This document provides an outline and overview of requirements elicitation and specifications for a system analysis and design course. It discusses key topics like the importance of requirements, types of requirements including functional and non-functional, techniques for eliciting requirements like interviews and questionnaires, prioritizing requirements, validating requirements, and managing requirements. The document is intended to educate students on properly defining what a system must do through detailed requirements.
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Presentation at the University of Miami on 3 December 2021 on how Stack Overflow improved the retention of new contributors whose initial question is rejected (closed) as substandard. The presentation is based on a paper coauthored with Sunil Wattal.
With the help of this powerpoint presentation, Ken Mease, discusses the advantages of various types of data sources and collection methods, including archival and secondary data, survey data, quantitative and qualitative approaches and data, and finally de jure and de facto information. The presentation was held at the Workshop on Governance Assessment Methods and Applications of Governance Data in Policy-Making (June 2009)
Not Good Enough but Try Again! Mitigating the Impact of Rejections on New Con...Aleksi Aaltonen
Presentation at the University of Miami on 3 December 2021 on how Stack Overflow improved the retention of new contributors whose initial question is rejected (closed) as substandard. The presentation is based on a paper coauthored with Sunil Wattal.
With the help of this powerpoint presentation, Ken Mease, discusses the advantages of various types of data sources and collection methods, including archival and secondary data, survey data, quantitative and qualitative approaches and data, and finally de jure and de facto information. The presentation was held at the Workshop on Governance Assessment Methods and Applications of Governance Data in Policy-Making (June 2009)
Correlation Technology Business Solutions: Market Researchs0P5a41b
This is a no-nonsense business-to-business document containing an in-depth analysis of the market research industry, its competitive landscape, major players, and complete SWOT analysis. Specific problems currently facing the industry are identified, and the disruptive impact of Correlation Technology when used to provide new dynamic solutions to traditional market research challenges. Update: This document and accompanying SWOT analysis has been updated to reflect changes to the competitive landscape in the industry created by the acquisition of Synovate by IPSOS in 2011.
an efficient approach for co extracting opinion targets based in online revie...INFOGAIN PUBLICATION
Mining opinion targets and opinion words from on-line reviews square measure vital tasks for fine-grained opinion mining, the key part of that involves detective work opinion relations among words.We propose An Efficient Approach for Co-Extracting Opinion Targets in Online Reviews Based on Supervised Word-Alignment Model it is a unique approach supported the fully-supervised alignment model that regards distinctive opinion relations as an alignment method. Then, a graph-based Re-ranking algorithmic rule is exploited to estimate the boldness of every candidate. This Re-ranking algorithm is used to achieve the better results from co-extracting word alignment model. Finally, candidates with higher confidence area unit extracted as opinion targets or opinion words. Compared to previous ways supported the nearest-neighbor rules, our model captures opinion relations a lot of exactly, particularly for long-span relations. Compared to syntax-based ways, our word alignment model effectively alleviates the negative effects of parsing errors once managing informal on-line texts. In explicit, compared to the normal unsupervised alignment model, the planned model obtains higher exactness attributable to the usage of fully oversight. Additionally, once estimating candidate confidence, we have a tendency to punish higher-degree vertices in our graph-based Re-ranking algorithmic rule to decrease the likelihood of error generation. Our experimental results on 3 corpora with completely different sizes and languages show that our approach effectively outperforms progressive ways.
ASPECT-BASED OPINION EXTRACTION FROM CUSTOMER REVIEWScsandit
Text is the main method of communicating information in the digital age. Messages, blogs,
news articles, reviews, and opinionated information abounds on the Internet. People commonly
purchase products online and post their opinions about purchased items. This feedback is
displayed publicly to assist others with their purchasing decisions, creating the need for a
mechanism with which to extract and summarize useful information for enhancing the decisionmaking
process. Our contribution is to improve the accuracy of extraction by combining
different techniques from three major areas, namedData Mining, Natural Language Processing
techniques and Ontologies. The proposed framework sequentially mines product’s aspects and
users’ opinions, groups representative aspects by similarity, and generates an output summary.
This paper focuses on the task of extracting product aspects and users’ opinions by extracting
all possible aspects and opinions from reviews using natural language, ontology, and frequent
“tag”sets. The proposed framework, when compared with an existing baseline model, yielded
promising results.
Automatic vs. human question answering over multimedia meeting recordingsLê Anh
Information access in meeting recordings can be assisted by
meeting browsers, or can be fully automated following a
question-answering (QA) approach. An information access task
is defined, aiming at discriminating true vs. false parallel statements
about facts in meetings. An automatic QA algorithm is
applied to this task, using passage retrieval over a meeting transcript.
