The document provides an overview of software cost estimation. It discusses factors that influence software cost such as programmer ability, product size, available time, required reliability, and level of technology. It also covers different software cost estimation techniques including expert judgment, Delphi estimation, work breakdown structures, algorithmic models like COCOMO, and estimating maintenance costs. The document emphasizes that accurate cost estimation is difficult during planning due to many unknown factors, so organizations may use iterative estimates to reduce cost overruns.
The document discusses software cost estimation and introduces the COCOMO model. It describes that COCOMO takes into account project attributes, product attributes, personnel attributes, and hardware attributes to predict development effort. It also explains that algorithmic cost models can be used to quantitatively analyze options by comparing the costs of different development strategies. Finally, it notes that project duration is independent of team size, and adding people too quickly can actually lead to schedule delays.
Software Cost Estimation in Software Engineering SE23koolkampus
Software cost estimation involves predicting resources required for development using metrics like productivity, size, and function points. The COCOMO 2 model is an empirical algorithmic model that estimates effort as a function of product, project, and process attributes. It operates at three levels - early prototyping based on object points, early design using function points mapped to lines of code, and post-architecture directly using lines of code. Key cost drivers include requirements, personnel experience, reuse, and development flexibility.
The document discusses software project management. It defines a software project as the complete process of software development from requirements gathering through testing and maintenance. A software project manager closely monitors the development process, prepares plans, arranges resources, and manages communication between team members. Software project management involves planning, scope management, estimation of size, effort, time and cost, and other activities. Estimation techniques include decomposition by functions or activities and empirical models. Lines of code is a common size metric but does not consider complexity. Effort estimation forecasts time required and project estimation uses a stepwise decomposition approach.
The document discusses project estimation and scheduling. It introduces the COCOMO model, which is an algorithmic cost modeling technique. COCOMO estimates software development effort, cost, and schedule as a function of several cost drivers and project attributes. It can be used for early rough estimates and provides more accurate estimates than subjective methods alone. The document explains the different COCOMO modes and models and how to apply the basic COCOMO equations.
The document discusses project estimation and scheduling. It introduces the COCOMO model, which is an algorithmic cost modeling technique. COCOMO estimates software development effort, cost, and schedule as a function of several cost drivers and project attributes. It categorizes projects into organic, semidetached, and embedded modes with different productivity rates and equations. The intermediate COCOMO model multiplies the basic estimate by effort adjustment factors based on ratings for 15 cost drivers.
spm cost estmate slides for bca 4-195245927.pptRidyaGupta1
This document discusses software cost estimation. It introduces metrics for assessing software productivity like lines of code and function points. It describes techniques for software estimation like algorithmic cost modeling, expert judgment, and analogy. The COCOMO 2 cost estimation model is explained, which uses multipliers for attributes like personnel experience and software size to predict project effort. Project duration, staffing needs, and how cost models support project planning options are also covered.
This document discusses software cost estimation. It introduces software cost estimation and describes objectives like introducing fundamentals of software costing and pricing, describing metrics for software productivity assessment, explaining different techniques for software estimation, and describing the COCOMO 2 cost estimation model. It covers topics like productivity, estimation techniques, algorithmic cost modeling, and project duration and staffing. It describes software cost components, costing and pricing factors, productivity measures and problems, and factors affecting productivity. It also explains various estimation techniques like algorithmic cost modeling, expert judgement, estimation by analogy, and Parkinson's Law. It provides details on the COCOMO 2 cost estimation model and its different levels.
The document discusses software project estimation and scheduling. It explains that accurate estimation is important to avoid cost overruns and schedule slips. Common problems with estimation include predicting software costs, schedules, and risks. Fundamental estimation questions relate to effort, time, and costs. Estimation methods include expert judgment, analogy, top-down and bottom-up approaches, and algorithmic modeling. Productivity and function measures are used to estimate software size. Changing technologies also impact estimation accuracy. Compression techniques can shorten schedules through crashing or fast tracking.
The document discusses software cost estimation and introduces the COCOMO model. It describes that COCOMO takes into account project attributes, product attributes, personnel attributes, and hardware attributes to predict development effort. It also explains that algorithmic cost models can be used to quantitatively analyze options by comparing the costs of different development strategies. Finally, it notes that project duration is independent of team size, and adding people too quickly can actually lead to schedule delays.
Software Cost Estimation in Software Engineering SE23koolkampus
Software cost estimation involves predicting resources required for development using metrics like productivity, size, and function points. The COCOMO 2 model is an empirical algorithmic model that estimates effort as a function of product, project, and process attributes. It operates at three levels - early prototyping based on object points, early design using function points mapped to lines of code, and post-architecture directly using lines of code. Key cost drivers include requirements, personnel experience, reuse, and development flexibility.
The document discusses software project management. It defines a software project as the complete process of software development from requirements gathering through testing and maintenance. A software project manager closely monitors the development process, prepares plans, arranges resources, and manages communication between team members. Software project management involves planning, scope management, estimation of size, effort, time and cost, and other activities. Estimation techniques include decomposition by functions or activities and empirical models. Lines of code is a common size metric but does not consider complexity. Effort estimation forecasts time required and project estimation uses a stepwise decomposition approach.
