This document provides an introduction to Function Point Analysis (FPA), a method for measuring the size and complexity of software from the user's perspective. FPA focuses on five functional components - internal logical files, external interface files, external inputs, external outputs, and external inquiries. It also considers two adjustment factors - functional complexity and a value adjustment factor. FPA can be used to estimate projects, measure productivity, manage changing requirements, and communicate functional needs to users. The document outlines the benefits of FPA and provides an example of how to conduct an FPA using a structured workshop approach.
This document presents a framework for estimating the effort required for Service Oriented Architecture (SOA) and Enterprise Service Bus (ESB) projects. It decomposes SOA/ESB projects into business factors and technical factors. Business factors include processes, services, and integration. Technical factors include non-functional requirements. It assigns complexity weights and degrees of influence to these factors. A derived formula is presented to calculate the adjusted size of the project based on these factors, which can then be used to estimate effort. Sample data from past projects is also shown.
The document provides an introduction to computer organization and architecture. It defines computer architecture as the attributes visible to the programmer, such as the instruction set, while computer organization refers to how those architectural specifications are implemented internally. The basic functions of a computer are described as data processing, storage, movement, and control. A computer's main components are the central processing unit, main memory, and input/output. The document outlines the fetch-execute cycle of instruction processing and how interrupts can alter the control flow. It also discusses trends driving the need for performance improvements like faster memory.
This document discusses considerations for applying FPGAs (field programmable gate arrays) in industrial applications. It presents a systematic approach for evaluating hardware platforms that involves identifying relevant hardware attributes and features. The document then evaluates several key hardware attributes of FPGAs, including their performance and functional range enabled by dedicated resources like multipliers and memory blocks. It also discusses FPGAs' marketability in terms of costs, time to market, and ability to be reprogrammed after production.
Ec6703 embedded and real time systems(1)viswnathan
This document contains a question bank for the subject EC6703 - Embedded and Real Time Systems. It includes questions divided into two units:
Unit I focuses on introduction to embedded computing, ARM processors, and real time systems. It includes 20 short answer and long answer questions related to these topics.
Unit II focuses on embedded computing platform design. It includes 20 more short answer and long answer questions related to topics like CPU buses, memory systems, programming models, debugging tools, and performance optimization.
The document provides a detailed question bank to test students' understanding of key concepts from the course on embedded and real time systems.
Managing a Microsoft Windows Server 2003 Environment discusses monitoring server performance using built-in tools like Task Manager, Event Viewer, and the Performance console. Task Manager provides snapshots of CPU, memory, and network usage. Event Viewer views logs to identify problems. The Performance console's System Monitor and Performance Logs and Alerts tools gather detailed performance data and generate alerts. The chapter also covers optimizing performance by configuring services.
The document describes the design of an air traffic control (ATC) system using the Unified Modeling Language (UML). It aims to model the departure process of air traffic control through UML diagrams to address issues with existing ATC systems like lack of a well-defined human/software interface, need for high maintenance, and outdated design/technology. The key aspects covered include:
1) Developing a formal UML activity diagram to model the departure process with clearly defined semantics and states compared to an informal diagram.
2) Proposing the use of additional UML diagrams like use case, class, and sequence diagrams to further model the ATC system and address limitations of existing approaches.
3) Argu
An Algorithm Based Simulation Modeling For Control of Production SystemsIJMER
This document describes an algorithm-based simulation approach for modeling and controlling flexible production systems. The approach models both the physical production system and the control system to evaluate their integrated performance. Key features include:
1) The approach integrates control system design into the physical simulation to evaluate their combined impact.
2) The algorithm-based design is extensible and allows modeling of different control programs and production system designs.
3) Finite automata formalism provides a mathematical foundation for logical and quantitative analysis of the system.
4) The framework facilitates robust controller models that can resolve issues like deadlocks and accommodate failures.
5) Analysts can evaluate how different control programs and production system designs impact
This document defines the technical specifications for an inventory management system. It outlines the workflow stages a vehicle passes through, including acquiring the vehicle, decoding the VIN, selecting for auction, and more. It also describes the database tables used to manage workflow stages, vehicle sources, and exceptions. Procedures and classes are defined to support moving vehicles through each stage and handling exceptions.
