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<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta>
      <journal-title-group>
        <journal-title>Proceedings of MoDISE-EUS</journal-title>
      </journal-title-group>
    </journal-meta>
    <article-meta>
      <title-group>
        <article-title>Improving Software Development Processes with Multicriteria Methods</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Elena Kornyshova</string-name>
          <email>elena.kornyshova@univ-paris1.fr</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Rébecca Deneckère</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Camille Salinesi</string-name>
          <email>camille.salinesi@univ-paris1.fr</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>CRI, University Paris 1 - Panthéon Sorbonne</institution>
          ,
          <addr-line>90, rue de Tolbiac, 75013 Paris</addr-line>
          ,
          <country country="FR">France</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2008</year>
      </pub-date>
      <volume>105</volume>
      <fpage>103</fpage>
      <lpage>113</lpage>
      <abstract>
        <p>All software development processes include steps where several alternatives induce a choice, a decision-making. Sometimes, methodologies offer a way to make decisions. However, in a lot of cases, the arguments to carry out the decision are very poor and the choice is made in an intuitive and hazardous way. The aim of our work is to offer a scientifically founded way to guide the engineer through tactical choices with the application of multicriteria methods in software development processes. This approach is illustrated with three cases: risks, use cases and tools within Rational Unified Process.</p>
      </abstract>
      <kwd-group>
        <kwd>Decision-making</kwd>
        <kwd>Multicriteria Methods</kwd>
        <kwd>Software Development Process</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>Researches on several engineering fields (systems engineering, process engineering,
method engineering, and so on) show that there are many development cases where
information system (IS) engineers has critical choices to carry out. As a matter of fact,
they have to deal with a large number of characteristics, artifacts, ideas, possibilities,
etc. Many strategies are offered to manage them and choosing one over the others is
often a very difficult task to handle. Some development activities aim to sort possible
alternatives by prioritizing them. However, these priorities are often applied
intuitively and there is a great need for a better priorisation support.</p>
      <p>
        Generally, a decision-making (DM) problem is defined by the presence of
alternatives. The traditional approach consists in using only one criterion in order to
select alternatives. The usual example is the selection of the projects according to the
net present value. However, using a single criterion is not sufficient when the
consequences of the alternatives to be analyzed are important [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ]. The goal of the
Multicriteria (MC) DM methods consists in defining priorities between alternatives
(actions, scenarios, projects) according to multiple criteria. In contrast to a
monocriterion approach, MC methods allow a more in-depth analysis of the problem
because they consider various aspects. However, their application has proved more
difficult.
      </p>
      <p>
        MC DM methods have shown their qualities for over 30 years [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ] and they
currently dominate in the field of decision-making [
        <xref ref-type="bibr" rid="ref3 ref4">3,4</xref>
        ]. They appeared at the
beginning of the Sixties, and their number and application contexts increase
continually. For example, these methods are employed for requirements priorisation
[
        <xref ref-type="bibr" rid="ref5">5</xref>
        ], to choose evolution scenario [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ], or to make operational decisions [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ].
      </p>
      <p>
        Five families of MC methods can be considered: MAUT [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ], AHP [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ], outranking
methods [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ], weighting methods [10], and fuzzy methods [11]. These methods will be
detailed in the following.
      </p>
      <p>We propose in this work to improve any development process with the use of
multicriteria methods as a way to choose the most adapted alternative to each
situation. We propose a process, illustrated by an example within Rational Unified
Process (RUP) [12, 13], which integrates MC methods at the DM point of the
development process. Our aim is to propose a formal approach for priorisation in
order to enhance DM in development process.</p>
      <p>The paper is organized as follows: section 2 gives an overview of our proposed
process, which is illustrated in section 3 on three DM points of RUP, and concluded
in section 4.</p>
    </sec>
    <sec id="sec-2">
      <title>2. Overview of the multicriteria methods integration process</title>
      <p>Our proposal consists of the integration of MC methods in the methodologies of
software development. It is described by an "integration process" (IP) which is
presented on Figure 1.</p>
      <p>Identify requirements for priorisation
Specify requirements for MC methods</p>
      <p>Select a MC method</p>
      <p>Apply the MC method and validate results
The integration process includes four steps: 1) Identify requirements for priorisation,
2) Specify requirements for MC methods, 3) Select a MC method, and 4) Apply the
MC method and validate results. This IP includes both direct steps and flashbacks.
