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please just write the bulk of the paper with in text citations and
a work cited page as well don’t worry about title page and
header and footer I will edit that upon completion.
To access articles in the Library for this class and others, please
refer to the instructions on the Syllabus and in Case 1.
For the session long project, choose one area within the health
issue below as your research topic. You will focus on the same
topic for your SLP throughout the session.
Traumatic brain injury
Before you begin, read the instructions and expectations
carefully -- this is not a typical report-style assignment.
Narrow down the topic to a certain part of the population (i.e.
an age group, gender, a certain race or ethnicity, or a particular
geographic area). It will help to do some research before
choosing your focus, so you can see what literature will be
available to use throughout the session. Look at the SLP in
Modules 2 - 5 so you can plan ahead as approporiate.
Use credible professional sources such as ProQuest or EBSCO
articles, or Websites from a university, government, or
nonprofit organization to search for information about the issue.
Consumer sources such as e-magazines, newspapers, and .com
sites are not appropriate.
1. Introduce the topic and write a brief background about the
scope of the problem. What is the health effect? How many
people does it affect? Is there a treatment or a cure? What kind
of research is being conducted about the problem? This part of
the paper should be approximately 1 page.
2. Now, based on what you learned about the topic, think
about what the gaps in knowledge seem to be. They are often
stated in the "conclusions" of research articles. Using that
information, do the following:
State a properly phrased health-related research question that
you would like to answer if you were a researcher. Review the
information in the link provided on the Background Information
page so you are clear as to what a research question is. This
should not be a paragraph or an explanation, just a research
question.
3. Now, formulate a specific hypothesis to investigate that
research question. Again, this should not be a paragraph or an
explanation, just a properly stated hypothesis. Review the
information in the links provided on the Background
Information page so you are clear as to what a hypothesis is.
ASSIGNMENT EXPECTATIONS: Please read before
completing assignments.
· Copy the actual assignment from this page onto the cover page
of your paper (do this for all papers in all courses).
· Assignment should be 2 pages in length (double-spaced).
· Please use major sections corresponding to the major points of
the assignment, and where appropriate use sub-sections (with
headings).
· Remember to write in a Scientific manner (try to avoid using
the first person except when describing a relevant personal
experience).
· Quoted material should not exceed 10% of the total paper
(since the focus of these assignments is on independent thinking
and critical analysis). Use your own words and build on the
ideas of others.
· When material is copied verbatim from external sources, it
MUST be properly cited. This means that material copied
verbatim must be enclosed in quotes and the reference should be
cited either within the text or with a footnote.
· Use of peer-reviewed articles is required. Websites as
references should be minimal and must be professional sources
(such as university, government, nonprofit) rather than
consumer sources (such as e-magazines and .com sites).
Cognitive Complexity Metrics and its Impact on Software
Reliability Based on
Cognitive Software Development Model
Dharmender Singh Kushwaha and A.K.Misra
Department of Computer Science and Engineering
Moti Lal Nehru National Institute Of Technology
Allahabad, India.
Email:[email protected],[email protected]
Abstract
Software metrics provide a quantitative basis for the
development
and validation of models of software development process.
Information gained from metrics is used in managing the
development process in order to improve the reliability and
quality
of software product. The software metric is used to estimate
various parameters of software development lifecycle such as
cost,
schedule productivity, quality and reliability. In this paper, an
attempt has been made to frame the cognitive complexity
metrics
that will aid in increasing the reliability of software product
being
developed during the development lifecycle.
Keywords
Cognitive Software Development Model,Cognitive
Documentation Complexity, Metacognition, Cognitive Software
Inspection Process, Cognitive Requirement Engineering.
1. Introduction
Metrics are a useful means for monitoring progress, attaining
more
accurate estimation of milestones and developing a software
system that contains minimal faults thus improving the quality.
Measures are necessary to identify weaknesses of the
development
process. They also prompt the necessary corrective activities
and
enable us to monitor the results. Hence they act as feedback
mechanism that plays a vital role in the improvement of the
software development process. There is an urgent need of
software
metrics to monitor the software development process for
improving the overall quality of the software . Since complexity
metrics are a significant and determinant factor of a systems
success or failure, there is always a higher risk involved when
the
complexity measurement is ignored. Software metrics have been
used for over three decades to assess or predict properties of
software systems, but success has been limited by factors such
as
lack of sound models, the difficulty of conducting controlled
repeatable experiments in educational or commercial context,
and
the inability to compare data obtained by different researchers.
It is hypothesized that an overly complex code (i.e. an
unstructured
code with low cohesion) will be difficult to maintain and is
likely
to be unreliable. In order to create software, our design
decisions,
cognition, metacognition learning process and problem
comprehensibility should be able to guide us to create software
such that overall complexity is reduced. The most efficient way
to
deal with developing reliable software for large systems is by
creating smaller modules. Weyuker’s [7] property 5 (∀ P)(
∀ Q)(|P|
≤ |P;Q| and |Q| ≤ |P;Q|) just aims to achieve this. The
implication
of this property is that as the size of program segment is
increased,
its complexity should also increase. Hence the divide and
conquers
technique which relies on decomposing the original problem
into
sub-problems with well defined interactions will lead to a
structured design that will make the software reliable and
maintainable.
Cognitive aspects focus on the ease of understanding or the
property of comprehension. Comprehension is the key feature
that
distinguishes any entity as being complex or simple.
Comprehensibility of a problem helps in efficient design
solution
and improvement of software product quality. Thus property of
comprehensibility can be used in all the different phases of
software engineering.
2. Cognitive Software Development Model
Kushwaha and Misra [5] have proposed Cognitive Software
Development Model, with emphasis on cognitive aspects. This
cognitive model of software development is based on the
following broad phenomena:
• Cognitive process of requirement engineering;
• Cognitive system analysis;
• Cognitive system design;
• Assigning team members to different tasks based on the
cognitive phenomena;
• Cognitive approach to software inspection and testing;
• Cognitive documentation style.