This document presents a framework for estimating the effort required for Service Oriented Architecture (SOA) and Enterprise Service Bus (ESB) projects. It decomposes SOA/ESB projects into business factors and technical factors. Business factors include processes, services, and integration. Technical factors include non-functional requirements. It assigns complexity weights and degrees of influence to these factors. A derived formula is presented to calculate the adjusted size of the project based on these factors, which can then be used to estimate effort. Sample data from past projects is also shown.
The document provides an introduction to computer organization and architecture. It defines computer architecture as the attributes visible to the programmer, such as the instruction set, while computer organization refers to how those architectural specifications are implemented internally. The basic functions of a computer are described as data processing, storage, movement, and control. A computer's main components are the central processing unit, main memory, and input/output. The document outlines the fetch-execute cycle of instruction processing and how interrupts can alter the control flow. It also discusses trends driving the need for performance improvements like faster memory.
This document discusses considerations for applying FPGAs (field programmable gate arrays) in industrial applications. It presents a systematic approach for evaluating hardware platforms that involves identifying relevant hardware attributes and features. The document then evaluates several key hardware attributes of FPGAs, including their performance and functional range enabled by dedicated resources like multipliers and memory blocks. It also discusses FPGAs' marketability in terms of costs, time to market, and ability to be reprogrammed after production.
Ec6703 embedded and real time systems(1)viswnathan
This document contains a question bank for the subject EC6703 - Embedded and Real Time Systems. It includes questions divided into two units:
Unit I focuses on introduction to embedded computing, ARM processors, and real time systems. It includes 20 short answer and long answer questions related to these topics.
Unit II focuses on embedded computing platform design. It includes 20 more short answer and long answer questions related to topics like CPU buses, memory systems, programming models, debugging tools, and performance optimization.
The document provides a detailed question bank to test students' understanding of key concepts from the course on embedded and real time systems.
Managing a Microsoft Windows Server 2003 Environment discusses monitoring server performance using built-in tools like Task Manager, Event Viewer, and the Performance console. Task Manager provides snapshots of CPU, memory, and network usage. Event Viewer views logs to identify problems. The Performance console's System Monitor and Performance Logs and Alerts tools gather detailed performance data and generate alerts. The chapter also covers optimizing performance by configuring services.
The document describes the design of an air traffic control (ATC) system using the Unified Modeling Language (UML). It aims to model the departure process of air traffic control through UML diagrams to address issues with existing ATC systems like lack of a well-defined human/software interface, need for high maintenance, and outdated design/technology. The key aspects covered include:
1) Developing a formal UML activity diagram to model the departure process with clearly defined semantics and states compared to an informal diagram.
2) Proposing the use of additional UML diagrams like use case, class, and sequence diagrams to further model the ATC system and address limitations of existing approaches.
3) Argu
An Algorithm Based Simulation Modeling For Control of Production SystemsIJMER
This document describes an algorithm-based simulation approach for modeling and controlling flexible production systems. The approach models both the physical production system and the control system to evaluate their integrated performance. Key features include:
1) The approach integrates control system design into the physical simulation to evaluate their combined impact.
2) The algorithm-based design is extensible and allows modeling of different control programs and production system designs.
3) Finite automata formalism provides a mathematical foundation for logical and quantitative analysis of the system.
4) The framework facilitates robust controller models that can resolve issues like deadlocks and accommodate failures.
5) Analysts can evaluate how different control programs and production system designs impact
This document defines the technical specifications for an inventory management system. It outlines the workflow stages a vehicle passes through, including acquiring the vehicle, decoding the VIN, selecting for auction, and more. It also describes the database tables used to manage workflow stages, vehicle sources, and exceptions. Procedures and classes are defined to support moving vehicles through each stage and handling exceptions.
Function point analysis is a method of estimating the size of a software or system by counting the number of inputs, outputs, inquiries, internal logical files and external interface files. It was introduced in 1979 as an alternative to simply counting lines of code. Function point analysis measures the software based on end user requirements rather than implementation details. It provides a consistent way to measure software across different projects, organizations and programming languages. The document provides an overview of function point analysis including its history, why it is needed, how it works and how it is used to estimate sizes of major software applications.