The document discusses project estimation and scheduling. It introduces the COCOMO model, which is an algorithmic cost modeling technique. COCOMO estimates software development effort, cost, and schedule as a function of several cost drivers and project attributes. It can be used for early rough estimates and provides more accurate estimates than subjective methods alone. The document explains the different COCOMO modes and models and how to apply the basic COCOMO equations.
The document discusses project estimation and scheduling. It introduces the COCOMO model, which is an algorithmic cost modeling technique. COCOMO estimates software development effort, cost, and schedule as a function of several cost drivers and project attributes. It categorizes projects into organic, semidetached, and embedded modes with different productivity rates and equations. The intermediate COCOMO model multiplies the basic estimate by effort adjustment factors based on ratings for 15 cost drivers.
spm cost estmate slides for bca 4-195245927.pptRidyaGupta1
This document discusses software cost estimation. It introduces metrics for assessing software productivity like lines of code and function points. It describes techniques for software estimation like algorithmic cost modeling, expert judgment, and analogy. The COCOMO 2 cost estimation model is explained, which uses multipliers for attributes like personnel experience and software size to predict project effort. Project duration, staffing needs, and how cost models support project planning options are also covered.
This document discusses software cost estimation. It introduces software cost estimation and describes objectives like introducing fundamentals of software costing and pricing, describing metrics for software productivity assessment, explaining different techniques for software estimation, and describing the COCOMO 2 cost estimation model. It covers topics like productivity, estimation techniques, algorithmic cost modeling, and project duration and staffing. It describes software cost components, costing and pricing factors, productivity measures and problems, and factors affecting productivity. It also explains various estimation techniques like algorithmic cost modeling, expert judgement, estimation by analogy, and Parkinson's Law. It provides details on the COCOMO 2 cost estimation model and its different levels.
The document discusses software project estimation and scheduling. It explains that accurate estimation is important to avoid cost overruns and schedule slips. Common problems with estimation include predicting software costs, schedules, and risks. Fundamental estimation questions relate to effort, time, and costs. Estimation methods include expert judgment, analogy, top-down and bottom-up approaches, and algorithmic modeling. Productivity and function measures are used to estimate software size. Changing technologies also impact estimation accuracy. Compression techniques can shorten schedules through crashing or fast tracking.
This document discusses various techniques for estimating software costs:
1. Expert judgment relies on experienced people's assessments but can be unreliable due to biases. The Delphi technique improves expert judgment by anonymously aggregating estimates over multiple rounds.
2. Work breakdown structures break projects down into components to estimate costs bottom-up. The COCOMO model also estimates bottom-up using algorithmic formulas adjusted by multipliers for attributes.
3. COCOMO is demonstrated through an example estimating effort of 191 person-months and a 13 month schedule for a 30,000 line embedded software project with high reliability requirements.
This document discusses software cost estimation. It describes the objectives of software cost estimation and the fundamental questions that must be answered. It explains different techniques for software cost estimation including algorithmic cost modeling, expert judgement, and estimation by analogy. A key part of the document focuses on the COCOMO model, including the different levels of COCOMO 2 for estimation. It also discusses using cost estimation for project planning and management.
A Review of Agile Software Effort Estimation MethodsEditor IJCATR
Software cost estimation is an essential aspect of software project management and therefore the success or failure of a software
project depends on accuracy in estimating effort, time and cost. Software cost estimation is a scientific activity that requires knowledge of a
number of relevant attributes that will determine which estimation method to use in a given situation. Over the years various studies were done
to evaluate software effort estimation methods however due to introduction of new software development methods, the reviews have not
captured new software development methods. Agile software development method is one of the recent popular methods that were not taken
into account in previous cost estimation reviews. The main aim of this paper is to review existing software effort estimation methods
exhaustively by exploring estimation methods suitable for new software development methods.
This document provides an overview of software estimation techniques. It discusses why estimation is important, the general estimation process, and factors that impact accuracy such as requirements management and experience. The document also describes different estimation methods like expert judgment, analogy-based, top-down, and bottom-up. It provides examples of estimation tools like Function Point Analysis and COCOMO II for sizing and effort estimation.
The document discusses various topics related to managing software projects, including cost estimation and control, scope management, scheduling, and risk management. It provides information on processes for project management, defining activities and their relationships, estimating activity durations and resource needs, developing project schedules, and controlling changes to maintain the schedule. Key aspects covered are the project management process groups, developing a preliminary scope statement, integrated change control, monitoring project work, and managing conflicts that arise over the life of a project.
The document discusses various types of audit software and tools used by auditors. It describes generalized audit software (GAS) that can automate audit tasks and specialized audit software designed for specific audit objectives. It also covers integrated test facilities, snapshot techniques, data security procedures like backups, replication, and server clusters. The system development life cycle and auditor's role in reviewing each phase is explained.