The cognitive software development model of software
development is illustrated in fig.1
It can be inferred from the cognitive software development
model
that the phases that also contribute to software reliability are:
1. Cognitive phenomena based team member selection;
2. Human centric requirement engineering;
3. Cognitive software inspection, a part of testing;
4. Documentation based on cognitive phenomena and
5. Validation by Metrics.
Hence the following sections of our paper will elaborate on how
above-mentioned factors and metrics will help in development
of
reliable software systems.
ACM SIGSOFT Software Engineering Notes Page 1
March 2006 Volume 31 Number 2
3. Reliability
The basic requirement for software system is correctness. A
program is correct if the output satisfies the output
requirements
for every input specified by the input requirements. There are
active and passive approaches to achieve program correctness.
The
active approach takes the form of program correctness proofs.
Passive approach takes the form of traditional testing and
debugging. Since testing can only indicate the presence of bugs,
not their absence, hence it is not possible to estimate the
number of
bugs remaining in the software system. Hence testing cannot
guarantee program correctness. Based on the above reasoning
the
reliability of software can be defined as the probability that the
subsequent execution and invocation of the program is also
correct.
Our approach to reliability is based on the theory of “Prevention
is
better than cure”. To achieve this, we propose our metrics that
are
constructive, analytic and cognitive in approach. We begin with
human centric approach of requirement engineering in the next
section.
4. Cognitive Process of Requirement Engineering
Until now, the requirement engineering has focused on the
following areas:
• Abstract functional requirements;
• Non-
functional
requirements;
• System
properties
such as
availability
and
performance;
• System and
environment
requirements.
The areas that have a
major impact in
requirement
engineering but often
ignored are:
• They do not
distinguish
between the
client and the
end user.
Since client is
the one who
first comes in
contact with
the software
engineer /
software
practitioner
representing
the vendor
and the end user is the one who has to use the software.
The perspectives of both shall be different and should be
gathered carefully.
SYSTEM
Cognitive Process of
Requirement Engineering
Problem
Analysis
System
Design
Sub-System
Design
Sub-System
Interface Design
Validation by
Metrics
Implementation /
Development
Testing
Maintenance
Cognitive
Phenomena
Based
Team
Member
Selection
Documentatio
n based
on
Cognitive
Phenomena
Figure 1:Cognitive Software development moel
• Client is not able to describe and establish the cognition
and psychological level of the end users of the proposed
system
• The requirement analysis is not performed from the users
point of view and as such system oriented requirement
analysis is performed
• The requirement-gathering phase doesn’t distinguish
between low level details and cognition characteristics of
these details.
• System oriented design fails to uncover the need for
domain specific training of the end user or change in
human organization.
The cognitive requirement-engineering model is proposed to
provide a holistic description of cognitive characteristics of the
system under study (including the cognitive characteristics of
the
end user). Cognitive characteristics capture information such as
user preferences. These also help in understanding the cognitive
phenomena of the user, which will help in streamlining further
interactions with the users in producing reliable software. We
propose a model to describe the cognitive characteristics of the
different user as depicted in fig. 2.
The requirement analyst has the responsibility of analyzing the
requirements and views. The requirement gathering, if properly
ACM SIGSOFT Software Engineering Notes Page 2
March 2006 Volume 31 Number 2
classified depending on the kind of user interacted with, will
provide for a total system view, thereby reducing the number of
interactions and the rework. These views can be organized as a
tuple [RTP, RPROF, RAMAT, RNOV] representing
requirements of top
management, professional, amateur or novice user. Once the
analyst is able to categorize the viewpoint of the users at
different
hierarchies with varying cognitive phenomena, the overall
system
developed will be in total synch not only with the explicitly
stated
requirements but also with the implicit ones. Also the
information
domain of the system to be developed must be clearly
understood.
The requirement-engineering model is depicted in fig. 3. The
person who is the catalyst behind the request for the software
will
play a key role in extending the need analysis and hence
carrying
out the requirement analysis. Once proper requirement
engineering
has been carried out, we can safely proceed to problem analysis.
This will reduce the amount of rework.
SYSTEM USER
TOP
MANAGEMENT
END USER
NEW
CLIENT
EXISTING
CLIENT
COGNITIVE PHENOMENA
Professional Amateur Novice
Figure 2: Cognitive characteristics of user
5. Cognitive Software Inspection and Team Member
Selection
As the software system evolves and grows larger, the effort and
cost needed by verification process grows astronomically. Dolan
[6] reports a 30 times return on investment for every hour
devoted
to the software inspection. Software inspection process is still
far
from optimal, and one area that has seen limited research is the
impact of team member selection on it.
The bottlenecks of code inspection are:
Operational
Characteristics
Of Organization
Cognitive
Characteristics
of User
Feasibility
Study and
Report
Requirement
Elicitation
Cognitive
Character-
istics of
Requirement
Elicitation
Requirement
Specification
Require -
ment
Validation
Require-ment
Documentation
Figure 3 : Cognitive Requirement Engineering Model
• Lack of research on team member selection
• Incorrect selection mechanism of team members
• Team members sharing / possessing similar view point to
a particular problem
ACM SIGSOFT Software Engineering Notes Page 3
March 2006 Volume 31 Number 2
• It is a cognitive phenomenon, but unfortunately, it has
been seen in terms of technical maturity of team member
performing the code inspection.