The former indicate the normal IP development, and the latter enable returns to the
previous steps if necessary.</p>
      <sec id="sec-2-1">
        <title>2.1. Identify Requirements for Priorisation</title>
        <p>This step may also be seen as the recognition and description of a specific situation of
DM. The first element to define is the identification of the presence of alternatives. If
a process offers a different manner to fulfill a specific objective, we may see this
process as a "DM point". Identifying these points may be a difficult task to perform
and we suggest asking the following questions:</p>
        <p>- “What is the type of guidance to run this task: linear or tree form (set of
possibilities)? “</p>
        <p>- “Does the guidance offer arguments (metrics or criteria) to choose between the
alternatives?”
- “Does the guidance offer a way to assign a prioritization to these alternatives?”
There are different kinds of DM problems. They may be classified (according to
the number of criterion and of decision-makers they have) into five types (cf. Figure
2).</p>
        <p>The first type presents a monocriterion problem and can be resolved as an
optimization task. In the following, we will focus only on the problems that can be
solved by MC methods (types: 2 to 5).</p>
        <p>When the DM point has been identified, the IP step guides the engineer in describing
its situation. B. Roy defines three basic concepts that play a fundamental role in
analysing and structuring decisions in close connection with the decision process
itself [14]: alternatives (potential actions), criteria family, and decision problem.
Based on this, we propose to specify decision situation as a &lt;Problem; Alternative;
Criterion&gt; triplet, where problem refers decision problem; alternative refers the
collection of alternatives among which one will be chosen; and criterion refers the list
of criteria by which alternatives will be evaluated. This description will allow the
engineer to define the DM point on a generic level (called level 1 in this work).</p>
        <p>The decision problem [14] can be defined by the result expected from a DM. When
the result consists in a subset of a potential alternatives (most often one alternative)
then it is a choice problem. When the result represents the potential alternatives'
affectation to some predefined clusters, then it is a classification problem. When the
result consists in a potential alternatives ordered collection, then it is a ranking
problematic. Given that each MC method is able to support a specific type of
decision, it is important to know which type of decision is faced to be able to select
the appropriate DM method. The concept of alternative designates the object of
decisions. Any decision involves at least two alternatives that must be well identified.
A criterion can be any type of information that enables the evaluation of alternatives
and their comparison. Often, development processes already propose a predefined
criteria set. This set can be improved by adapting it to the project at hand. One of the
improvement possibilities takes its roots in two directions: software metrics [15] and
typology of characteristics of IS development project [16]. Within a MC problem, the
metrics and the projects characteristics are considered as criteria. In a general way, the
criteria may be qualitative or quantitative, relative or absolute, and criteria of time,
cost, quality, size, efficiency, and so on.</p>
      </sec>
      <sec id="sec-2-2">
        <title>2.2. Specify Requirements for MC Methods</title>
        <p>In order to deal with decisions, we define a second level of decision-making for
selecting a MC method (DM Situation L2). Whereas the level 1 deals with the
priorization problem, the level 2 is addressing the MC methods selection problem to
solve the level 1 one. The identification of requirement for MC methods allows
characterizing the specific parameters required for MC method selection. The
problem is always a choice, the alternatives are MC methods, and the selection is
made using criteria defined as (a) an aggregate view of the requirements for
priorisation, and (b) supplementary criteria referring to the usage of the intended
method. The Figure 4 illustrates the model of DM situation applied to the selection of
MC method (L2 decision).