This document discusses software cost estimation. It covers fundamentals of cost estimation including cost components. It discusses cost estimation during the software lifecycle and the general process. It then describes several methods for cost estimation - algorithmic/parametric models, expert judgment, top-down, bottom-up, analogy, and price to win. It stresses the importance of accurate cost estimation and concludes by listing references.
This document discusses software cost estimation. It introduces metrics for assessing software productivity and techniques for estimating software costs, including algorithmic modeling. A key technique is the COCOMO model, which relates software size to project costs based on historical data. The document also covers how to estimate project duration and staffing needs.
How Should We Estimate Agile Software Development Projects and What Data Do W...Glen Alleman
Estimating techniques for an acquisition program progresses from analogies to actual cost method as the program matures and more information is known. The analogy method is most appropriate early in the program life cycle when the system is not yet fully defined.
This document provides an overview of software engineering concepts covered in lecture notes. It discusses the software development life cycle (SDLC) which includes key stages like requirements gathering, design, coding, testing, integration and maintenance. The SDLC framework aims to develop software efficiently using a well-defined process. Software engineering principles like abstraction and decomposition are used to reduce complexity when developing large programs.
The document discusses software cost estimation techniques. It begins by introducing software productivity metrics like lines of code and function points. It then describes various estimation techniques, highlighting the COCOMO model. COCOMO is an algorithmic cost model that relates project size and factors to effort. It has different models for early design, reuse, and post-architecture. The document concludes by mentioning recent trends in software cost estimation like neural networks, analogy estimation, and Bayesian belief networks.
Lect-5: Work Breakdown Structure and Project Cost EstimationMubashir Ali
This document discusses work breakdown structures (WBS) and project cost estimation. It begins by defining a WBS as a method to divide complex projects into simpler, manageable tasks. This allows projects to be more easily planned, scheduled, and budgeted. The document then provides examples of how to outline a WBS and discusses how WBS helps managers assign responsibilities and monitor projects. It also discusses different cost estimation techniques like expert judgement, analogy, and algorithmic modeling. Overall, the document provides an overview of how WBS is used to define project scope and organize work, and different approaches to estimating project costs.
This document discusses software cost estimation and factors that influence productivity. It defines software cost estimation as predicting resources needed for development like effort, time and total cost. Cost components include hardware/software, travel/training, and effort costs like salaries and overheads. Productivity measures include lines of code, function points based on functionality, and object points. Factors like language, code verbosity, and system characteristics can impact productivity estimates.
This document discusses software cost estimation. It begins by distinguishing between effort, which is the number of hours of work required, and time, which is the duration from start to finish. It then describes factors that influence cost estimation, such as project type and size, and development team size. Finally, it outlines several techniques used for cost estimation, including algorithmic models, expert judgment, top-down estimation, and bottom-up estimation.
The document discusses software development lifecycles and strategies. It describes:
1) Common lifecycle activities like planning, development, testing and maintenance. Different models can be used depending on the product.
2) Solution strategies are developed to determine the nature of possible solutions and provide a framework for design and implementation. The best strategies are developed by trained groups using techniques like brainstorming.
3) The phased lifecycle model involves a series of defined activities with inputs, processes, and outputs at each phase. Resources are required to complete each defined phase.
The document discusses various aspects of planning and managing the software development process, including:
1) Developing a solution strategy and selecting a software life cycle model to provide a framework for the project.
2) Common software life cycle activities like planning, development, testing, and maintenance.
3) Using milestones, documents, and reviews to improve project visibility and management.
4) Organizing development tasks and teams using different structures like project, functional, and matrix formats.
This document discusses several techniques for estimating software costs: expert judgement, pricing to win, estimation by analogy, bottom-up, top-down, and algorithmic cost modeling. Expert judgement involves consulting experts and iterating until agreement. Pricing to win bases the estimate only on the customer's budget. Estimation by analogy compares a new project to similar past projects. Bottom-up and top-down respectively estimate from components or overall functionality. Algorithmic cost modeling uses mathematical equations based on historical data.
This document discusses rapid software development methods like agile development and extreme programming (XP). It explains that agile methods use iterative development with customer involvement to quickly deliver working software. XP in particular emphasizes practices like test-driven development, pair programming, and frequent small releases. The document also covers rapid application development tools and the use of prototypes to help define requirements before full system development.
SOFTWARE COST ESTIMATION USING FUZZY NUMBER AND PARTICLE SWARM OPTIMIZATIONIJCI JOURNAL
Software cost estimation is a process to calculate effort, time and cost of a project, and assist in better
decision making about the feasibility or viability of project. Accurate cost prediction is required to
effectively organize the project development tasks and to make economical and strategic planning, project
management. There are several known and unknown factors affect this process, so cost estimation is a very
difficult process. Software size is a very important factor that impacts the process of cost estimation.
Accuracy of cost estimation is directly proportional to the accuracy of the size estimation.
Failure of Software projects has always been an important area of focus for the Software Industry.