Function point analysis is a method of estimating the size of a software application based on the number and complexity of inputs, outputs, inquiries, internal logical files, and external interface files. The document outlines the process for counting function points, which involves identifying the different types of components, determining the unadjusted function point count, assessing value adjustment factors, and calculating the adjusted function point count. Function point analysis provides a standardized, technology-independent way to measure and estimate software size that allows for more accurate comparisons of projects.
The document defines various elements of function point analysis including:
1. File Type References (FTRs), Internal Logical Files (ILFs), External Interface Files (EIFs), External Input (EI), External Output (EO), External Inquiry (EQ), and General System Characteristics (GSCs) which are the main components measured in a function point analysis.
2. It provides descriptions of each component - FTRs refer to files referenced by transactions, ILFs and EIFs are files stored internally or externally, EI involves data entering the system, EO is data exiting, and EQ retrieves data without updates.
3. GSCs consider other factors like architecture and performance that
This document provides an overview of function point estimation techniques. It discusses counting practices, vocabulary, components like external inputs, outputs, inquiries and files. It covers the rating and weighting of different components. The document also discusses techniques like use case point estimation, ESB/SOA estimation and COSMIC functional size measurement. Key aspects covered are decomposing systems, defining business and technical factors, deriving size formulas and nominal values. Productivity relationships and various points to ponder regarding estimation techniques are also presented.
There are three main elements used to determine estimates for black box testing using Test Point Analysis (TPA): size, test strategy, and productivity. Size is mainly defined by the number of function points, but complexity, interfacing, and uniformity must also be considered. Test strategy depends on requirement importance and user usage/importance ratings. Productivity is affected by many factors and depends on the team. Together these three elements are used to calculate the estimated effort for black box testing on a project.
This document summarizes an approach to estimating software size using function point analysis. It involves calculating unadjusted function points based on complexity ratings of internal logical files, external interface files, external inputs, external outputs, and external inquiries. A value adjustment factor is then calculated based on ratings of 14 general system characteristics. The unadjusted function point value is multiplied by the value adjustment factor to obtain the final function point count, which provides an estimate of the software size independent of implementation technologies. The document provides an example calculation where unadjusted function points are determined to be 194, the value adjustment factor is 0.81, resulting in a final function point count of 157.
This document discusses function point analysis, which is a method for estimating the size of application software based on its functionality from the user's perspective. It involves identifying different types of functions - external inputs, outputs, inquiries, internal logical files, and external interface files. Each function is classified as simple, average, or complex and assigned a weight. These weights are summed to calculate the unadjusted function point count. A value adjustment factor is also calculated based on characteristics of the system to adjust the unadjusted function point count. The final function point count is obtained by multiplying the unadjusted function point count by the value adjustment factor. As an example, the document calculates the unadjusted function point count and value adjustment factor for a sample project to
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
What is Quality ||
Software Quality Metrics ||
Types of Software Quality Metrics ||
Three groups of Software Quality Metrics ||
Customer Satisfaction Metrics ||
Tools used for Quality Metrics/Measurements ||
PERT and CPM ||
A document discusses various software estimation techniques including function point analysis, COCOMO models, and cost drivers. Function point analysis breaks a system into functional components like inputs, outputs, inquiries and files that are assigned complexity weights and counts. COCOMO models like COCOMO I and COCOMO II estimate effort using size of the project and cost multipliers related to attributes of the product, computer system, personnel and project. Cost drivers help assess these multipliers to refine effort estimates.
This document discusses Function Point Analysis, which is a technique for measuring the size of software systems. It breaks systems into smaller components like external inputs, outputs, inquiries, internal logical files, and external interface files. Counting these components provides a total Function Point that can be used to measure a system's size, track scope changes, and compare productivity across tools and languages. The benefits are that Function Points allow for accurate sizing, can be counted consistently, and help with estimating and communicating a system's size to stakeholders.
The document discusses software estimation techniques. It describes estimating the size and cost of software projects using methods like lines of code counting, function point counting, and work breakdown structures. It discusses best practices for software estimation like explicitly defining project scope, using historical metrics, employing multiple techniques or estimators, and accounting for inherent uncertainty. The document then explains techniques like function point analysis in detail, including how to classify components, assign complexity weights, and compute the final function point count and estimation.
