=Paper=
{{Paper
|id=Vol-2475/short7
|storemode=property
|title=Analysis and Risk Management in Software Development Using the Logical-Algebraic Model
|pdfUrl=https://ceur-ws.org/Vol-2475/short7.pdf
|volume=Vol-2475
|authors=Khansaa Al-Husseini,Ali Obaid
}}
==Analysis and Risk Management in Software Development Using the Logical-Algebraic Model==
https://ceur-ws.org/Vol-2475/short7.pdf
Analysis and Risk Management in Software Development Using
the Logical-Algebraic Model
[1]
Khansaa Azeez Obayes Al-Husseini, [2] Ali Hamzah Obaid
1
Babylon Technical Institute, Al-Furat Al-Awsat Technical University,51015 Babylon, Iraq.
inb.khansaa@atu.edu.iq, azeezkhansaa@gmail.com
2
Babylon Technical Institute, Al-Furat Al-Awsat Technical University,51015 Babylon, Iraq.
inb.ali210@atu.edu.iq ,alimk_iq@yahoo.com
Abstract. In this paper, we construct a logical-algebraic model that covers all
the parameters and operations of the risk process and create Specification of
risk assessment processes based on logical-algebraic formalisms-sets, matches,
relations, tuples, predicates, and Specification tools to automate the process of
risk assessment. And addressing concerns in a change in the software develop-
ment life cycle that changes requirements depending on the requirements of the
development work.
Keywords: Risk Management, Software Intensive Systems (SIS), information
technology (IT).
1 Introduction
Risk is an increased probability of loss, The risk is an increased probability at losses,
a possible problem that is or not to occur. This, as a rule, arises from the loss of input,
control in time. And the possibility of a loss in the process of software development is
called the risk of software development. The loss can be any, for example, increasing
the cost of production, reducing the quality of software development, the inability to
complete the project on time. The risk of software development exists because the
future remains uncertain, and there are many known and unknown things that cannot
be included in the project plan. The risk of software development There are two types
of risks that are either internal and controlled by the project manager or external risks
that are outside the control of the project manager To automate the processes of risk
assessment, first of all, it is necessary to build the most general model that reflects
common entities: the totality of the parameters used and the operations used. Logical
algebraic models are most often used to specify objects of modeling at the most gen-
eral level. When modeling the risk assessment processes, this reveals a multitude of
parameter values and a variety of operations of the risk assessment process. When
___________________________
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribu-
tion 4.0 International (CC BY 4.0).
In: P. Sosnin, V. Maklaev, E. Sosnina (eds.): Proceedings of the IS-2019 Conference, Ulyanovsk, Russia,
24-27 September 2019, published at http://ceur-ws.org
242
creating appropriate automation tools in the logical-algebraic model, multiple specifi-
cations appear that are involved in risk assessment, as well as many software func-
tions for processing these specifications and generating estimates.
2 Software development methodology
is the operation of dividing software development work into distinct stages And aim-
ing to a good organization and to improve the design. Common methodologies in-
clude a prototyping, Development (RAD) , Rational Unified Process (RUP)
,waterfall, Most theories attempt to minimize risk by using developing software in
little time, called restoration, which typically lasts one week to one month and in-
cludes all the tasks necessary " planning, requirements analysis, design, coding, test-
ing, and documentation". Figure (1)
Fig. 1. The basic approaches
3 Software Development Process
A set of steps illustrating the stages of software development shows Figure (2)
Fig. 2. Software development process.
243
Figure(2) above oversimplifies the process subtleties The first step is ideas in the
process, extract and form these ideas of the requirements, the requirements that feed
the process are ideas. Program objectives can be set at the requirements stage.
In the second step, the output of a development process, The user manual, software
development documentation, testing, and maintenance is the product of the develop-
ment process to help developers improve and develop the software in the future
4 Risk Management in Software Development
Risk is the probability of loss. This depends both on the likelihood of adverse
events and the consequences of these events; The impact is manifested in a blend of
money related misfortunes, time delays and loss of productivity. Hazard is an ante-
cedent to the issue, the probability that at some random point in the product life cycle,
Because of these and other factors, every software development project contains ele-
ments of uncertainty. the predicted goals will become unattainable within the accessi-
ble assets.
5 Empirical Data Sample Analysis
is a proof-based way to deal with the investigation and translation of data. The exact
methodology depends on genuine information, measurements, and results as opposed
to speculations and ideas. The data sample provided by project consists the following
assumptions about the data sample were made:
Duration of the project.
Start and finish date.
Development cost.
Rate software development.
These findings suggest that the data sample provided by the project the specific fea-
tures of risk data. Software Development projects have a high rate of failure. A mod-
el of software development using the Logical-Algebraic Model describes managerial
processes that can be used to reduce software development difficulties from the man-
agerial control perspective.
Our study examined the performance of projects Software Development in relation
to the activities of maturity. activities associated with the Software Development con-
trol of development-related positively to project performance measures.
Measure of probability
Probability measures in Software Development risk analysis must relate to a
specified level of exposure which can, for example, be the consumption of a particular
quantity of Project time without work, or an individual exposure event.
244
. The probability measures are generally expressed in one of two forms:
• The probability of the risk event occurring with a specified exposure event (e.g.
probability of illness),
• The average number of risk events that may occur within a specified period.
6 Description of the Risk Assessment Process
Software Development projects have a high rate of failure. Organizations have tried to
reduce the rate through methodological approaches but with little perceived success.