Implementation phase is not the only phase for Software projects to fail, instead planning and estimation
steps are the most crucial ones, which lead to their failure. More than 50% of the total projects fail which
go beyond the estimated time and cost. The Standish group‘s CHAOS reports failure rate of 70% for the
software projects. This paper presents the existing algorithms for software estimation and the relevant
concepts of Fuzzy Theory and PSO. Also explains the proposed algorithm with experimental results.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
This document discusses various techniques for estimating software costs:
1. Expert judgment relies on experienced people's assessments but can be unreliable due to biases. The Delphi technique improves expert judgment by anonymously aggregating estimates over multiple rounds.
2. Work breakdown structures break projects down into components to estimate costs bottom-up. The COCOMO model also estimates bottom-up using algorithmic formulas adjusted by multipliers for attributes.
3. COCOMO is demonstrated through an example estimating effort of 191 person-months and a 13 month schedule for a 30,000 line embedded software project with high reliability requirements.
This document discusses software cost estimation. It describes the objectives of software cost estimation and the fundamental questions that must be answered. It explains different techniques for software cost estimation including algorithmic cost modeling, expert judgement, and estimation by analogy. A key part of the document focuses on the COCOMO model, including the different levels of COCOMO 2 for estimation. It also discusses using cost estimation for project planning and management.
A Review of Agile Software Effort Estimation MethodsEditor IJCATR
Software cost estimation is an essential aspect of software project management and therefore the success or failure of a software
project depends on accuracy in estimating effort, time and cost. Software cost estimation is a scientific activity that requires knowledge of a
number of relevant attributes that will determine which estimation method to use in a given situation. Over the years various studies were done
to evaluate software effort estimation methods however due to introduction of new software development methods, the reviews have not
captured new software development methods. Agile software development method is one of the recent popular methods that were not taken
into account in previous cost estimation reviews. The main aim of this paper is to review existing software effort estimation methods
exhaustively by exploring estimation methods suitable for new software development methods.
This document provides an overview of software estimation techniques. It discusses why estimation is important, the general estimation process, and factors that impact accuracy such as requirements management and experience. The document also describes different estimation methods like expert judgment, analogy-based, top-down, and bottom-up. It provides examples of estimation tools like Function Point Analysis and COCOMO II for sizing and effort estimation.
The document discusses various topics related to managing software projects, including cost estimation and control, scope management, scheduling, and risk management. It provides information on processes for project management, defining activities and their relationships, estimating activity durations and resource needs, developing project schedules, and controlling changes to maintain the schedule. Key aspects covered are the project management process groups, developing a preliminary scope statement, integrated change control, monitoring project work, and managing conflicts that arise over the life of a project.
The document discusses various types of audit software and tools used by auditors. It describes generalized audit software (GAS) that can automate audit tasks and specialized audit software designed for specific audit objectives. It also covers integrated test facilities, snapshot techniques, data security procedures like backups, replication, and server clusters. The system development life cycle and auditor's role in reviewing each phase is explained.
This document discusses software cost estimation. It covers fundamentals of cost estimation including cost components. It discusses cost estimation during the software lifecycle and the general process. It then describes several methods for cost estimation - algorithmic/parametric models, expert judgment, top-down, bottom-up, analogy, and price to win. It stresses the importance of accurate cost estimation and concludes by listing references.
This document discusses software cost estimation. It introduces metrics for assessing software productivity and techniques for estimating software costs, including algorithmic modeling. A key technique is the COCOMO model, which relates software size to project costs based on historical data. The document also covers how to estimate project duration and staffing needs.
How Should We Estimate Agile Software Development Projects and What Data Do W...Glen Alleman
Estimating techniques for an acquisition program progresses from analogies to actual cost method as the program matures and more information is known. The analogy method is most appropriate early in the program life cycle when the system is not yet fully defined.
This document provides an overview of software engineering concepts covered in lecture notes. It discusses the software development life cycle (SDLC) which includes key stages like requirements gathering, design, coding, testing, integration and maintenance. The SDLC framework aims to develop software efficiently using a well-defined process. Software engineering principles like abstraction and decomposition are used to reduce complexity when developing large programs.
The document discusses software cost estimation techniques. It begins by introducing software productivity metrics like lines of code and function points. It then describes various estimation techniques, highlighting the COCOMO model. COCOMO is an algorithmic cost model that relates project size and factors to effort. It has different models for early design, reuse, and post-architecture. The document concludes by mentioning recent trends in software cost estimation like neural networks, analogy estimation, and Bayesian belief networks.
Lect-5: Work Breakdown Structure and Project Cost EstimationMubashir Ali
This document discusses work breakdown structures (WBS) and project cost estimation. It begins by defining a WBS as a method to divide complex projects into simpler, manageable tasks. This allows projects to be more easily planned, scheduled, and budgeted. The document then provides examples of how to outline a WBS and discusses how WBS helps managers assign responsibilities and monitor projects. It also discusses different cost estimation techniques like expert judgement, analogy, and algorithmic modeling. Overall, the document provides an overview of how WBS is used to define project scope and organize work, and different approaches to estimating project costs.