1. The document discusses software project planning and estimation techniques. It covers size estimation, cost estimation, development time estimation, and project scheduling.
2. The document discusses different techniques for estimating the size of a software project, including lines of code counting and function point analysis. It provides examples of how to apply function point analysis to estimate the size of a project.
3. Function point analysis breaks a project into different functional components or units and assigns weighted scores to each unit based on complexity. The counts are then adjusted based on other project factors to determine the total function points of the project, which can then estimate development effort.
This document discusses software metrics and function point analysis. It provides information on different types of software metrics including size-oriented, function-oriented, and attribute metrics. It then focuses on explaining function point analysis in detail. Function point analysis measures software size based on user requirements rather than lines of code. It involves counting various functional components and adjusting for complexity. The document provides steps to calculate unadjusted and adjusted function points for different examples. Overall, the document provides a comprehensive overview of software metrics with a focus on function point analysis methodology.
This document describes a project that implements graphical password authentication to access applications remotely. It uses images retrieved from a database for the login process. The user must select the exact images to gain access. It also allows remote control functions like shutdown and file permissions checks. The project has modules for authentication, remote handling, file searching, privileges management, and process management. It was developed using technologies like JDK, Java Swing, Oracle, and RMI. The purpose is to provide a more secure authentication method compared to text passwords.
The document discusses an integrated ERP system with a web portal. It proposes using ETL tools to extract data from legacy ERP systems and load it into a centralized data warehouse ("one-version data store"). Data marts are then extracted from the data warehouse to improve query response times. A web portal is built on top of the data marts to provide customized, personalized access and collaboration for managers to support decision making using business intelligence tools. The model aims to address challenges of legacy ERP systems like poor performance and lack of strategic reporting capabilities.
The document discusses the Software Development Life Cycle (SDLC), which is a process used in software engineering to design, develop, and test high-quality software. It describes the main phases of SDLC as planning, defining, designing, building, and testing. Key activities in each phase like feasibility study, requirement analysis, prototyping are explained. Various tools used for system analysis and design such as data flow diagrams, flow charts are also outlined.
The document provides an overview of software sizing and function point analysis (FPA). It discusses the need for software sizing to estimate size and manage projects. It introduces common sizing methodologies like lines of code and use cases. The bulk of the document then focuses on explaining FPA, including defining what a function point is, categorizing functional requirements into base components, assigning complexity ratings and counts, and determining an adjusted function point count using value adjustment factors.
The document discusses hybrid machine learning and crowdsourcing approaches for various tasks. It proposes combining machine learning algorithms with human input to contextualize data, identify patterns, process difficult data, and improve algorithms. Example application areas mentioned include transportation (predicting congestion), shopping/advertising (understanding consumer behavior), healthcare (monitoring epidemics), and document translation. It also addresses challenges like privacy, cost, and ensuring high quality contributions from humans. Methods developed so far include crowdsourcing mobile app architectures, learning privacy policies with human guidance, combining Twitter data with transportation agency reports, and algorithms for estimating ground truth and contributor trustworthiness.
Expanding Access to Affordable At-Home EV Charging by Vanessa WarheitForth
Vanessa Warheit, Co-Founder of EV Charging for All, gave this presentation at the Forth Addressing The Challenges of Charging at Multi-Family Housing webinar on June 11, 2024.
Function point analysis is a method of estimating the size of a software or system by counting the number of inputs, outputs, inquiries, internal logical files and external interface files. It was introduced in 1979 as an alternative to simply counting lines of code. Function point analysis measures the software based on end user requirements rather than implementation details. It provides a consistent way to measure software across different projects, organizations and programming languages. The document provides an overview of function point analysis including its history, why it is needed, how it works and how it is used to estimate sizes of major software applications.
Function point analysis is a method of estimating the size of a software application based on the number and complexity of inputs, outputs, inquiries, internal logical files, and external interface files. The document outlines the process for counting function points, which involves identifying the different types of components, determining the unadjusted function point count, assessing value adjustment factors, and calculating the adjusted function point count. Function point analysis provides a standardized, technology-independent way to measure and estimate software size that allows for more accurate comparisons of projects.
