangeably.
In the past few years, two main approaches have been
considered to deal with the issue of bioinformatics tools
integration. The first approach consists in developing and
deploying locally interactive environments in order to facilitate
bioinformatics analyses. Examples of such environments are:
Isys [1], Turbobench [2], and Applab [3]. The drawback of this
approach is that the integration environment as well as the tools
must be installed and configured locally, which requires
substantial IT expertise.
The second approach consists in taking benefit of the
growing use of the Web to make the tools accessible through
Web interfaces using HTML and various scripting languages
(CGI, Perl, etc.) and technologies (Java, RMI, EJB, and
CORBA). Examples of environments adopting this approach
are: Bionavigator [4], NCSA Biology Workbench [5], and
Anabench [6].
The recent development in terms of distributed computing
technologies, have led to the Web and Grid services
technologies, which promise to alleviate the integration and
A Web Services based Framework for Uniform
Integration of Command-line Bioinformatics
Software Tools
Elarbi Badidi, M. Vall Mohamed Salem, Salah Bouktif, and Larbi Esmahi
L

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interoperability issues. In this paper, we present our proposed
Web-services based framework for bioinformatics tools
integration, which allows wrapping applications as Web
services. In contrast to the above frameworks, in which the
tools are accessed only from a Web interface, our framework
will allow accessing application services through a Web portal
as well as programmatically by exporting their WSDL [7] files.
The Web portal may be implemented using various Web
technologies such JSP, ASP, and JSF.
II. RELATED WORK
The trend now is to use Web and Grid services technologies
as well as semantic Web services to solve the integration
problem not only in life sciences but in enterprise (or business)
integration as well. Examples of life sciences frameworks using
these technologies are Soaplab, myGrid, and BioMoby.
Soaplab [8] is a soap-based programmatic interface to
command-line applications on remote computers. Soaplab uses
Apache Axis [9] to create Sun Java implementation classes and
deployment descriptors for all derived analysis services. It uses
CORBA on the server side to find, start, control, and use
applications. Soaplab has been developed within the UK
e-Science initiative as a component of the myGrid [10] project.
myGrid provides high-level open source grid middleware to
facilitate building high level services for data and application
resource integration such as resource discovery, workflow
execution and distributed query processing. The emphasis is on
data integration, and workflow, personalization. Using the
myGrid workflow construction tool Taverna [11], workflows
can be composed with semantic descriptions and published.
BioMoby [12] is an open source project that aims to provide a
framework for the discovery, representation, integration, and
retrieval of biological data from widely disparate data hosts and
analysis services using Web services technology. myGrid and
BioMoby are very ambitious projects that aim to achieve
integration of biological data distributed worldwide in disparate
sources.
Our framework shares the same goals with Soaplab, which is
also designed to provide Web services wrappers for
command-line applications, mainly to the Emboss
bioinformatics package [13]. However, the main difference
between our framework and Soaplab resides in the approach
used for describing input and output of the analysis programs.
In soaplab, the service generation mechanism expects inputs
and outputs described in the ACD language of the Emboss
package, while our service generation expects inputs and
outputs described in XML using our XML schema for tools
description that we have developed. The utilization of XML
and XML Schema greatly reduces the complexity of dealing
with heterogeneous analysis tools.
By developing Web services wrappers for these
command-line tools, we can overcome many of the limitations
mentioned above. By using the Java Architecture for XML
Binding (JAXB), we can implement very easily these Web
service wrappers as well as the user interfaces of the tools from
their XML descriptors. Also, the composition of Web services
using standards such as BPEL [14] will facilitate the
composition of biological protocols.
III. BACKGROUND
A. Command-line interfaces
A command line interface (CLI) is a user interface to a
computer's operating system or a software application in which
the user responds to a visual prompt by typing in a command on
a specified line to perform specific tasks, receives a response
back from the system, and then enters another command, and so
forth. The Unix Prompt and the MS-DOS Prompt in a Windows
operating system is an example of the provision of a command
line interface. CLIs are often used by system administrators and
programmers in engineering and scientific environments. A
CLI is often used when a large vocabulary of commands,
together with a wide range of options, can be entered more
rapidly as text than with a pure GUI. This is typically the case
with operating system command shells.
Today, most users prefer the graphical user interface (GUI)
offered by Windows, Mac OS, and others. Typically, most of
today's Unix-based systems and software applications, such as
MYSQL and MATLAB, offer both a command line interface
and a graphical user interface with the benefits of both.
In a CLI, commands are typically written in a particular way.