A model of software development maturity using the Logical-Algebraic Model de-
scribes managerial processes that can be used to attack software development difficul-
ties from the managerial control perspective. Our study examined the performance of
projects Software Development in relation to the activities of maturity. activities as-
sociated with the Software Development control of development-related positively to
project performance measures.
Work on risk analysis and the construction of an adequate model of its assess-
ment is very time-consuming. This is due, on the one hand, to the instability of the
causes of risk factors, and on the other hand, to the complexity of formalizing the
quantitative assessment of performance. Therefore, the justification and development
of risk assessment models require a thorough analysis of the nature of the initial in-
formation on the causes and risk factors, as well as the purpose of the study.
Depending on the nature of the initial information available at the time of problem
statement and the chosen method of uncertainty description, the following classes of
mathematical models of risk impact assessment are most common: deterministic;
stochastic; linguistic and non-stochastic.
In its most general form, parameterization of risk assessment processes covers the
following entities:
where R is an assessment of the consequences of a risk event;
P-probability of occurrence of a risk event;
I-potential consequences of the risk factor.
7 Development of Logical-Algebraic Model
The above description shows that the risk assessment process involves different in
nature and mechanisms of representation of the entity, which causes the multi-grade
algebraic model. To formalize using the technique of multi-sorted algebras (algebras
multistoried) you must first specify the underlying set. This specification is given
below.
PSPEC ={ PSpec1, PSpec2, …} – project specification,
Where PSpeci =< attгi ,vali> – significant specifier, attг i – attribute і-rо spec-
ifier's, vali – attribute value і-rо specifier's.
245
Dictionary report error RF={rf1, rf2………….} – multiple risk factors,
Where rfi=,
Where rfnamei – risk factor name;
pspeci PSREC – program specification, which is associated with the i-th risk
factor;
PR – set of material values of risk probability;
SR – the set of values of financial losses associated with the fact of risk trigger-
ing;
PF – many types of prototyping used to Refine risk assessments;
EST = {est1, est2 ….} – many of the risk assessments,
Where
esti = – vector of estimation-set of complex estimations risk the
form of triples, where rfi RF, pri PR, sr SR.
EXP = {exp1, exp2, …} – a lot of experts submitted a spec to the following:
expi = ,
Where exp_namei, exp_wi, exp_speci – name, weight and specialization of the
expert;
LOGS = {log1, log2, …} – multiple log entries that capture the results of the risk
assessment process;
The functions used in the risk assessment process in the form adopted for the log-
ical-algebraic specification are as follows:
Fest: PSPE × C × Exp × XRF → EST - risk assessment function;
Frf select: RF×SPEC→RF* – function of selection of a subset of risk factors
important for the project;
Pspec_select: PSPEC × EST → PSPEC – allocation function specifiers, which
have made the greatest impact on value pi и si;
Flog: EXP × EST × DT→ LOGS – a function of General process logging, where
DT is a set of data-time values to be recorded in log records.
Pstop: RF × PR × SF → {true, false} – predicate of the iterative process stop "
Risk Assessment-Prototyping-Modification PSPEC».
246
Pnp: RF × PR × SF × PF → {true, false} – the predicate initiate the prototyping
process in order to clarify the risk factors.
Composing a system of supporting sets and functions involved in risk assess-
ment, as well as a set of predicates that serve the process, we obtain the following
logical-algebraic model in the format of a multi-grade algebra specification:
RfsckA =(RF, PSPEC, EST, EXP | Fest, Frf select, Pspec_select, Flog, P_stop,
Prt,Perr,………)
Where Prt - the predicate of the decision about the need to create and execute a
prototype of profiling .
Perr - The predicate of the decision about the need to create and perform a proto-
type evaluation of accuracy.
Strategy pessimistic assessment
=
for an optimistic assessment
=
average grade
=
8 Model of Iterative Process of Risk Minimization in The
Design of Automated Systems
Risk assessment - a set of analytical measures to predict the possibility of obtaining
additional business income or a certain amount of damage from the risk situation and
late adoption of measures to prevent the risk.
The degree of risk is the probability of occurrence of a loss event, as well as the
amount of possible damage from it. Risk can be:
acceptable-there is a threat of complete loss of profit from the implementation of
the planned project;
critical-possible non-receipt of not only profits, but also revenue and loss coverage
at the expense of the entrepreneur;
catastrophic-possible loss of capital, property, and bankruptcy of the entrepreneur.
The risk impact assessment model can be summarized as follows:
F = f(P, I)……
where: F - assessment of the consequences of a risk event;
P-probability of occurrence of a risk event;
I-potential consequences of a risk event.
247
In General, the construction of a risk assessment model is complicated by the
instability of causes or risk factors and the complexity of formalizing the results of
activities. Therefore, when justifying and developing risk assessment models, a thor-
ough analysis of the nature of the initial information on the causes and risk factors is
required.
From the above we come to an Algebraic model of the process Figure (3).
PPstop = Predicate that detects that all the possibilities to Refine the risk
assessment have been exhausted
Pstop=( T Bound
Fig. 3. Algebraic model of the process.
9 Conclusion
The practical importance of research is the ability to use theoretical and
methodological results in practice to ensure risk calculation and thus the stability
of the means of implementation and development of the project as there are many
risks associated with creating high-quality programs on time and with a specific
budget. Nevertheless, in order to make sense to take these risks, they should be
compensated with sufficient remuneration. The developed tools help the project
manager to provide for risk response measures, based on more reliable infor-
mation. Reliable and more detailed information allows making more effective de-
cisions, which in turn reduces the possibility of risk occurrence. The product of
248
probability and impact determines the importance of risk - its value is an indicator
that can be used in the decision-making process.
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