This document discusses software cost estimation and factors that influence productivity. It defines software cost estimation as predicting resources needed for development like effort, time and total cost. Cost components include hardware/software, travel/training, and effort costs like salaries and overheads. Productivity measures include lines of code, function points based on functionality, and object points. Factors like language, code verbosity, and system characteristics can impact productivity estimates.
This document discusses software cost estimation. It begins by distinguishing between effort, which is the number of hours of work required, and time, which is the duration from start to finish. It then describes factors that influence cost estimation, such as project type and size, and development team size. Finally, it outlines several techniques used for cost estimation, including algorithmic models, expert judgment, top-down estimation, and bottom-up estimation.
The document discusses software development lifecycles and strategies. It describes:
1) Common lifecycle activities like planning, development, testing and maintenance. Different models can be used depending on the product.
2) Solution strategies are developed to determine the nature of possible solutions and provide a framework for design and implementation. The best strategies are developed by trained groups using techniques like brainstorming.
3) The phased lifecycle model involves a series of defined activities with inputs, processes, and outputs at each phase. Resources are required to complete each defined phase.
The document discusses various aspects of planning and managing the software development process, including:
1) Developing a solution strategy and selecting a software life cycle model to provide a framework for the project.
2) Common software life cycle activities like planning, development, testing, and maintenance.
3) Using milestones, documents, and reviews to improve project visibility and management.
4) Organizing development tasks and teams using different structures like project, functional, and matrix formats.
This document discusses several techniques for estimating software costs: expert judgement, pricing to win, estimation by analogy, bottom-up, top-down, and algorithmic cost modeling. Expert judgement involves consulting experts and iterating until agreement. Pricing to win bases the estimate only on the customer's budget. Estimation by analogy compares a new project to similar past projects. Bottom-up and top-down respectively estimate from components or overall functionality. Algorithmic cost modeling uses mathematical equations based on historical data.
This document discusses rapid software development methods like agile development and extreme programming (XP). It explains that agile methods use iterative development with customer involvement to quickly deliver working software. XP in particular emphasizes practices like test-driven development, pair programming, and frequent small releases. The document also covers rapid application development tools and the use of prototypes to help define requirements before full system development.
SOFTWARE COST ESTIMATION USING FUZZY NUMBER AND PARTICLE SWARM OPTIMIZATIONIJCI JOURNAL
Software cost estimation is a process to calculate effort, time and cost of a project, and assist in better
decision making about the feasibility or viability of project. Accurate cost prediction is required to
effectively organize the project development tasks and to make economical and strategic planning, project
management. There are several known and unknown factors affect this process, so cost estimation is a very
difficult process. Software size is a very important factor that impacts the process of cost estimation.
Accuracy of cost estimation is directly proportional to the accuracy of the size estimation.
Failure of Software projects has always been an important area of focus for the Software Industry.
Implementation phase is not the only phase for Software projects to fail, instead planning and estimation
steps are the most crucial ones, which lead to their failure. More than 50% of the total projects fail which
go beyond the estimated time and cost. The Standish group‘s CHAOS reports failure rate of 70% for the
software projects. This paper presents the existing algorithms for software estimation and the relevant
concepts of Fuzzy Theory and PSO. Also explains the proposed algorithm with experimental results.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Communicating effectively and consistently with students can help them feel at ease during their learning experience and provide the instructor with a communication trail to track the course's progress. This workshop will take you through constructing an engaging course container to facilitate effective communication.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
2. Software Cost Estimation
Estimating the cost of a software is one of the difficult task in software engineering.
During the planning phase, it is very difficult to make an accurate estimation of the
software as there are a large number of unknown factors at that time.
In order to overcome the problem of cost overrun, some organizations use a series of
cost estimates.
A preliminary estimate is prepared during the planning phase and presented at the project
feasibility review.
An improved estimate is prepared and presented at the software requirements, review
and the final estimate is presented at the preliminary design review.
Each estimate is a refinement of the previous one and is based on the additional
information gained as a result of additional work activities.
This allows the customer to choose a cost effective solution from a range of possible
solutions.
3. Software Cost Estimation
Major factors that influence software cost.
Programmer ability
Product size
Available time
Required reliability
Level of technology.
4. Software Cost Estimation
Programmer Ability
The individual attributes of project and their familiarity with
the application area is an important software cost factor.
On very large products, the differences in individual
programmer ability will tend to average out, but on projects
utilizing five or fewer programmers, individual differences in
ability can be significant.
5. Software Cost Estimation
Project Complexity
Generally, there are three categories of software products:
application programs, utility programs and system level
programs.
Application programs which include data processing and
scientific programs are developed in the environment
provided by the language compiler.
Utility programs such as compilers, linkage editors and
inventory systems are written to provide user processing
environments, Utility programs make sophisticated use of
6. Software Cost Estimation
Brooks states that utility programs are three time as difficult
to write as application programs and that systems
programs are three times as difficult to write as utility
programs.