For example, the command is typed first with no spaces in the
name. Then after a space, one can sometimes modify the
command by adding what are called “options” or “parameters”.
Options change or limit the way the command is executed.
They are usually preceded by a dash or another symbol. A
command may also include the name of a file or directory that
one wants the command to work on. The finished command
will look something like this.
command -option file
command -option sourceFile destinationFile
Fig. 1. Example of command-line options
A CLI defines a grammar, a set of rules that all commands
within the CLI must follow. This is the case for UNIX
operating system. These rules may be different from one CLI to
another. Therefore, with the heterogeneity of rules, it’s only
through the documentation of the CLI that one can learn how to
run the commands with the right options.
In bioinformatics, several software packages and tools, such
as Emboss provide only a command line interface. Fig. 1
provides a short description of the options that can be used with
the seqret tool of Emboss.
B. Web services in the Life Sciences
With increasing acceptance among software vendors and
rising adoption in the marketplace, Web Services are becoming

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the basis for many Web-based applications. They are
interoperable across platforms and neutral to languages, which
makes them appropriate for access from heterogeneous
environments, enabling mass dissemination of knowledge. In
the life sciences, adopting the Web services technology is seen
as a key to achieve the coordination and interoperability among
incompatible bioinformatics applications available from
different providers, an endeavor that is becoming more and
more significant to biological research.
Within the life sciences community, in which scientists
spend a great deal of their time using various incompatible tools,
accessing remote databases, copying and pasting data to
combine their analyses, converting data formats, and
assembling results in ad-hoc protocols, the service oriented
approach for accessing bioinformatics tools and databases as
services in a standardized fashion has very quickly caught the
interest of several organizations and research centers that have
published their tools as Web services. The National Center for
Biotechnology Information (NCBI;
http://www.ncbi.nlm.nih.gov/) has published its Entrez
Utilities as Web Services. The DNA Data Bank of Japan
(DDBJ; http://www.ddbj.nig.ac.jp/) provides a Web API for
biology (WABI), which includes several services. The
European Bioinformatics Institute Web service (EBI;
http://www.ebi.ac.uk/) provides programmatic access to data
retrieval and analytical tools for several molecular databases.
C. Biological workflows
Complex analysis, annotation, and data integration typically
involves various bioinformatics tools. In the past few years,
several software environments and platforms emerged to
enable, the orchestration, and execution of these tools in
biological workflows. Examples of such systems include
Bionavigator [4], Turbobench [2], Pegasys [15], w3h [16],
G-Pipe [17], Biopipe [18], VIBE [19], Flosys [20], and Pise
[21].
With the current trends towards using Web services
technology in life sciences, new environments and frameworks
have emerged to enable the orchestration and the execution of
biological Web services. The most notable systems include
Taverna (part of the myGrid project) [11] and BioMoby [12] as
mentioned earlier. Moreover, the different standards in the area
of Web services (WS_* standards) in particular the standards
for service composition, including the Business Process
Execution Language for Web Services (BPEL4WS) and the
Business Process Modeling Language (BPML), will allow to
go further in biological data and tools integration.
D. Workflow use case: phylogenetic analysis
A phylogenetic analysis workflow of newly sequenced
protein genes involves the following steps:
1) Translation of the nucleic acid sequence to the
corresponding peptide sequence in six frames (e.g. using
tools such as transeq [13] or ExPASy translate tool [22]),
2) Identification of ORFs (Open reading frame) that
correspond to conserved proteins by similarity search
(e.g. using tools such as blast [23] or getorf [13]),
3) Retrieval of protein sequences from GenBank [24] (e.g.
using Entrez [25] or seqret [13]),
4) Multiple protein alignment (e.g. using clustalw [26]),
5) Extraction of well aligned sequence stretches [27],
6) Tree inferences based on various models of evolution, and
7) Tree testing (e.g. using phylip [28] and consel [29]).
Typically, such analysis pipelines are employed several times
with different data sets or parameters.
IV. FRAMEWORK OVERVIEW
A. Objectives
With the growing interest in data and tools integration in life
sciences and the limited number of integration frameworks
based on Web services, we set out to develop a framework that
allows to:
1) Develop a Web service wrapper around each
command-line tool,
2) Make unified and remotely accessible the interfaces of
these tools,
3) Hide their dependencies on the underlying operating
systems, and
4) Access these tools programmatically in order to be able to
compose workflows describing many biological protocols.
By converting the command-line applications into Web
services, we can overcome many of the limitations and
heterogeneity of styles of these applications we mentioned in
the introduction. In this paper, an application service is an
application with a Web service interface that is described by
WSDL document as collections of network endpoints, or ports.