The document defines various elements of function point analysis including:
1. File Type References (FTRs), Internal Logical Files (ILFs), External Interface Files (EIFs), External Input (EI), External Output (EO), External Inquiry (EQ), and General System Characteristics (GSCs) which are the main components measured in a function point analysis.
2. It provides descriptions of each component - FTRs refer to files referenced by transactions, ILFs and EIFs are files stored internally or externally, EI involves data entering the system, EO is data exiting, and EQ retrieves data without updates.
3. GSCs consider other factors like architecture and performance that
This document provides an overview of function point estimation techniques. It discusses counting practices, vocabulary, components like external inputs, outputs, inquiries and files. It covers the rating and weighting of different components. The document also discusses techniques like use case point estimation, ESB/SOA estimation and COSMIC functional size measurement. Key aspects covered are decomposing systems, defining business and technical factors, deriving size formulas and nominal values. Productivity relationships and various points to ponder regarding estimation techniques are also presented.
There are three main elements used to determine estimates for black box testing using Test Point Analysis (TPA): size, test strategy, and productivity. Size is mainly defined by the number of function points, but complexity, interfacing, and uniformity must also be considered. Test strategy depends on requirement importance and user usage/importance ratings. Productivity is affected by many factors and depends on the team. Together these three elements are used to calculate the estimated effort for black box testing on a project.
This document summarizes an approach to estimating software size using function point analysis. It involves calculating unadjusted function points based on complexity ratings of internal logical files, external interface files, external inputs, external outputs, and external inquiries. A value adjustment factor is then calculated based on ratings of 14 general system characteristics. The unadjusted function point value is multiplied by the value adjustment factor to obtain the final function point count, which provides an estimate of the software size independent of implementation technologies. The document provides an example calculation where unadjusted function points are determined to be 194, the value adjustment factor is 0.81, resulting in a final function point count of 157.
This document discusses function point analysis, which is a method for estimating the size of application software based on its functionality from the user's perspective. It involves identifying different types of functions - external inputs, outputs, inquiries, internal logical files, and external interface files. Each function is classified as simple, average, or complex and assigned a weight. These weights are summed to calculate the unadjusted function point count. A value adjustment factor is also calculated based on characteristics of the system to adjust the unadjusted function point count. The final function point count is obtained by multiplying the unadjusted function point count by the value adjustment factor. As an example, the document calculates the unadjusted function point count and value adjustment factor for a sample project to
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
What is Quality ||
Software Quality Metrics ||
Types of Software Quality Metrics ||
Three groups of Software Quality Metrics ||
Customer Satisfaction Metrics ||
Tools used for Quality Metrics/Measurements ||
PERT and CPM ||
A document discusses various software estimation techniques including function point analysis, COCOMO models, and cost drivers. Function point analysis breaks a system into functional components like inputs, outputs, inquiries and files that are assigned complexity weights and counts. COCOMO models like COCOMO I and COCOMO II estimate effort using size of the project and cost multipliers related to attributes of the product, computer system, personnel and project. Cost drivers help assess these multipliers to refine effort estimates.
This document discusses Function Point Analysis, which is a technique for measuring the size of software systems. It breaks systems into smaller components like external inputs, outputs, inquiries, internal logical files, and external interface files. Counting these components provides a total Function Point that can be used to measure a system's size, track scope changes, and compare productivity across tools and languages. The benefits are that Function Points allow for accurate sizing, can be counted consistently, and help with estimating and communicating a system's size to stakeholders.
The document discusses software estimation techniques. It describes estimating the size and cost of software projects using methods like lines of code counting, function point counting, and work breakdown structures. It discusses best practices for software estimation like explicitly defining project scope, using historical metrics, employing multiple techniques or estimators, and accounting for inherent uncertainty. The document then explains techniques like function point analysis in detail, including how to classify components, assign complexity weights, and compute the final function point count and estimation.
1. The document discusses software project planning and estimation techniques. It covers size estimation, cost estimation, development time estimation, and project scheduling.
2. The document discusses different techniques for estimating the size of a software project, including lines of code counting and function point analysis. It provides examples of how to apply function point analysis to estimate the size of a project.
3. Function point analysis breaks a project into different functional components or units and assigns weighted scores to each unit based on complexity. The counts are then adjusted based on other project factors to determine the total function points of the project, which can then estimate development effort.