His levels of product complexity are thus 1-3-9 for
applications utility systems programs
8. Software Cost Estimation
Product size
Obviously a large software product is more expensive to develop
than a small one.
the rate of increase in required effort grows with the number of
source instructions at an exponential rate slightly greater than 1.
Available time
Total project effort is sensitive to the calendar time available for project
completion.
the total effort required .to complete the project decreases with
the increase in the development time for that project, But that is
not true. If the development time for the project is expanded
beyond some limit it will increase the total effort required to
develop the software project.
9. Software Cost Estimation
Required Level of Reliability
Software reliability can be defined as the probability that a
program will perform a required function under stated
conditions for a stated period of time.
Reliability can be expressed in terms of accuracy,
robustness, completeness and consistency of the source
code.
To ensure higher reliability, there is a cost associated with the increased
level of analysis, design, implementation and verification and validation
10. Software Cost Estimation
Required Level of Reliability
Software reliability can be defined as the probability that a program will perform
a required function under stated conditions for a stated period of time.
Reliability can be expressed in terms of accuracy, robustness, completeness
and consistency of the source code.
To ensure higher reliability, there is a cost associated with the increased level of
analysis, design, implementation and verification and validation
In a software project, some product failure may cause little inconvenience to the
user, while failure of other products may lead to high financial loss.
So the required level of reliability should be established during the planning
phase by considering the cost of software failures.
11. Software Cost Estimation
Level of Technology
The level of technology in a software development project is
reflected by the programing language, the abstract machine
(hardware and software), the programming practices the
software tools used.
As the program statements written in high level language instead
of assembly language increases programmer productivity by a
factor of 5 to 10.
Modern languages improve programmer productivity and software
reliability.
These features include strong type-checking, data abstraction,
separate compilation, exception handling, interrupt handling and
concurrency mechanisms.
12. Software cost estimation
techniques
Within most organizations, software cost estimates are
based on past performance.
The cost and productivity data must be collected on current
project in order to estimate the future ones.
Cost estimates can be made either top-down or bottom-up.
Top-down estimation first focuses on system-level costs,
such as the computing resources and personnel required to
develop the system, as well as the costs of configuration
and management, quality assurance, system integration,
training and publications.
13. Software cost estimation
techniques
The two top-down cost estimation technique which we are going to discuss..
1. Expert Judgment
2. Delphi cost Estimation
Bottom-up cost estimation first estimates the cost to develop each module or
subsystem.
Those cost are combined to arrive at an overall estimate, Work Breakdown
structures and Algorithmic cost estimators are the bottom-up cost estimators.
Top-down estimation has the advantage of focusing on system level costs, but
may overlook various technical factors in some of the modules to the
developed.
Bottom-up estimation emphasizes the costs associated with developing
individual system components, but may fail to account for system-level costs,
such as configuration management and quality control.
14. Software cost estimation
techniques
Expert Judgment
Expert judgment relies on the experience, background and business sense of
one or more key people in the organization.
An expert on identifying the similarity between the new project and project they
have developed in the recent past, estimates the cost of the new project in the
following manner.
If the new system has similar functions as that of the old one and also has
some more functions, then it increase the time and cost estimates of the new
project.
Based on the cost and schedule of the previous project and analyzing the new
project, the expert estimates the cost and schedule of the new project.
15. Software cost estimation
techniques
Delphi cost estimation
1. A co-ordinator provides each estimator with the System Definition document
and a form for recording a cost estimate,
2. Estimators study the definition and complete their estimates anonymously.
They may ask questions to the co-ordinator, but they do not discuss their
estimates with one another.
3. The co-ordinator prepares and distributes a summary of the estimators
responses, and include any unusual rationales noted by the estimators,
4. Estimators complete another estimate, again anonymously, using the results
from the previous estimate. Estimators whose estimates differ sharply from the
group may be asked, anonymously, to provide justification for their estimates.
5. The process is iterated for as many rounds as required, No group discussion
is allowed during the entire process,
16. Software cost estimation
techniques
The following approach is a variation on the standard Delphi technique that
increases communication while preserving anonymity,.
1. The co-ordinator provides each estimator with a System Definition and an
estimation form.
2. The estimators study the definition and the co-ordinator calls a group meeting so
that estimators can discuss estimation issues with the co-ordinator and one-another,
3. Estimators complete their estimates anonymously.
4. The co-ordinator prepares a summary of the estimates, but does not record/any
rationales.
5. The co-ordinator calls a group meeting to focus on issues where the estimates
vary widely.
6. Estimators complete another estimate, again anonymously. The process is
iterated for as many rounds as necessary.
17. Software cost estimation
techniques
Work breakdown structures
Expert judgment and group consensus are top-down estimation techniques.
The work breakdown structure is a bottom-up estimation tool.
A work breakdown structure is a hierarchical chart that accounts for the
individual parts of the system.
A WBS chart can indicate either product hierarchy or process hierarchy.
In product hierarchy, product components are identified and the manner in
which the components are inter-connected are specified.
A WBS chart of process hierarchy identifies the work activities and the
relationships among those activities.