To wrap a command-line tool as a Web service, we first
describe the tool properties and its parameters in XML. We
then translate the XML specification of the tool, which
describes its parameters, its data types and data formats, into
WSDL, and then create an entry in the UDDI registry [30] to
advertise the WSDL specification. Web services clients can
then look up the WSDL in the registry and interact with the tool
as a Web service. Client applications can be written in various
programming languages.
The XML description of the data types and the data formats
supported by command-line tools greatly reduces the
complexity of their composition into workflows. Two given
tools may be composed in a workflow in a serial fashion
provided that the data type and data format of the first tool
output are compatible with the data types and data formats of
the second tool input. In the case of incompatibility of data
formats, a data format conversion tool, such as readseq [31], is
introduced between the two given tools in the workflow. The
conversion is then performed without manual user intervention
and without data loss. However, readseq is not recommended
for very large (100+MB) sequence files, whether as a single
record or multiple records.
B. System components
The architecture of the system is shown in Fig. 2. It is a
three-tier architecture composed of a client layer providing
presentation logic, a middle-tier layer containing the business

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logic, and a back-end database. Users may interact with the
system through a portal using HTML and JSP (Java Server
Pages) screen forms, for example, or by invoking the
application services programmatically. The requests of the
application services submitted by users at the presentation level
are handled by an application server equipped with a Servlet
and JSP container. Requests may be invocation of individual
services or may be part of a workflow.
The Workflows manager allows the user to compose
workflows from the application services generated from
command-line applications. This may be performed from a user
interface or programmatically given that the input and output
types and formats of applications are described for each
application as we will see in the next section. At the back-end
level, we find the command-line applications, the session
management database which stores information about users’
sessions, and the service registry.
We have designed the system architecture based on the
service oriented architecture principles, and especially on using
XML to describe tools and their parameters. The utilization of
XML and XML schema greatly reduces the system complexity
and deals with the heterogeneity of applications.
Fig. 2. Framework components
The key component of the system is the XML schema we
have developed to describe the applications and their
parameters. This XML schema catches most of the different
situations and cases of applications and parameters. For
instance, with this schema we should be able to describe
various applications that are handling several data types
(nucleotide, protein, taxonomic, etc.), several data formats
(Fasta, Genbank, Embl, etc), as well as heterogeneous
parameters with different types and syntax for assigning values
to the parameters. From the XML description of an application,
we may generate the user interface in the form of HTML and
JSP pages, for example, and the Web service associated to the
application. This is performed by the User Interface generator
and the Web service Generator components. The WSDL of the
application service is then published to the service registry.
C. Bioinformatics tools as Web services
Many platforms are now available to develop Web services
applications. Some of them are commercial products, while
others are freely available, such as Jakarta Tomcat Web server
and the Apache Axis toolkit. Using this toolkit, for example,
one can convert a Java application into a Web service.
To build a Web service for a given tool, we have to write a Java
application to invoke and execute this tool. One can use the
following Java class, described in Fig. 3, to run an application,
which is external to the Java virtual machine (JVM).
Fig. 3: a Java class to run applications external to the JVM.
The method runApplication() requires the name of the
application (name of the executable program), the path to the
application, and the arguments to be passed to the application
(input, output, and other options of the tool).
To illustrate this, we will consider a small tool called infoalign,
which is part of the Emboss package. Infoalign is a small utility
to list some simple properties of sequences in an alignment. The
above code fragment can be converted into a Web service with
the following methods: setInfoalignInput(),
setInfoAlignOutput(), setInfoAlignOptions(), and
runInfoalign(). A WSDL file for this Web service will be
automatically created. This feature is provided by most Web
services development platforms. This file may be accessed, for
example, from:
http://localhost:8091/axis/services/RunInfoAlign.wsdl
Using this WSDL file, client applications may be created to
consume the newly created Web service. Under this scheme,
the client should have prior knowledge about the parameters of
the application - input, output, and options- with their syntax
and order. To solve this problem, information about the
application parameters may be part of the information that may
be obtained from the Web service. So, by adding a new method
called getInfoalignParameters() to the Web service, the client
can get a description of the parameters of the infoalign
application, and then he can customize the user interface to
invoke the infoalign Web service. This solution is very
simplistic as the description of the application and its
parameters is more complex because of the variety of tools and
their parameters.
D. Application and parameters description
Prior to generating a Web service for a command-line
application, the parameters of the application should be
described in a structured way that can be used by programs. As
these command-line applications are developed by several

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programmers, and implemented in various programming
languages, they do not follow the same rules for specifying
their parameters. Therefore, coming up with a general
description schema of the application parameters is very
tentative. We have formalized the above descriptions of
applications and parameters by defining the XML schema for
both application and parameters descriptions.