The algorithm scores 59% accuracy for passage retrieval,
while random guessing is below 1%, but only scores 60% on
combined retrieval and question discrimination, for which humans
reach 70%–80% and the baseline is 50%. The algorithm
clearly outperforms humans for speed, at less than 1 second
per question, vs. 1.5–2 minutes per question for humans. The
degradation on ASR compared to manual transcripts still yields
lower but acceptable scores, especially for passage identification.
Automatic QA thus appears to be a promising enhancement
to meeting browsers used by humans, as an assistant for
relevant passage identification.
Usability Testing Basics: What's it All About? at Web SIG ClevelandCarol Smith
Presented to Web SIG Cleveland on May 21, 2011 at Notre Dame College in South Euclid (Cleveland), Ohio.
Learn all you need to get started:
- Where you can conduct studies (does it have to be in a lab?)
- Types of studies (RITE, think aloud, etc.)
- Tips for recruiting participants
- Tips for Interacting with participants without biasing the study
- Preparing for the study (materials needed, forms, etc.)
- Guidance for analyzing the study
Different Methods of Collection of DataP. Veeresha
Data collection is a term used to describe a process of preparing and collecting data.
Data are the basic inputs to any decision making process in any fields like education, business, industries…. etc
The primary data are those which are collected afresh and for the first time, and thus happen to be original in character. It is real time data and which are collected by the researcher himself.
Secondary data means data that are already available i.e., they refer to the data which have already been collected and analyzed by someone else.
Correlation Technology Business Solutions: Market Researchs0P5a41b
This is a no-nonsense business-to-business document containing an in-depth analysis of the market research industry, its competitive landscape, major players, and complete SWOT analysis. Specific problems currently facing the industry are identified, and the disruptive impact of Correlation Technology when used to provide new dynamic solutions to traditional market research challenges. Update: This document and accompanying SWOT analysis has been updated to reflect changes to the competitive landscape in the industry created by the acquisition of Synovate by IPSOS in 2011.
an efficient approach for co extracting opinion targets based in online revie...INFOGAIN PUBLICATION
Mining opinion targets and opinion words from on-line reviews square measure vital tasks for fine-grained opinion mining, the key part of that involves detective work opinion relations among words.We propose An Efficient Approach for Co-Extracting Opinion Targets in Online Reviews Based on Supervised Word-Alignment Model it is a unique approach supported the fully-supervised alignment model that regards distinctive opinion relations as an alignment method. Then, a graph-based Re-ranking algorithmic rule is exploited to estimate the boldness of every candidate. This Re-ranking algorithm is used to achieve the better results from co-extracting word alignment model. Finally, candidates with higher confidence area unit extracted as opinion targets or opinion words. Compared to previous ways supported the nearest-neighbor rules, our model captures opinion relations a lot of exactly, particularly for long-span relations. Compared to syntax-based ways, our word alignment model effectively alleviates the negative effects of parsing errors once managing informal on-line texts. In explicit, compared to the normal unsupervised alignment model, the planned model obtains higher exactness attributable to the usage of fully oversight. Additionally, once estimating candidate confidence, we have a tendency to punish higher-degree vertices in our graph-based Re-ranking algorithmic rule to decrease the likelihood of error generation. Our experimental results on 3 corpora with completely different sizes and languages show that our approach effectively outperforms progressive ways.
ASPECT-BASED OPINION EXTRACTION FROM CUSTOMER REVIEWScsandit
Text is the main method of communicating information in the digital age. Messages, blogs,
news articles, reviews, and opinionated information abounds on the Internet. People commonly
purchase products online and post their opinions about purchased items. This feedback is
displayed publicly to assist others with their purchasing decisions, creating the need for a
mechanism with which to extract and summarize useful information for enhancing the decisionmaking
process. Our contribution is to improve the accuracy of extraction by combining
different techniques from three major areas, namedData Mining, Natural Language Processing
techniques and Ontologies. The proposed framework sequentially mines product’s aspects and
users’ opinions, groups representative aspects by similarity, and generates an output summary.
This paper focuses on the task of extracting product aspects and users’ opinions by extracting
all possible aspects and opinions from reviews using natural language, ontology, and frequent
“tag”sets. The proposed framework, when compared with an existing baseline model, yielded
promising results.