19. Software cost estimation
techniques
Using the WBS technique, cost are estimated by assigning costs to each
individual component in the chart and summing the costs.
The main advantage of using WBS cost estimation technique is that it makes all
the process and product factors that are included in the cost estimation explicit
to all.
Expert judgment, group consensus and WBS are most widely used cost
estimation technique.
Many organizations use all three approaches and iterate on the estimates until
differences have been resolved.
20. Software cost estimation
techniques
Algorithmic cost models
Algorithmic cost models are bottom-up cost estimators.
Algorithmic cost estimators compute the estimated cost of a software system as
the sum of the costs of the modules and subsystems that comprise the system.
The Constructive Cost Model (CoCoMo) is an algorithmic cost model described
in BOE81 CoCoMo is briefly summarized here.
CoCoMo to provide nominal estimates of programmer-months and
development schedule for a program, unit, based on the estimated number of
Delivered Source Instructions (DSI) in the unit Effort multipliers are then used to
adjust the estimate for the product attributes, computer attributes personnel
attributes and project attributes.
22. Software cost estimation
techniques
Staffing-Level Estimation
The number of personnel required throughout a software development project
is not constant.
The number of personnel required during each phase of the project differs from
one project to the other.
Typically, planning and analysis are performed by a small group of people,
architectural design by a larger group and detailed design by a still larger
number of people.
The early phase of maintenance may require numerous personnel, but the
number should decrease in a short time.
If there is no major enhancement or adaptation, then the number of personnel
for maintenance should remain small
23. Software cost estimation
techniques
Estimating software maintenance cost
Software maintenance typically requires 40 to 60 percent and in some cases as
much as 90 percent of the total life - cycle effort devoted to software product.
Maintenance activities include
1. Enhancements to the product.
2. Adapting the product to new processing environments.
3. Correcting problems.
During the planning phase of a software project thq number of maintenance
programmers needed are estimated and facilities required for maintenance are
specified.
the typical level of effort devoted to software maintenance was around 50
percent of total life-cycle effort, and that the distribution of maintenance
activities was 51.3 percent for enhancement.
25. Software cost estimation
techniques
An estimate of the number of full-time software personnel needed for
software maintenance can be determined by dividing the estimated
number of source instructions to be maintained by the estimated
number of instructions that can be maintained by a maintenance
programmer.
if a maintenance programmer can maintain 32 KDSI, then two
maintenance programmers are required to maintain 64KDSI.
Heavy emphasis on reliability and the use of modern programming practices
during development may reduce the amount of effort required for maintenance,
while low emphasis on reliability and modern practices during development may
increase the difficulty of maintenance.
26. Software Requirements
There are two sub phases in the analysis phase. They are planning and
software requirements definition.
The outcome of planning are the system definition, the project Plan and the
preliminary User's Manual.
They are primarily concerned with the user and the external view of the software
product.
The outcome of the software requirements definition activity is recorded in the
Software requirements Specification.
The technical requirements for the software product is specified completely and
concisely in an unambiguous manner.
Formal notations are used as appropriate.
Depending on the size and complexity of the product, the size of the software requirements
27. Software Requirements
The Software Requirements Specification
Section 1: Product overview and summary
Section 2: Development, Operating and Maintenance Environments
Section 3: External Interfaces and data flow
Section 4: Functional Requirements
Section 5: Performance Requirements
Section 6: Exception Handling
Section 7: Early subsets and Implementation Priorities
Section 8: Foreseeable Modifications and Enhancements
Section 9: Acceptance criteria
Section 10: Design Hints and Guidelines
Section 11: Cross-Reference Index
Section 12: Glossary of terms
28. Software Requirements
Sections 1 and 2 of the requirements document present an overview of product
features and summarize the processing environments for development operation
and maintenance of the product.
This information is an elaboration in the software product characteristics contained
in the system Definition and the preliminary users manual.
External Interfaces such as user displays and report formats, a summary of user
commands and report options, data flow diagrams and data dictionary are included
in section-3. High level data flow diagrams and a data dictionary are derived.
Data flow diagrams specify data sources and data sinks, data stores,
transformations to be performed on the data, and the flow of data between sources,
sinks, transformations and stores.
A data store is a conceptual data structure in the sense that physical
implementation details are suppressed; only the logical characteristics of data are
emphasized in a data flow diagrams.
29. Software Requirements
Data flow diagrams can be depicted informally, or by using special notation
Data sources and data sinks are depicted by shaded rectangles transformation
by ordinary rectangles and data stores by open ended rectangles.
The arcs in a data flow diagram specify data flow.
They are labelled with the names of data items.
The characteristics of these data items are specified in the data dictionary.
Data flow diagrams are not concerned with decision structure or algorithmic
details.
Data flow diagrams can be used at any level of detail.
They can be hierarchically decomposed.
The inner workings of the functional nodes are specified using additional data
32. Software Requirements
Formal Specification Techniques
Formal notations are used to specify the functional characteristics of a software
product in the requirements document.