The main elements describing an application are:
application name, application description, version number,
category, documentation URL, application path, minimum
number of input data, maximum number of input data, input
types, input formats.
Fig. 4. Definition of input types and input/output data formats.
An application tool may handle one or more of data types,
including: protein, nucleotide, taxonomic, and result. Also, an
application tool may handle one or several input and output
data formats. This is described in Fig. 4 using XML schema
types.
The output of an application may be as well in one of the
above data formats. By describing the data types and data
formats handled by an application, we can compose workflows
by connecting outputs of an application service to the inputs of
other application services.
The main elements describing a parameter of an application
are: parameter name, parameter description, type, the option
used to invoke the parameter, the value to be assigned to the
parameter, the syntax describing how a value is assigned to the
parameter, the min and max value in the case of integer
parameters, and default values. Each parameter belongs to one
following types: IntegerParameter, FloatParameter,
StringParameter, SwitchParameter, ChoiceListParameter,
FileParameter, and SequenceParameter. The complete XML
schema is available at:
http://faculty.uaeu.ac.ae/ebadidi/applSchema.xsd
V. IMPLEMENTATION
A. Generic XML Schema
A prototype of our proposed framework is under
construction. We have developed The XML schema for
application and parameters description, using Stylus Studio
enterprise edition [32]. This schema was used to develop and
validate the description of some bioinformatics tools such as
clustalw, infoalign, seqret, transeq, pepcoil, and silent. A
template has been also generated from the schema to allow easy
description of any command-line analysis tool. Using this
template and the textual documentation of a given tool, one can
create its XML descriptor that may be validated against our
XML schema. Fig. 6 shows an extract from the XML
description of the clustalw application for multiple alignments.
B. Web service and User interface generation
To implement the Java Web service for a given XML
descriptor, we are using the Java Architecture for XML
Binding (JAXB 2.0), which provides a fast and convenient way
to bind between XML schemas and Java representations,
making it easy for Java developers to incorporate XML data
and processing functions in Java applications. As part of this
process, JAXB provides methods for un-marshalling XML
descriptor documents into Java content trees of data objects
instantiated from the generated JAXB classes. These content
trees are then used to implement associated Web services and
user interfaces using JSP and HTML. This process is illustrated
in Fig. 5.
Fig. 5. Implementation process
Fig. 7 depicts the JSP interface generated from the above
classes for the seqret tool from the Emboss package.

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Fig. 6. XML Description of the clustalw application
Fig. 7. Generated JSP User Interface of Seqret
Using the above process, we generate JAXB classes from the
XML descriptors for few command-driven bioinformatics
software tools from the Emboss package, such as: infoalign,
seqret, transeq, getorf, silent, and pepcoil. These classes are
used in the implementation of related Web services. Table 1
provides a description of the operations of some of these Web
service.
TABLE I
SAMPLE WEB SERVICES OPERATIONS
Fig. 8. Tree representation of the seqret WSDL file.
The getInputTypes() operation returns the list of data types
(nucleotide, protein, etc) that should be provided as input data
to the tool. The getInputFormats() operation returns the list of
data formats (Fasta, Genbank, GCG, etc.) of the input data of
the tool. The getOutputFormats() operation returns the possible
data formats of the output files of the tool. The run operations
(runInfoalign, runSeqret, …) allow launching the execution of
a tool given input data and a list of arguments. Fig. 8 shows the
tree representation of the seqret WSDL file.

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C. Biological workflow composition
Using the above operations, it becomes possible to link the
tools’ Web services in workflows. Indeed, these operations
allow checking the compatibility between the types and formats
of output data of a given tool with the types and formats of
input data of another tool. Two of the generated Web services
can be composed in a workflow if the output data of the first
Web service is compatible in terms of types and formats with
the input data of the second Web service.
As a first attempt to specify biological workflows from the
generated Web services, the Business Process Execution
Language (BPEL) was the obvious composition language of
choice. BPEL provides a rich vocabulary for defining processes
and has several features which are not found in programming
languages. It enables users to describe business process
activities as Web services and define how they can be
connected to accomplish specific tasks. The Netbeans
development platform supports designing BPEL processes
since version 5.5.
Our goal is to allow the scientist to visually compose and
execute workflows in an easy way by hiding the technical
details of BPEL. A graphical user interface will allow the user
to specify his workflow in an easy way by just dragging and
dropping tools into a canvas. In addition, the composition of
workflows should be carried out by checking the compatibility
among application services based on their inputs and outputs.