SOFTWARE ENGINEER / PROFESSIONAL
REALISTIC IDEALISTIC
Solution
Seeking PROFESSIO AMATEURS
NALS
GUI
Design Deve loped
Higher level
Cognitive
Function
Sub -
Conscious
Function
Meta
Cognition
Function
System
Architect
To overcome the above bottlenecks, a cognitive model of team
selection procedure for software inspection is proposed based
on
the functionalities best performed depending on the cognitive
activity level of team members.
ure
Coding Testing Coding
Code
Review &
Testing Testing Requireme
nt
Gathering
Code
Review
Quality
Control
Code
Review
SOFTWARE INSPECTION TEAM
Figure 4: Cognitive phenomena based team member selection
mechanism
ACM SIGSOFT Software Engineering Notes Page 4
March 2006 Volume 31 Number 2
Wang [10], proposed cognitive phenomena, which classifies
cognitive functions as sub-conscious, meta-cognitive and higher
cognitive. Wang [8] described two types of programmers –
realistic and idealistic. It is important issue to contrast and
analyze
the cognitive levels of the team members. It is agreed among
researchers that increasing diversity among team members is the
key to increasing the software inspection effectiveness. Hence
creating inspection team with a combination of members from
different cognitive levels will increase the effectiveness of code
review, thereby reducing the testing effort.
The difference between professionals and amateurs is whether
their knowledge and skills are wired or temporary programmed
in
the brain [9]. For e.g. Professional software engineers possess
wired skills in programming, and with a global view on
software
development. They focus not only on required functions, but
also
on exceptions-handling and fault tolerance. However, amateur
programmers possess ad-hoc programming knowledge, eager to
try what is directly required, and tend to focus on details
without a
global and systematic view. Hence software inspection and
testing
team should include members from this amateur category also,
since they have the quality to have a narrow focus as illustrated
in
fig. 4. The amateurs try to deal with individual concepts before
taking on the new ones are also candidate for testing and
debugging. This will ascertain that the software inspection so
carried out increases the reliability of software product.
6. Cognitive Documentation Complexity (CDC)
Very little attention has been paid to the comprehensibility of
various documents created during software development
lifecycle.
If a novice is able to understand the various documents, then we
are sure of creating a reliable and quality artifact. Cognitive
documentation complexity of a class can be measured in terms
of
the cognitive phenomena and the associated weight. There are
numerous documentation types that will speak about the level of
useful information provided by the documentation. Even today,
header information, comments and use of good identifier names
are considered to be the quality factors of best documentation.
These practices, do not count on the comprehensibility and the
cognitive phenomenon of the mind that assists the software
developer in reducing the comprehension effort and improving
the
coding standard.
If the documentation provides reasonable amount of useful
information about the class to a novice, average and expert
software practitioner, it implies that ready understandability
was
present in the documentation of the class and is termed to be of
high quality. On the contrary, if only expert practitioner
understands the documentation, then the documentation quality
is
termed to be low. This also implies that sub-conscious cognitive
functions (the one that are not wired) are not enough in
comprehending the documentation. The classification of
cognitive
phenomenon is as described by Wang [10]. This is summarized
in
the table below.
S.No Cognitive Phenomena associated with
Documentation
Quality of
Documentation
1. Sub – Conscious Cognitive function High-Quality
2. Meta – Cognitive function Average-Quality
3. Higher Cognitive functions Low-Quality
Table 1: Quality of Documentation Based on Cognitive
Phenomena
High quality documents are very useful and enable us to:
• Enhance comprehensibility of software product
• Reduce maintenance cost
• Effectively exploit the system
• Reduce re-engineering cost and effort.
7. Cognitive Conceptual Complexity of Class / Module
The syntactic metrics measure the complexity of the software. It
is
the details of implementation that determines the
comprehension
complexity [1, 2]. We also need some metrics to measure the
psychological complexity that measures the difficulty of
understanding of the software module. This psychological
complexity is based on the number of distinct key concepts in
the
class or module and is defined as
m
CCCC = ∑ [(No. of distinct Cognitive Concepts) * (Weight of
i=1 Concept)]i
Where ‘m’ is the number of distinct concepts in the class or
module.
The weighing factor of cognitive concepts is based on the
classification of cognitive phenomenon as described by Wang
[8],
is as follows:
S.No Cognitive Phenomena Weight
1. Sub – Conscious Cognitive function 1
2. Meta – Cognitive function 2
3. Higher Cognitive functions 3
Table 2: Weights Based on Cognitive Phenomena
Higher weight indicates that greater amount of comprehension
effort is required in understanding the software module under
consideration. If there exists a distinct concept but is not
understood by the practitioner (because he may be novice or
semi-
skilled), it is the subconscious life function that will guide him
to
identify it. Hence higher weight is associated with it. Higher
cognitive functions will require lower comprehension effort and
hence lower weight associated with it.
The mind is an artifact model of oneself and a thinking engine.
The mind, as a virtual model of a person in the brain, is
partially
programmed and partially wired. The former is evolved for the
flexibility of the life functions while the latter is formed for the
efficiency of frequently conducted activities. The complexity of
the class can be calculated by using the CICM metric that is a
robust cognitive complexity measure [3, 4].
8. Conclusion
ACM SIGSOFT Software Engineering Notes Page 5
March 2006 Volume 31 Number 2
This paper is based on the cognitive software development
model.
It has made an attempt to emphasize the importance of cognitive
metrics and its impact in achieving reliable software
development.
It also identifies those areas that are vital to reliable software
development process but have been either ignored or given
lower
degree of importance by the researcher community in the past.
In
future, we shall work to propose cognitive complexity metrics
for
all the phases of cognitive software development model in order
to
produce software that is not only reliable but is of highest
quality.
References
[1] Kushwaha, D.S. and Misra, A.K.,: A Complexity Measure
Based on Information Contained in the Software, 5th WSEAS
International Conference on Software Engineering, Parallel and
Distributed Systems (SEPADS 2006), Madrid, Spain, To
Appear,
Feb. 2006.