This document discusses software metrics and function point analysis. It provides information on different types of software metrics including size-oriented, function-oriented, and attribute metrics. It then focuses on explaining function point analysis in detail. Function point analysis measures software size based on user requirements rather than lines of code. It involves counting various functional components and adjusting for complexity. The document provides steps to calculate unadjusted and adjusted function points for different examples. Overall, the document provides a comprehensive overview of software metrics with a focus on function point analysis methodology.
This document describes a project that implements graphical password authentication to access applications remotely. It uses images retrieved from a database for the login process. The user must select the exact images to gain access. It also allows remote control functions like shutdown and file permissions checks. The project has modules for authentication, remote handling, file searching, privileges management, and process management. It was developed using technologies like JDK, Java Swing, Oracle, and RMI. The purpose is to provide a more secure authentication method compared to text passwords.
The document discusses an integrated ERP system with a web portal. It proposes using ETL tools to extract data from legacy ERP systems and load it into a centralized data warehouse ("one-version data store"). Data marts are then extracted from the data warehouse to improve query response times. A web portal is built on top of the data marts to provide customized, personalized access and collaboration for managers to support decision making using business intelligence tools. The model aims to address challenges of legacy ERP systems like poor performance and lack of strategic reporting capabilities.
The document discusses the Software Development Life Cycle (SDLC), which is a process used in software engineering to design, develop, and test high-quality software. It describes the main phases of SDLC as planning, defining, designing, building, and testing. Key activities in each phase like feasibility study, requirement analysis, prototyping are explained. Various tools used for system analysis and design such as data flow diagrams, flow charts are also outlined.
The document provides an overview of software sizing and function point analysis (FPA). It discusses the need for software sizing to estimate size and manage projects. It introduces common sizing methodologies like lines of code and use cases. The bulk of the document then focuses on explaining FPA, including defining what a function point is, categorizing functional requirements into base components, assigning complexity ratings and counts, and determining an adjusted function point count using value adjustment factors.
The document discusses hybrid machine learning and crowdsourcing approaches for various tasks. It proposes combining machine learning algorithms with human input to contextualize data, identify patterns, process difficult data, and improve algorithms. Example application areas mentioned include transportation (predicting congestion), shopping/advertising (understanding consumer behavior), healthcare (monitoring epidemics), and document translation. It also addresses challenges like privacy, cost, and ensuring high quality contributions from humans. Methods developed so far include crowdsourcing mobile app architectures, learning privacy policies with human guidance, combining Twitter data with transportation agency reports, and algorithms for estimating ground truth and contributor trustworthiness.
Expanding Access to Affordable At-Home EV Charging by Vanessa WarheitForth
Vanessa Warheit, Co-Founder of EV Charging for All, gave this presentation at the Forth Addressing The Challenges of Charging at Multi-Family Housing webinar on June 11, 2024.
Charging Fueling & Infrastructure (CFI) Program Resources by Cat PleinForth
Cat Plein, Development & Communications Director of Forth, gave this presentation at the Forth and Electrification Coalition CFI Grant Program - Overview and Technical Assistance webinar on June 12, 2024.
Implementing ELDs or Electronic Logging Devices is slowly but surely becoming the norm in fleet management. Why? Well, integrating ELDs and associated connected vehicle solutions like fleet tracking devices lets businesses and their in-house fleet managers reap several benefits. Check out the post below to learn more.
Charging Fueling & Infrastructure (CFI) Program by Kevin MillerForth
Kevin Miller, Senior Advisor, Business Models of the Joint Office of Energy and Transportation gave this presentation at the Forth and Electrification Coalition CFI Grant Program - Overview and Technical Assistance webinar on June 12, 2024.
Welcome to ASP Cranes, your trusted partner for crane solutions in Raipur, Chhattisgarh! With years of experience and a commitment to excellence, we offer a comprehensive range of crane services tailored to meet your lifting and material handling needs.
At ASP Cranes, we understand the importance of reliable and efficient crane operations in various industries, from construction and manufacturing to logistics and infrastructure development. That's why we strive to deliver top-notch solutions that enhance productivity, safety, and cost-effectiveness for our clients.