Automatic vs. human question answering over multimedia meeting recordingsLê Anh
Information access in meeting recordings can be assisted by
meeting browsers, or can be fully automated following a
question-answering (QA) approach. An information access task
is defined, aiming at discriminating true vs. false parallel statements
about facts in meetings. An automatic QA algorithm is
applied to this task, using passage retrieval over a meeting transcript.
The algorithm scores 59% accuracy for passage retrieval,
while random guessing is below 1%, but only scores 60% on
combined retrieval and question discrimination, for which humans
reach 70%–80% and the baseline is 50%. The algorithm
clearly outperforms humans for speed, at less than 1 second
per question, vs. 1.5–2 minutes per question for humans. The
degradation on ASR compared to manual transcripts still yields
lower but acceptable scores, especially for passage identification.
Automatic QA thus appears to be a promising enhancement
to meeting browsers used by humans, as an assistant for
relevant passage identification.
Usability Testing Basics: What's it All About? at Web SIG ClevelandCarol Smith
Presented to Web SIG Cleveland on May 21, 2011 at Notre Dame College in South Euclid (Cleveland), Ohio.
Learn all you need to get started:
- Where you can conduct studies (does it have to be in a lab?)
- Types of studies (RITE, think aloud, etc.)
- Tips for recruiting participants
- Tips for Interacting with participants without biasing the study
- Preparing for the study (materials needed, forms, etc.)
- Guidance for analyzing the study
Different Methods of Collection of DataP. Veeresha
Data collection is a term used to describe a process of preparing and collecting data.
Data are the basic inputs to any decision making process in any fields like education, business, industries…. etc
The primary data are those which are collected afresh and for the first time, and thus happen to be original in character. It is real time data and which are collected by the researcher himself.
Secondary data means data that are already available i.e., they refer to the data which have already been collected and analyzed by someone else.
these are mainly the IT questions mainly asked by IT companies or organization when. employing workers its a review of how people can answer and what they should be prepared for in such a situation.
Fact Finding Techniques:
Introduction to Fact finding techniques,
Decision Tables and trees,
Normalization and its types-
(1st, 2nd, 3rd, 4th, 5th, and Boyce code normal forms),
Introduction to Object oriented programming concepts.
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1. CS 0124:
System Analysis and
Design
By
Mr. Bernard Julius
Bsc (Hons). Computer Science UDSM
Msc. Information Technology Development and Management
(NM-AIST)
2. REQUIREMENTS ELICITATION AND
SPECIFICATIONS
OUTLINE
Introduction to Requirements
Importance of Requirements
Types of Requirements
Requirements Elicitation/Gathering
Techniques
Prioritization of Requirements
Requirements Validation
Requirements Management
3. Introduction to Requirements
Requirements determination is performed to
transform the system request’s high level statement
of business requirements into a more detailed,
precise list of what the new system must do to
provide the needed value to the business.
This detailed list of requirements is supported,
confirmed, and clarified by the other activities of the
analysis phase: creating use cases, building process
models, and building a data model.
We first explain what a requirement is and discuss
the process of creating a requirements definition
statement.
4. What is a Requirement?
A requirement is simply a statement of what the system
must do or what characteristics it needs to have or
descriptions of the services that a system must provide
and the constraints under which it must operate .
It may range from a high-level abstract statement of a
service or of a system constraint to a detailed
mathematical functional specification
During a systems development project, requirements will
be created that describe what the business needs
(business requirements); what the users need to do (user
requirements); what the software should do ( functional
requirements); characteristics the system should have
(nonfunctional requirements); and how the system
should be built (system requirements).
5. Importance of Requirements
To provide system developers with a better
understanding of the system requirements.
To define the boundaries of (delimit) the system.
To provide a basis for planning the technical contents
of iterations.
To provide a basis for estimating cost and time to
develop the system.
To define a user-interface for the system, focusing on
the needs and goals of the users.
6. Types of Requirements
User requirements
o Statements in natural language plus
diagrams of the services that the
systems provides and its operational
constraints.
o Written for customers
7. Types of Requirements
System Requirements
o A structured document setting out
detailed descriptions of the system
services.
o Written for developers
o They may be functional or non-functional
requirements
8. Functional and Non-functional
Requirements
Functional Requirements
o Describe functionality or system
services.
o Depend on the type of software,
expected users and the type of system
where the software is used.
o Functional system requirements should
describe the system services in detail.
9. Functional and Non-functional
Requirements
Non-Functional Requirements
o Requirements which specify that the
delivered product must behave in a
particular way, e.g. execution speed,
reliability, availability, usability, security
etc.
11. Interviews
The interview is the most commonly used requirements
elicitation technique. After all, it is natural—usually, if
you need to know something, you ask someone.