[2] Kushwaha, D.S. and Misra, A.K.: Cognitive Complexity
Measure of Object-Oriented Software – A Practitioners
Approach,
5th WSEAS International Conference on Software Engineering,
Parallel and Distributed Systems (SEPADS 2006), Madrid,
Spain,
To Appear. Feb. 2006.
[3] Kushwaha D.S.and.Misra A.K: “Robustness Analysis of
Cognitive Information Complexity Measure using Weyuker
Properties”, ACM SIGSOFT Software Engineering Notes, Vol.
31,
No. 7, January 2006.
[4] Kushwaha D.S.and.Misra A.K: “Evaluating Cognitive
Information Complexity Measure ”, 13th Annual IEEE
International Conference and Workshop on the Engineering of
Computer Based Systems (ECBS) To Appear,2006.
[5] Kushwaha, D.S. and Misra, A.K.: A Cognitive Complexity
Metric Suite for Object-Oriented Software”, WSEAS
Transactions
on Computers, To Appear, Feb. 2006.
[6] E.P.Doolan, :Experience with Fagans Inspection Method,
Software Practice and Experience. Vol. 2, No. 2, pp. 173-182,
Feb. 1992.
[7] Weyuker, E.,: Evaluating software complexity measure.
IEEE
Transaction on Software Engineering Vol. 14(9): 1357-1365,
september1988.
[8] Wang,Y.,: On The Cognitive Informatics Foundations of
Software Engineering, IEEE International Conference on
Cognitive Informatics, 2004.
[9] Wang,Y.,: On The Informatics Laws of Software, IEEE
International Conference on Cognitive Informatics, 2004.
[10] Wang,Y.,: On Cognitive Informatics, Keynote Lecture,
Proceedings of IEEE International Conference on Cognitive
Informatics, 2002, pp. 34 – 42.
ACM SIGSOFT Software Engineering Notes Page 6
March 2006 Volume 31 Number 2
Cognitive Complexity Metrics and its Impact on Software
Reliability Based on Cognitive Software Development
ModelAbstractKeywords1. Introduction2. Cognitive Software
Development Model Kushwaha and Misra [5] have proposed
Cognitive Software Development Model, with emphasis on
cognitive aspects. This cognitive model of software
development is based on the following broad phenomena:3.
Reliability Table 2: Weights Based on Cognitive Phenomena 8.
ConclusionReferences
please just write the bulk of the paper with in text citations and
a work cited page as well don’t worry about title page and
header and footer I will edit that upon completion.
thank you
Assignment
Being able to read and understand research studies requires
quantitative reasoning. The purpose of this assignment is to
help you get accustomed to identifying the various parts of a
research study. Be sure to review the module homepage and
background information before you begin any of the
assignments in this course.
In general, the best way to approach the assignment is to read
the article through rather rapidly in order to get an impression
of its general content; then read it more slowly and make
appropriate notes so you can complete the assignment as
directed below.
Review the instructions and the ASSIGNMENT
EXPECTATIONS below, and then read this research article,
retrieved from Proquest:
Van Voorhees, Benjamin W, MD, MPH, Gollan, J., PhD., &
Fogel, J., PhD. (2012). Pilot study of internet-based early
intervention for combat-related mental distress. Journal of
Rehabilitation Research and Development, 49(8), 1175-90.
Retrieved from Proquest.
Your task is to identify and summarize the main points of the
research study according to the directions below. This is
different than a typical essay. Read the whole assignment and
ALL instructiions before beginning your paper.
Organize your paper using these headings, in this order. Your
paper should look like the following list/outline, with these
same subheadings listed in the same order. Just provide the
information for each section.
I already know that the authors of the article can identify their
purpose, hypothesis, etc. so you will not earn credit for copying
the information from the article. Show me what you understand
after reading the article. Explain each section very briefly so I
can see what you learned from reading the article. Your
summary of each section must be written in your own words. Do
not copy or simply paraphrase.
Reference: This should be so accurate that the reader can go
directly from your abstract to the original article. Give a
complete APA style reference. (Hint: the reference above is in
APA style, so your reference should like like that)
Purpose of the study: Sometimes the purpose is stated as an
aim, an objective, or a goal. At other times, it is incorporated in
a statement of a problem, leaving the reader to infer the purpose
has a stated problem, a purpose, or both. If the purpose is
inferred, you may state it in your own words.
Participants: The term “participant” refers to the sample
studied. Under this heading, you should include a description of
ages, sexes, socio-economic status, school grade, mental level,
number, and/or any other demographic characteristics given in
the article to describe the particular sample used in the study.
Type of Study: Was it a quantitative or a qualitative study? Or
were both types of data used? Please explain why you think so.
Hypothesis: What is the hypothesis of the study? If
the hypothesis is inferred, you may state it in your own words.
Procedure: Sometimes the procedure is referred to as the
“method” and includes a description of control techniques,
measuring devices, materials used and ways of proceeding, in
attempting to achieve the purpose or purposes of the study.
Statistical Tests: Identify the statistical tests used in the article;
examples might be chi square (x2), t-test, f-test, Mann-Whitney,
etc.
Results or Findings: What actual data was reported by the
author of the study? Explain the results -- don't just copy them.
Conclusions: What does the author of the research
article believe the results or findings mean?
Critique: In each of the previous sections, you have been
reporting what the article said. Now, I want you to think
critically about what you've learned, and give me your
own thoughts. Briefly describe your reaction to the article. For
example, was it well-organized? Easy or difficult to understand
(please explain why)? Did it present diverse perspectives about
the topic? Don't limit yourself to just these questions -- be
reflective about what you read.
ASSIGNMENT EXPECTATIONS: Please read before
completing assignments.
· Copy the actual assignment from this page onto the cover page
of your paper (do this for all papers in all courses).