Several strategies can be applied to specify requirements for MC methods. One of
them is to specify the requirements by problem investigation. It means that the
engineer has to identify the operations that enable to switch from the requirements for
prioritization to the requirements for MC methods. These operations are (i) for
problem: retaining the problem type; (ii) for alternatives: calculating the alternatives
number, retaining alternatives nature, retaining alternatives incompatibility, and (iii)
for criteria: retaining criteria data type, retaining criteria measure scale, and retaining
weighting type. Additional information may also be required to specify the MC
method usage in the given situation: if a DM tool is needed or not, the nature of the
notation, the method easiness, and the level of engineer skills required for applying
the MC method.</p>
      </sec>
      <sec id="sec-2-3">
        <title>2.3. Select a MC Method</title>
        <p>Each MC method is able to deal with problems with specific characteristics. For
instance, the number and nature of the alternatives, the decision criteria or the
presence of multiple stakeholders with different viewpoints. Besides, the existing
methods have different characteristics such as complexity or ability to deal with
quantitative or qualitative criteria. A few selection approaches were thus developed to
guide specifically MCDM method selection. The state of the art is presented in [17].</p>
        <p>Our assumption is that a process guiding the selection of a DM method should (a)
be simple to use, (b) provide results that can be trusted, and therefore (c) take into
account all the relevant aspects of the situation at hand. Our approach focusing on
these relevant aspects focuses on the comparison technique presented in the next
subsection. The current section focuses on the selection process itself.</p>
        <p>We introduce the notion of MC method interface to guide MC method selection.
The interface represents the characteristics of the situations in which a given MC
method can be used and corresponds to the criteria set from the model presented in
Fig. 4. The figure 5 shows the relationship between method and interface and several
MC method family’ interfaces, which are described in the Table 1. In this table, a line
represents a general attribute of the interface (level 2) and a column represents a
particular MC method family.</p>
        <p>Experience may be sufficient to select a method, in particular if the exact same
situation has already been met.</p>
        <p>An MC method may be selected by MC search. This means that the engineer has to
search an appropriated method using L2 criteria identified earlier in order to obtain
one or several MC methods corresponding to his/her requirements for MC method.</p>
        <p>If the achievement of the MC search application drives to the selection of several MC
methods, it is possible to choose one of them by weighting. Using this approach,
weights must be given to the L2 criteria. These weights indicate the relative importance
of the L2 criteria to the situation at hand. Then, "0" or "1" values are allocated to
candidate MC methods according to each criterion. The method having the highest
weighted sum of criteria values is then chosen. This strategy is not adequate when the
previously selected methods have the same interfaces with reference to specified
requirements.</p>
      </sec>
      <sec id="sec-2-4">
        <title>2.4. Apply the MC Method and Validate Results</title>
        <p>The final step of our proposed process is to apply the chosen multicriteria methods on
the identified decision points of the development process. The validation is made
following the matching between the users' requirements and the obtained results. The
MC methods application and its complexity degree depend on the selected method. It
may require additional skills or the acquisition of a tool that supports MC decision
making. The presence of a tool is an important factor for practitioners who are
concerned with the rapid application of a selected MC method. Tools are however,
sometimes costly (purchasing and training), and their acquisition and deployment can
be time consuming.
1 Fuzzy methods differ according to the "basic" MC method: MAUT, outranking methods, and
so on. Hence, they have the value "Different".</p>
        <p>
          The engineer may also execute the MC method by achieving manual calculation or
by developing a tool ad hoc. Applying different methods involve different activities.
For instance, the MAUT requires constructing partial utility functions and their
aggregation into a general utility function by addition or multiplication [
          <xref ref-type="bibr" rid="ref8">8</xref>
          ]. AHP is
based on a dominance hierarchy and carried out by decision-makers' pair-wise
comparisons [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ]. Outranking methods are based on analysis of the degree of
dominance of one alternative over another [
          <xref ref-type="bibr" rid="ref6 ref7">6,7</xref>
          ]. Weighting methods are characterized
by a weight assignment being applied to the decision criteria; and the aggregation of
the evaluations is based on a weighted sum [10]. The fuzzy MC methods employ the
fuzzy sets theory to add flexibility and to enrich methods by fuzzy parameters [11].