In general, interviews are conducted one on one (one
interviewer and one interviewee), but sometimes, due to
time constraints, several people are interviewed at the
same time.
There are five basic steps to the interview process:
selecting interviewees, designing interview questions,
preparing for the interview, conducting the interview, and
post interview follow-up.
12. Interviews
An interview schedule should be created, listing who will
be interviewed, the purpose of the interview, and where
and when it will take place.
The people who appear on the interview schedule are
selected on the basis of the analyst’s information needs.
There are three types of interview questions: closed-
ended questions, open-ended questions, and probing
questions.
13. Interview
Closed ended questions require a specific answer. You
can think of them as being similar to multiple choice or
arithmetic questions on an exam. Closed ended
questions require a specific answer. You can think of
them as being similar to multiple choice or arithmetic
questions on an exam.
Open-ended questions are those that leave room for
elaboration on the part of the interviewee. They are
similar in many ways to essay questions that you might
find on an exam. Open-ended questions are designed to
gather rich information and give the interviewee more
control over the information that is revealed during the
interview
Probing questions encourage the interviewee to expand
on or to confirm information from a previous response,
and they are a signal that the interviewer is listening and
interested in the topic under discussion.
14. Questionnaires
A questionnaire is a set of written questions for
obtaining information from individuals.
Questionnaires often are used when there is a large
number of people from whom information and opinions
are needed. In our experience, questionnaires are
commonly used for systems intended for use outside of
the organization (e.g., by customers or vendors) or for
systems with business users spread across many
geographic locations.
Most people automatically think of paper when they think
of questionnaires, but today more questionnaires are
being distributed in electronic form, either via e-mail or
on the Web. Electronic distribution can save a significant
amount of money, compared with distributing paper
questionnaires.
15. Questionnaires
As with interviews and JAD sessions, the first step is to
select the individuals to whom the questionnaire will be
sent.
However, it is not usual to select every person who could
provide useful information. The standard approach is to
select a sample, or subset, of people who are
representative of the entire group.
Developing good questions is critical for questionnaires
because the information on a questionnaire cannot be
immediately clarified for a confused respondent.
Systems analysts have additional techniques to improve
responses rates inside the organization, such as
personally handing out the questionnaire and personally
contacting those who have not returned them after a
week or two, as well as requesting the respondents’
supervisors to administer the questionnaires in a group
meeting.
16. Questionnaires
Good questionnaire Design
o Begin with nonthreatening and interesting
questions.
o Group items into logically coherent sections.
o Do not put important items at the very end of
the questionnaire.
o Do not crowd a page with too many items.
o Avoid abbreviations.
o Avoid biased or suggestive items or terms.
o Number questions to avoid confusion.
o Pretest the questionnaire to identify confusing
questions.
o Provide anonymity to respondents.
17. Observation
Observation is the act of watching processes being
performed, is a powerful tool to gain insight into the as-is
system. Observation enables the analyst to see the
reality of a situation, rather than listening to others
describe it in interviews or JAD sessions.
Observation is a good way to check the validity of
information gathered from other sources such as
interviews and questionnaires.
Observation is often used to supplement interview
information
For example, an analyst might become skeptical of
someone who claims to use the existing computer
system extensively if the computer is never turned on
while the analyst visits
18. Document Analysis
Project teams often use document analysis to
understand the as-is system
These documents (forms, reports, policy
manuals, organization charts) only tell part of
the story. They represent the formal system
that the organization uses.
Thus, it is useful to review both blank and
completed forms to identify the requirements
19. Requirements Prioritization
There are usually more requirements than you can
implement given stakeholder`s time and resource
constraints,
Lot`s of
requirements
Few
resources
20. Requirements Prioritization
... on the other hand, systems have
useless functions for the users and
customers!
Large amount of the software
functions are ”rarely” (19%) or
”never used” (45%) [Moi00]
21. Requirements Validations
Certifies that the requirements document is an
acceptable description of the system to be
implemented
Checks a requirements document for
Completeness and consistency
Conformance to standards
Requirements conflicts
Technical errors
Ambiguous requirements
22. Requirements Management
It is often the case that more than
50% of a system’s requirements will
be modified before it is put into
service [Kot98].
New requirements emerge and
existing change due to
o errors
o increased understanding
o change in external circumstances.
23. Requirements Management
Changes to the requirements should be
documented and controlled formally.
Change management process ensures
that
o changes are made systematically
o similar information is collected for each
proposed change
o overall analysis is made about the costs,
benefits and timing
o the requirements document is updated.