· Assignment should be approximately 1 page in length, and no
more than 2 pages (double-spaced). You are not restricted to a
certain number of words, as you would be if you were preparing
an abstract for publication.
· Please use major sections corresponding to the major points of
the assignment, and where appropriate use sub-sections (with
headings).
· Remember to write in a Scientific manner (try to avoid using
the first person except when describing a relevant personal
experience).
· Quoted material should not exceed 10% of the total paper
(since the focus of these assignments is on independent thinking
and critical analysis). Use your own words and build on the
ideas of others.
· When material is copied verbatim from external sources, it
MUST be properly cited. This means that material copied
verbatim must be enclosed in quotes and the reference should be
cited either within the text or with a footnote.

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  • 1. please just write the bulk of the paper with in text citations and a work cited page as well don’t worry about title page and header and footer I will edit that upon completion. To access articles in the Library for this class and others, please refer to the instructions on the Syllabus and in Case 1. For the session long project, choose one area within the health issue below as your research topic. You will focus on the same topic for your SLP throughout the session. Traumatic brain injury Before you begin, read the instructions and expectations carefully -- this is not a typical report-style assignment. Narrow down the topic to a certain part of the population (i.e. an age group, gender, a certain race or ethnicity, or a particular geographic area). It will help to do some research before choosing your focus, so you can see what literature will be available to use throughout the session. Look at the SLP in Modules 2 - 5 so you can plan ahead as approporiate. Use credible professional sources such as ProQuest or EBSCO articles, or Websites from a university, government, or nonprofit organization to search for information about the issue. Consumer sources such as e-magazines, newspapers, and .com sites are not appropriate. 1. Introduce the topic and write a brief background about the scope of the problem. What is the health effect? How many people does it affect? Is there a treatment or a cure? What kind of research is being conducted about the problem? This part of the paper should be approximately 1 page. 2. Now, based on what you learned about the topic, think about what the gaps in knowledge seem to be. They are often stated in the "conclusions" of research articles. Using that information, do the following: State a properly phrased health-related research question that you would like to answer if you were a researcher. Review the
  • 2. information in the link provided on the Background Information page so you are clear as to what a research question is. This should not be a paragraph or an explanation, just a research question. 3. Now, formulate a specific hypothesis to investigate that research question. Again, this should not be a paragraph or an explanation, just a properly stated hypothesis. Review the information in the links provided on the Background Information page so you are clear as to what a hypothesis is. ASSIGNMENT EXPECTATIONS: Please read before completing assignments. · Copy the actual assignment from this page onto the cover page of your paper (do this for all papers in all courses). · Assignment should be 2 pages in length (double-spaced). · Please use major sections corresponding to the major points of the assignment, and where appropriate use sub-sections (with headings). · Remember to write in a Scientific manner (try to avoid using the first person except when describing a relevant personal experience). · Quoted material should not exceed 10% of the total paper (since the focus of these assignments is on independent thinking and critical analysis). Use your own words and build on the ideas of others. · When material is copied verbatim from external sources, it MUST be properly cited. This means that material copied verbatim must be enclosed in quotes and the reference should be cited either within the text or with a footnote. · Use of peer-reviewed articles is required. Websites as references should be minimal and must be professional sources (such as university, government, nonprofit) rather than consumer sources (such as e-magazines and .com sites).
  • 3. Cognitive Complexity Metrics and its Impact on Software Reliability Based on Cognitive Software Development Model Dharmender Singh Kushwaha and A.K.Misra Department of Computer Science and Engineering Moti Lal Nehru National Institute Of Technology Allahabad, India. Email:[email protected],[email protected] Abstract Software metrics provide a quantitative basis for the development and validation of models of software development process. Information gained from metrics is used in managing the development process in order to improve the reliability and quality of software product. The software metric is used to estimate various parameters of software development lifecycle such as cost, schedule productivity, quality and reliability. In this paper, an attempt has been made to frame the cognitive complexity metrics that will aid in increasing the reliability of software product being developed during the development lifecycle. Keywords Cognitive Software Development Model,Cognitive Documentation Complexity, Metacognition, Cognitive Software Inspection Process, Cognitive Requirement Engineering. 1. Introduction
  • 4. Metrics are a useful means for monitoring progress, attaining more accurate estimation of milestones and developing a software system that contains minimal faults thus improving the quality. Measures are necessary to identify weaknesses of the development process. They also prompt the necessary corrective activities and enable us to monitor the results. Hence they act as feedback mechanism that plays a vital role in the improvement of the software development process. There is an urgent need of software metrics to monitor the software development process for improving the overall quality of the software . Since complexity metrics are a significant and determinant factor of a systems success or failure, there is always a higher risk involved when the complexity measurement is ignored. Software metrics have been used for over three decades to assess or predict properties of software systems, but success has been limited by factors such as lack of sound models, the difficulty of conducting controlled repeatable experiments in educational or commercial context, and the inability to compare data obtained by different researchers. It is hypothesized that an overly complex code (i.e. an unstructured code with low cohesion) will be difficult to maintain and is likely to be unreliable. In order to create software, our design decisions, cognition, metacognition learning process and problem comprehensibility should be able to guide us to create software such that overall complexity is reduced. The most efficient way