        </p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>3. Application example with the Rational Unified Process</title>
      <p>We propose to illustrate the use of the proposed process by guiding decisions in the
Rational Unified Process (RUP) [12, 13]. The RUP is a body of software engineering
practices, which is maintained on a regular basis to reflect changes in industry
practices. It provides a wealth of guidance on software development practices that
both novice and experienced practitioners can exploit. However, although many RUP
practices call for decision-making, there is very little information about how to
achieve these decisions. All these arguments, together with the fact that the RUP is
widely used in the industry, convinced us that it was a good candidate to apply our
approach and evaluate it. This paper presents details about the core elements of our
proposal, which consists on identifying requirements for decision, specifying
requirements for MC methods, and selecting MC methods.</p>
      <p>Guidance is provided by the RUP under the form of descriptions of the tasks that
can be achieved and of the best practices attached to them. Putting ourselves in the
position of a person who wants to prepare a method for a project beforehand, we start
by scanning each task described to find those offering alternatives and some kind of
DM guidance. We chose to study 3 tasks more closely: (a) select and acquire tools,
(b) prioritize use cases, and (c) analyze and prioritize risks2.</p>
      <p>Select and Acquire Tools. This task guides the adoption of tools that support other
tasks in the RUP. Tools that need to be selected should fit the particular requirements
of the organization for which the selection is made. Furthermore, special tools
sometimes have to be developed internally to support special needs. One of the steps
in this task is to collect information about tools in order to gain a better
understanding. This information later serve as selection criteria to help the system
engineer decide which tool is right for the project at hand. The criteria for tool
selection are tool features, vendor and cost characteristics. The RUP proposes to
grade each criterion for evaluating candidate tools. However, the guidance stops there
and the engineer is left alone at the moment of the actual decision making.
2 Our case study is nominative and simplified. It was elaborated specially for illustrating
suggested approach application.
Analyze and Prioritize Risks. This task describes how to identify, analyse and
prioritize IS project risks. To achieve this, an inventory of what can go wrong within
the project must be made. Events that might decrease the chance of delivering all the
required IS features at the end of the project, at the required level of quality, and on
time/within budget. The RUP guides this by telling how to (i) look within
complementarities and redundancies to see if they would be a source of risk, (ii) put
them in a table known as the Risk List, and (iii) rank risks in decreasing order of
importance and associate them with specific mitigation or contingency actions. Again,
the RUP is very vague with respect to this DM problem: an “order of importance”
with respect to these criteria is not clearly defined.</p>
      <p>Prioritize Use Cases. The prioritization of use cases allows deciding their order of
development. The RUP guidance proposes that the software architect selects a certain
number of scenarios and use cases to be analyzed and designed. This proposal is
completed and refined in several ways: by development teams, customer
requirements, and based on COTS products. The selection is then made by
characterizing key factors. For instance, architecturally significant use cases that are
poorly understood or likely to change should be prioritized for clarification and
stabilization.</p>
      <p>These examples are presented in Table 2., which gives an overview of
requirements for L1 decisions. Some considerations must be made. For instance, the
cost evaluation of tools is carried out according to 5-grade scale (in RUP, - a 3-grade
scale) for facilitating DM.
Based on the information from Table 2, the strategy by problem investigation allows
identifying the requirements for L2 decisions. A summary of these requirements is
given in the table 3 (these requirements are specified.</p>
      <p>
        For tools prioritization, only the weighting method satisfies all requirements. With
reference to risks analysis, two MC methods are found: MAUT and outranking. To
make our final choice, the engineer decides to give a priority to methods offering a
tool. So, the outranking method allowing a tool panel (PROMETHEE I and II,
ELECTRE II and III [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]) is selected. Regarding use cases prioritization, no MC
method matches that requirement for criteria data type. In this case, another set of
candidate methods must be considered (for instance, fuzzy methods) or some
requirements removed (if it is possible to remove not-satisfied requirement in the
given situation).
      </p>
      <p>For the lack of space, we do not consider the application of selected methods. Our
aim is to illustrate, firstly, the MC method selection based on two levels requirements
and, secondly, the specific situation consideration expressed by these requirements.</p>
    </sec>
    <sec id="sec-4">
      <title>4. Conclusion</title>
      <p>Decision-making is a difficult process and prioritizing alternatives is a good and
efficient way to improve development processes. This is usually done on an intuitive
way. Our aim was to offer a scientifically founded way to make this priorization by
offering a guidance process to the engineer. This process proposes to use the
integration of multicriteria methods to choose the most adapted alternative to each
situation. We illustrated this process with examples taken within the Rational Unified
Process (RUP) [12, 13]. We showed how to use IP to integrate MC methods at a
specific decision-making point.</p>
      <p>Our research perspectives include:
- improving the DM methods signatures to better select MC methods;
- developing a tool that would offer a systematic guidance of IP;
- defining MC methods as a method fragment to allow for their integration into
any existing methodologies;
- exploring the issue of adapting DM methods to the situation at hand.
Several extensive case studies in the IS engineering area have also been undertaken.</p>
    </sec>
  </body>
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