The Workflow Manager component is responsible for allowing
such visual composition and enactment of workflows from our
generated Web services.
While investigating existing tools for visual composition, we
have found a tool called JOpera [33], which provides a
language for visual composition and which is implemented as a
plugin of the Eclipse development environment. JOpera is a
rapid service composition tool offering a visual language and
an execution environment for building processes out of
reusable services, which include but are not strictly limited to
Web services. It enables composing Web services into
processes by visually specifying the order of invocation of each
service (control flow) and to model the patterns of data
exchange between the services (data flow). The JOpera
environment provides support for the whole lifecycle of a
process; it features a visual monitoring and debugging
environment that lets the user interact with a running process.
Fig. 9 depicts a biological workflow that we have developed to
experiment with the JOpera environment. It is created from the
SeqretWS, TranseqWS, and GetorfWS Web services generated
respectively for seqret, transeq, and getorf Emboss tools. The
Bioworklow process is composed of three sub-processes:
SeqretSubprocess, TranseqSubprocess, and GetorfSubProcess.
Each of these subprocess is composed of tasks that represent
the invokation of the associated Web service operations. For
instance, the SeqretSubprocess is associated with the SeqretWS
Web service.
Fig. 9- Biological workflow created with the JOpera environment.
VI. CONCLUSION
In this paper, we have presented a new framework for
integrating bioinformatics tools by wrapping them as Web
services. These tools are characterized by the heterogeneity of
their styles, their parameters, and the data types and formats
they can handle. Our proposed framework allows creating
uniform interfaces of these tools without having to modify their
code or write additional code. This greatly simplifies
composing these applications into workflows to implement
biological protocols. The framework is based on using a
generic XML schema to describe bioinformatics applications
and their parameters in an easy way that catches various styles
and scenarios for using parameters in a command-line tool. A
prototype of our framework is still under development and
some sample application services, such as infoalign, seqret,
transeq, silent, getorf, and pepcoil have been generated and
customized.
As a future work, we intend to add various command-line
biological tools to the framework and to integrate JOpera with
our workflow manager. In addition to the framework tools, the
framework will provide support for importing external
biological Web services, available from the bioinformatics
community, and for their composition into workflows in the
same way as local Web services.

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ACKNOWLEDGMENT
The authors would like to thank Haifa Al Abdouli, Halima
Shehyari, and Mariam Hefaity for their contribution in the
implementation of the proposed test-bed.
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Elarbi Badidi is an Assistant Professor of computer science at the College of
Information Technology (CIT) of United Arab Emirates University. Before
joining the CIT, he held the position of bioinformatics group leader at the
Biochemistry Department of Université de Montréal from 2001 to July 2004.
He received a Ph.D. in computer science in 2000 from Université de Montréal,
Québec (Canada). His research interests include Web services and Service
Oriented Computing, Middleware, and Bioinformatics data and tools
integration.
M. Vall Mohamed Salem is currently an Assistant Professor with the
University of Wollongong in Dubai. His current interests are in performance
analysis and scalability issues, distributed systems and software engineering.
He received a Ph.D. in computer science in 2002 from Université de Montréal,
Québec (Canada). He held an IBM Canada Centre for Advanced Studies
fellowship and can be joined at salem@uow.edu.au.
Salah Bouktif is an Assistant Professor of software engineering at the College
of Information Technology (CIT) of United Arab Emirates University. Before
joining CIT, Dr. Bouktif was a Post Doc Fellow for two years at the department
of computer engineering of the polytechnic school of engineering of Montreal.
He received his Ph.D. Degree in 2005 with high honors from the University of
Montreal. Dr. Bouktif’s research interest includes Metrics and software quality
models, Software quality prediction improvement, Search-Based Software
Engineering, Software testing and test data generation, Software evolution,
Change and cost modeling.
Larbi Esmahi is an Associate Professor of the School of Computing and
Information Systems at Athabasca University. He was the graduate program
coordinator at the same school during 2002-2005. He holds a PhD in electrical
engineering from Ecole Polytechnique, University of Montreal. His current
research interests are in e-services, e-commerce, multiagent systems, and
intelligent systems. He is an associate editor for the Journal of Computer
Science, and the Tamkang Journal of Science and Engineering. He is also
member of the editorial advisory board of the Advances in Web-Based
Learning Book Series, IGI Global, and member of the international editorial
review board the International Journal of Web-Based Learning and Teaching
Technologies.
.

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