  • 5. to deal with developing reliable software for large systems is by creating smaller modules. Weyuker’s [7] property 5 (∀ P)( ∀ Q)(|P| ≤ |P;Q| and |Q| ≤ |P;Q|) just aims to achieve this. The implication of this property is that as the size of program segment is increased, its complexity should also increase. Hence the divide and conquers technique which relies on decomposing the original problem into sub-problems with well defined interactions will lead to a structured design that will make the software reliable and maintainable. Cognitive aspects focus on the ease of understanding or the property of comprehension. Comprehension is the key feature that distinguishes any entity as being complex or simple. Comprehensibility of a problem helps in efficient design solution and improvement of software product quality. Thus property of comprehensibility can be used in all the different phases of software engineering. 2. Cognitive Software Development Model Kushwaha and Misra [5] have proposed Cognitive Software Development Model, with emphasis on cognitive aspects. This cognitive model of software development is based on the following broad phenomena:
  • 6. • Cognitive process of requirement engineering; • Cognitive system analysis; • Cognitive system design; • Assigning team members to different tasks based on the cognitive phenomena; • Cognitive approach to software inspection and testing; • Cognitive documentation style. The cognitive software development model of software development is illustrated in fig.1 It can be inferred from the cognitive software development model that the phases that also contribute to software reliability are: 1. Cognitive phenomena based team member selection; 2. Human centric requirement engineering; 3. Cognitive software inspection, a part of testing; 4. Documentation based on cognitive phenomena and 5. Validation by Metrics. Hence the following sections of our paper will elaborate on how above-mentioned factors and metrics will help in development of reliable software systems. ACM SIGSOFT Software Engineering Notes Page 1 March 2006 Volume 31 Number 2
  • 7. 3. Reliability The basic requirement for software system is correctness. A program is correct if the output satisfies the output requirements for every input specified by the input requirements. There are active and passive approaches to achieve program correctness. The
  • 8. active approach takes the form of program correctness proofs. Passive approach takes the form of traditional testing and debugging. Since testing can only indicate the presence of bugs, not their absence, hence it is not possible to estimate the number of bugs remaining in the software system. Hence testing cannot guarantee program correctness. Based on the above reasoning the reliability of software can be defined as the probability that the subsequent execution and invocation of the program is also correct. Our approach to reliability is based on the theory of “Prevention is better than cure”. To achieve this, we propose our metrics that are constructive, analytic and cognitive in approach. We begin with human centric approach of requirement engineering in the next section. 4. Cognitive Process of Requirement Engineering Until now, the requirement engineering has focused on the following areas: • Abstract functional requirements; • Non- functional requirements; • System properties such as availability and performance;
  • 9. • System and environment requirements. The areas that have a major impact in requirement engineering but often ignored are: • They do not distinguish between the client and the end user. Since client is the one who first comes in contact with the software engineer / software practitioner representing the vendor and the end user is the one who has to use the software. The perspectives of both shall be different and should be gathered carefully.
  • 10. SYSTEM Cognitive Process of Requirement Engineering Problem Analysis System Design Sub-System Design Sub-System Interface Design Validation by Metrics Implementation / Development Testing Maintenance Cognitive Phenomena Based Team Member Selection
  • 11. Documentatio n based on Cognitive Phenomena Figure 1:Cognitive Software development moel • Client is not able to describe and establish the cognition and psychological level of the end users of the proposed system • The requirement analysis is not performed from the users point of view and as such system oriented requirement analysis is performed • The requirement-gathering phase doesn’t distinguish between low level details and cognition characteristics of these details. • System oriented design fails to uncover the need for domain specific training of the end user or change in human organization. The cognitive requirement-engineering model is proposed to provide a holistic description of cognitive characteristics of the system under study (including the cognitive characteristics of the end user). Cognitive characteristics capture information such as user preferences. These also help in understanding the cognitive
  • 12. phenomena of the user, which will help in streamlining further interactions with the users in producing reliable software. We propose a model to describe the cognitive characteristics of the different user as depicted in fig. 2. The requirement analyst has the responsibility of analyzing the requirements and views. The requirement gathering, if properly ACM SIGSOFT Software Engineering Notes Page 2 March 2006 Volume 31 Number 2 classified depending on the kind of user interacted with, will provide for a total system view, thereby reducing the number of interactions and the rework. These views can be organized as a tuple [RTP, RPROF, RAMAT, RNOV] representing requirements of top management, professional, amateur or novice user. Once the analyst is able to categorize the viewpoint of the users at different hierarchies with varying cognitive phenomena, the overall system developed will be in total synch not only with the explicitly stated requirements but also with the implicit ones. Also the information domain of the system to be developed must be clearly understood.
  • 13. The requirement-engineering model is depicted in fig. 3. The person who is the catalyst behind the request for the software will play a key role in extending the need analysis and hence carrying out the requirement analysis. Once proper requirement engineering has been carried out, we can safely proceed to problem analysis. This will reduce the amount of rework. SYSTEM USER TOP MANAGEMENT END USER NEW CLIENT EXISTING
  • 14. CLIENT COGNITIVE PHENOMENA Professional Amateur Novice Figure 2: Cognitive characteristics of user 5. Cognitive Software Inspection and Team Member Selection As the software system evolves and grows larger, the effort and cost needed by verification process grows astronomically. Dolan [6] reports a 30 times return on investment for every hour devoted to the software inspection. Software inspection process is still far from optimal, and one area that has seen limited research is the impact of team member selection on it.