The requirements document will be concise and the functional characteristics
can be expressed in an unambiguous manner by using the formal notations.
These notations support formal reasoning about the functional specifications
and they provide a basis for verification of the resulting software product.
Formal notations are not appropriate in all situations or for all types of systems.
To specify the functional characteristics of software both relational and state
oriented notations are used.
Relational notations are based on the concepts of entities and attributes.
33. Software Requirements
Entities are named elements in a system, the names are chosen to denote the
nature of the elements (eg., stack queue).
Attributes are specified by applying functions and relations to the names
entities.
Attributes specify permitted operations on entities, relationships among entities
and data flow between entities.
The state of system is the information required to summarize the status of
system entities at any particular point in time.
Given the current state and the current estimate, the next state can be
determined. .
The execution history by which the current estimate, the next state, it is only
dependent on the current state and current stimuli.
34. Software Requirements
State oriented notations include decision tables, event tables, transition tables,
finite-state mechanisms and Petri Nets.
These notations are formal in the sense that they are concise and
unambiguous.
Relational Notations
Implicit equations: Implicit equations specify the properties of a solution without
stating a solution method.
Recurrence relations: A recurrence relation consists of an initial part called the
basic and one or more recursive parts. Recurrence relations are easily
transformed into recursive programs. That doesn't mean every recursive
specification should;d be implemented as a recursive programs.
Algebraic Axioms: Mathematical systems are defined by axioms. The axioms
specify fundamental properties of a system and provide a basis for deriving
35. Software Requirements
The axiomatic approach can be used to specify functional properties of
software systems
The intention is to specify the fundamental nature of the system by stating a few
basic properties.
This approach can be used to specify abstract data types. The data type is
characterized as a set of objects and a set of permissible operations on those
objects.
Abstraction allows one to emphasize the important characteristics of a system
while suppressing unimportant details.
Thus, data abstraction emphasizes functional properties and suppresses
representation details.
Depending on the axioms provided, only some of many possible functional
36. Software Requirements
The Specification of an abstract data type using algebraic axioms involves
defining the syntax of the operations and specifying axiomatic relationships
among the operations.
The syntactic definition specifies names, domains and ranges of operation to be
performed on the data objects and the axioms specify interactions among
operations.
An example of axiomatic specification of the last-in-first-out (LIFO) property of
stack objects
37. Software Requirements
The Specification of an abstract data type using algebraic axioms involves
defining the syntax of the operations and specifying axiomatic relationships
among the operations.
The syntactic definition specifies names, domains and ranges of operation to be
performed on the data objects and the axioms specify interactions among
operations.
An example of axiomatic specification of the last-in-first-out (LIFO) property of
stack objects
39. Software Requirements
1. A new stack is empty.
2. A stack is not empty immediately after pushing an item onto it,
3. Attempting to pop a new stack results in an errors.
4. There is no top item on a new stack.
5. , Pushing an item onto a stack unchanged.
6. Pushing an item onto a stack and immediately requesting the top item
returns the items just pushed onto the stack.
40. Languages and Processors for
requirements specification
A number of special-purpose languages and processors have been developed
to permit concise statement and automated analysis of requirements
specifications for software.
Some specification languages are graphical in nature.
While others are textual, all are relational in nature some specification
languages are manually applied and others have automated processors.
PSL/PSA
The Problem Statement Language (PSL) was developed at the University of
Michigan.
The Problem Statement Analyser (PSA) is the PSL processor.
PSL is based on a general model of systems.
41. Languages and Processors for
requirements specification
Objects may be inter-connected; the connections are called relationships.
The general model is specialized to information systems by allowing only a limited
number of predefined objects, properties and relationships.
In PSL, system descriptions can be divided into eight major aspects:
• 1. System input/output flow.
• 2. System structure
• 3. Data structure
• 4. Date derivation
• 5. System size and volume
• 6. System dynamics
• 7. System properties
• 8. Project management
42. Languages and Processors for
requirements specification
The system input/output flow aspects deals with the interaction between a system and its
environment.
System structure is concerned with the hierarchies among objects in a system.
The data structure aspect includes all the relationships that exist among data used and
/or manipulated by a system as seen by the users of the system.
Data derivation describes data relationships that are internal to a system.
The system size and volume aspects is concerned with the size of the system and those
factors that influence the volume of processing required.
The Problem Statement Analyser (PSA) is an automated analyser for processing
requirements stated in PSL.
43. Languages and Processors for
requirements specification
PSA operates on a data base of information collected from a PSL description the PSA
system can provide reports in four categories
1. Data-base modification reports
2. References reports
3. Summary reports
4. Analysis reports
Data-base modification reports list changes that have been made since the last report
together with diagnostic and warming messages, these reports provide a record of
changes for error correction and recovery.
Reference reports include.
a. Name list report
b. Formatted problem statement Report and
c. Dictionary Report
44. Languages and Processors for
requirements specification
Name List Report lists all the objects in the database with types and dates of last change.
The Formatted problem Statement Report shows properties and relationships for
particular object.
The dictionary report provides a data dictionary.