  • 15. The bottlenecks of code inspection are: Operational Characteristics Of Organization Cognitive Characteristics of User Feasibility Study and Report Requirement Elicitation Cognitive Character- istics of Requirement Elicitation Requirement Specification Require - ment Validation Require-ment
  • 16. Documentation Figure 3 : Cognitive Requirement Engineering Model • Lack of research on team member selection • Incorrect selection mechanism of team members • Team members sharing / possessing similar view point to a particular problem ACM SIGSOFT Software Engineering Notes Page 3 March 2006 Volume 31 Number 2 • It is a cognitive phenomenon, but unfortunately, it has been seen in terms of technical maturity of team member performing the code inspection. SOFTWARE ENGINEER / PROFESSIONAL REALISTIC IDEALISTIC
  • 17. Solution Seeking PROFESSIO AMATEURS NALS GUI Design Deve loped Higher level Cognitive Function Sub - Conscious Function Meta Cognition Function System
  • 18. Architect To overcome the above bottlenecks, a cognitive model of team selection procedure for software inspection is proposed based on the functionalities best performed depending on the cognitive activity level of team members. ure Coding Testing Coding Code Review & Testing Testing Requireme nt Gathering Code Review Quality Control
  • 19. Code Review SOFTWARE INSPECTION TEAM Figure 4: Cognitive phenomena based team member selection mechanism ACM SIGSOFT Software Engineering Notes Page 4 March 2006 Volume 31 Number 2 Wang [10], proposed cognitive phenomena, which classifies cognitive functions as sub-conscious, meta-cognitive and higher cognitive. Wang [8] described two types of programmers – realistic and idealistic. It is important issue to contrast and analyze the cognitive levels of the team members. It is agreed among researchers that increasing diversity among team members is the key to increasing the software inspection effectiveness. Hence creating inspection team with a combination of members from different cognitive levels will increase the effectiveness of code review, thereby reducing the testing effort.
  • 20. The difference between professionals and amateurs is whether their knowledge and skills are wired or temporary programmed in the brain [9]. For e.g. Professional software engineers possess wired skills in programming, and with a global view on software development. They focus not only on required functions, but also on exceptions-handling and fault tolerance. However, amateur programmers possess ad-hoc programming knowledge, eager to try what is directly required, and tend to focus on details without a global and systematic view. Hence software inspection and testing team should include members from this amateur category also, since they have the quality to have a narrow focus as illustrated in fig. 4. The amateurs try to deal with individual concepts before taking on the new ones are also candidate for testing and debugging. This will ascertain that the software inspection so carried out increases the reliability of software product. 6. Cognitive Documentation Complexity (CDC)
  • 21. Very little attention has been paid to the comprehensibility of various documents created during software development lifecycle. If a novice is able to understand the various documents, then we are sure of creating a reliable and quality artifact. Cognitive documentation complexity of a class can be measured in terms of the cognitive phenomena and the associated weight. There are numerous documentation types that will speak about the level of useful information provided by the documentation. Even today, header information, comments and use of good identifier names are considered to be the quality factors of best documentation. These practices, do not count on the comprehensibility and the cognitive phenomenon of the mind that assists the software developer in reducing the comprehension effort and improving the coding standard. If the documentation provides reasonable amount of useful information about the class to a novice, average and expert software practitioner, it implies that ready understandability was present in the documentation of the class and is termed to be of high quality. On the contrary, if only expert practitioner understands the documentation, then the documentation quality is
  • 22. termed to be low. This also implies that sub-conscious cognitive functions (the one that are not wired) are not enough in comprehending the documentation. The classification of cognitive phenomenon is as described by Wang [10]. This is summarized in the table below. S.No Cognitive Phenomena associated with Documentation Quality of Documentation 1. Sub – Conscious Cognitive function High-Quality 2. Meta – Cognitive function Average-Quality 3. Higher Cognitive functions Low-Quality Table 1: Quality of Documentation Based on Cognitive Phenomena High quality documents are very useful and enable us to:
  • 23. • Enhance comprehensibility of software product • Reduce maintenance cost • Effectively exploit the system • Reduce re-engineering cost and effort. 7. Cognitive Conceptual Complexity of Class / Module The syntactic metrics measure the complexity of the software. It is the details of implementation that determines the comprehension complexity [1, 2]. We also need some metrics to measure the psychological complexity that measures the difficulty of understanding of the software module. This psychological complexity is based on the number of distinct key concepts in the class or module and is defined as m CCCC = ∑ [(No. of distinct Cognitive Concepts) * (Weight of i=1 Concept)]i
  • 24. Where ‘m’ is the number of distinct concepts in the class or module. The weighing factor of cognitive concepts is based on the classification of cognitive phenomenon as described by Wang [8], is as follows: S.No Cognitive Phenomena Weight 1. Sub – Conscious Cognitive function 1 2. Meta – Cognitive function 2 3. Higher Cognitive functions 3 Table 2: Weights Based on Cognitive Phenomena Higher weight indicates that greater amount of comprehension effort is required in understanding the software module under consideration. If there exists a distinct concept but is not
  • 25. understood by the practitioner (because he may be novice or semi- skilled), it is the subconscious life function that will guide him to identify it. Hence higher weight is associated with it. Higher cognitive functions will require lower comprehension effort and hence lower weight associated with it. The mind is an artifact model of oneself and a thinking engine. The mind, as a virtual model of a person in the brain, is partially programmed and partially wired. The former is evolved for the flexibility of the life functions while the latter is formed for the efficiency of frequently conducted activities. The complexity of the class can be calculated by using the CICM metric that is a robust cognitive complexity measure [3, 4]. 8. Conclusion ACM SIGSOFT Software Engineering Notes Page 5 March 2006 Volume 31 Number 2
  • 26. This paper is based on the cognitive software development model. It has made an attempt to emphasize the importance of cognitive metrics and its impact in achieving reliable software development. It also identifies those areas that are vital to reliable software development process but have been either ignored or given lower degree of importance by the researcher community in the past. In future, we shall work to propose cognitive complexity metrics for all the phases of cognitive software development model in order to produce software that is not only reliable but is of highest quality. References [1] Kushwaha, D.S. and Misra, A.K.,: A Complexity Measure Based on Information Contained in the Software, 5th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (SEPADS 2006), Madrid, Spain, To Appear, Feb. 2006.
  • 27. [2] Kushwaha, D.S. and Misra, A.K.: Cognitive Complexity Measure of Object-Oriented Software – A Practitioners Approach, 5th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (SEPADS 2006), Madrid, Spain, To Appear. Feb. 2006. [3] Kushwaha D.S.and.Misra A.K: “Robustness Analysis of Cognitive Information Complexity Measure using Weyuker Properties”, ACM SIGSOFT Software Engineering Notes, Vol. 31, No. 7, January 2006. [4] Kushwaha D.S.and.Misra A.K: “Evaluating Cognitive Information Complexity Measure ”, 13th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems (ECBS) To Appear,2006. [5] Kushwaha, D.S. and Misra, A.K.: A Cognitive Complexity Metric Suite for Object-Oriented Software”, WSEAS Transactions on Computers, To Appear, Feb. 2006. [6] E.P.Doolan, :Experience with Fagans Inspection Method, Software Practice and Experience. Vol. 2, No. 2, pp. 173-182, Feb. 1992. [7] Weyuker, E.,: Evaluating software complexity measure. IEEE
  • 28. Transaction on Software Engineering Vol. 14(9): 1357-1365, september1988. [8] Wang,Y.,: On The Cognitive Informatics Foundations of Software Engineering, IEEE International Conference on Cognitive Informatics, 2004. [9] Wang,Y.,: On The Informatics Laws of Software, IEEE International Conference on Cognitive Informatics, 2004. [10] Wang,Y.,: On Cognitive Informatics, Keynote Lecture, Proceedings of IEEE International Conference on Cognitive Informatics, 2002, pp. 34 – 42.
  • 29. ACM SIGSOFT Software Engineering Notes Page 6 March 2006 Volume 31 Number 2 Cognitive Complexity Metrics and its Impact on Software Reliability Based on Cognitive Software Development ModelAbstractKeywords1. Introduction2. Cognitive Software Development Model Kushwaha and Misra [5] have proposed Cognitive Software Development Model, with emphasis on cognitive aspects. This cognitive model of software development is based on the following broad phenomena:3. Reliability Table 2: Weights Based on Cognitive Phenomena 8. ConclusionReferences please just write the bulk of the paper with in text citations and a work cited page as well don’t worry about title page and header and footer I will edit that upon completion. thank you Assignment Being able to read and understand research studies requires quantitative reasoning. The purpose of this assignment is to help you get accustomed to identifying the various parts of a research study. Be sure to review the module homepage and background information before you begin any of the assignments in this course. In general, the best way to approach the assignment is to read the article through rather rapidly in order to get an impression
  • 30. of its general content; then read it more slowly and make appropriate notes so you can complete the assignment as directed below. Review the instructions and the ASSIGNMENT EXPECTATIONS below, and then read this research article, retrieved from Proquest: Van Voorhees, Benjamin W, MD, MPH, Gollan, J., PhD., & Fogel, J., PhD. (2012). Pilot study of internet-based early intervention for combat-related mental distress. Journal of Rehabilitation Research and Development, 49(8), 1175-90. Retrieved from Proquest. Your task is to identify and summarize the main points of the research study according to the directions below. This is different than a typical essay. Read the whole assignment and ALL instructiions before beginning your paper. Organize your paper using these headings, in this order. Your paper should look like the following list/outline, with these same subheadings listed in the same order. Just provide the information for each section. I already know that the authors of the article can identify their purpose, hypothesis, etc. so you will not earn credit for copying the information from the article. Show me what you understand after reading the article. Explain each section very briefly so I can see what you learned from reading the article. Your summary of each section must be written in your own words. Do
  • 31. not copy or simply paraphrase. Reference: This should be so accurate that the reader can go directly from your abstract to the original article. Give a complete APA style reference. (Hint: the reference above is in APA style, so your reference should like like that) Purpose of the study: Sometimes the purpose is stated as an aim, an objective, or a goal. At other times, it is incorporated in a statement of a problem, leaving the reader to infer the purpose has a stated problem, a purpose, or both. If the purpose is inferred, you may state it in your own words. Participants: The term “participant” refers to the sample studied. Under this heading, you should include a description of ages, sexes, socio-economic status, school grade, mental level, number, and/or any other demographic characteristics given in the article to describe the particular sample used in the study. Type of Study: Was it a quantitative or a qualitative study? Or were both types of data used? Please explain why you think so. Hypothesis: What is the hypothesis of the study? If the hypothesis is inferred, you may state it in your own words. Procedure: Sometimes the procedure is referred to as the “method” and includes a description of control techniques, measuring devices, materials used and ways of proceeding, in attempting to achieve the purpose or purposes of the study. Statistical Tests: Identify the statistical tests used in the article; examples might be chi square (x2), t-test, f-test, Mann-Whitney,
  • 32. etc. Results or Findings: What actual data was reported by the author of the study? Explain the results -- don't just copy them. Conclusions: What does the author of the research article believe the results or findings mean? Critique: In each of the previous sections, you have been reporting what the article said. Now, I want you to think critically about what you've learned, and give me your own thoughts. Briefly describe your reaction to the article. For example, was it well-organized? Easy or difficult to understand (please explain why)? Did it present diverse perspectives about the topic? Don't limit yourself to just these questions -- be reflective about what you read. ASSIGNMENT EXPECTATIONS: Please read before completing assignments. · Copy the actual assignment from this page onto the cover page of your paper (do this for all papers in all courses). · Assignment should be approximately 1 page in length, and no more than 2 pages (double-spaced). You are not restricted to a certain number of words, as you would be if you were preparing an abstract for publication. · Please use major sections corresponding to the major points of the assignment, and where appropriate use sub-sections (with headings).
  • 33. · Remember to write in a Scientific manner (try to avoid using the first person except when describing a relevant personal experience). · Quoted material should not exceed 10% of the total paper (since the focus of these assignments is on independent thinking and critical analysis). Use your own words and build on the ideas of others. · When material is copied verbatim from external sources, it MUST be properly cited. This means that material copied verbatim must be enclosed in quotes and the reference should be cited either within the text or with a footnote.