Our services include:
Crane Rental: Whether you need a crawler crane for heavy lifting or a hydraulic crane for versatile operations, we have a diverse fleet of well-maintained cranes available for rent. Our rental options are flexible and can be customized to suit your project requirements.
Crane Sales: Looking to invest in a crane for your business? We offer a wide selection of new and used cranes from leading manufacturers, ensuring you find the perfect equipment to match your needs and budget.
Crane Maintenance and Repair: To ensure optimal performance and safety, regular maintenance and timely repairs are essential for cranes. Our team of skilled technicians provides comprehensive maintenance and repair services to keep your equipment running smoothly and minimize downtime.
Crane Operator Training: Proper training is crucial for safe and efficient crane operation. We offer specialized training programs conducted by certified instructors to equip operators with the skills and knowledge they need to handle cranes effectively.
Custom Solutions: We understand that every project is unique, which is why we offer custom crane solutions tailored to your specific requirements. Whether you need modifications, attachments, or specialized equipment, we can design and implement solutions that meet your needs.
At ASP Cranes, customer satisfaction is our top priority. We are dedicated to delivering reliable, cost-effective, and innovative crane solutions that exceed expectations. Contact us today to learn more about our services and how we can support your project in Raipur, Chhattisgarh, and beyond. Let ASP Cranes be your trusted partner for all your crane needs!
Understanding Catalytic Converter Theft:
What is a Catalytic Converter?: Learn about the function of catalytic converters in vehicles and why they are targeted by thieves.
Why are They Stolen?: Discover the valuable metals inside catalytic converters (such as platinum, palladium, and rhodium) that make them attractive to criminals.
Steps to Prevent Catalytic Converter Theft:
Parking Strategies: Tips on where and how to park your vehicle to reduce the risk of theft, such as parking in well-lit areas or secure garages.
Protective Devices: Overview of various anti-theft devices available, including catalytic converter locks, shields, and alarms.
Etching and Marking: The benefits of etching your vehicle’s VIN on the catalytic converter or using a catalytic converter marking kit to make it traceable and less appealing to thieves.
Surveillance and Monitoring: Recommendations for using security cameras and motion-sensor lights to deter thieves.
Statistics and Insights:
Theft Rates by Borough: Analysis of data to determine which borough in NYC experiences the highest rate of catalytic converter thefts.
Recent Trends: Current trends and patterns in catalytic converter thefts to help you stay aware of emerging hotspots and tactics used by thieves.
Benefits of This Presentation:
Awareness: Increase your awareness about catalytic converter theft and its impact on vehicle owners.
Practical Tips: Gain actionable insights and tips to effectively prevent catalytic converter theft.
Local Insights: Understand the specific risks in different NYC boroughs, helping you take targeted preventive measures.
This presentation aims to equip you with the knowledge and tools needed to protect your vehicle from catalytic converter theft, ensuring you are prepared and proactive in safeguarding your property.
Charging and Fueling Infrastructure Grant: Round 2 by Brandt HertensteinForth
Brandt Hertenstein, Program Manager of the Electrification Coalition gave this presentation at the Forth and Electrification Coalition CFI Grant Program - Overview and Technical Assistance webinar on June 12, 2024.
EV Charging at MFH Properties by Whitaker JamiesonForth
Whitaker Jamieson, Senior Specialist at Forth, gave this presentation at the Forth Addressing The Challenges of Charging at Multi-Family Housing webinar on June 11, 2024.
1. An Introduction to Function Point Analysis
by Roger Heller
The purpose of this article is to provide an introduction to Function Point Analysis and its application in
non-traditional computing situations. Software engineers have been searching for a metric that is
applicable for a broad range of software environments. The metric should be technology independent
and support the need for estimating, project management, measuring quality and gathering
requirements. Function Point Analysis is rapidly becoming the measure of choice for these tasks.
Function Point Analysis has been proven as a reliable method for measuring the size of computer
software. In addition to measuring output, Function Point Analysis is extremely useful in estimating
projects, managing change of scope, measuring productivity, and communicating functional
requirements.
There have been many misconceptions regarding the appropriateness of Function Point Analysis in
evaluating emerging environments such as real time embedded code and Object Oriented programming.
Since function points express the resulting work-product in terms of functionality as seen from the user's
perspective, the tools and technologies used to deliver it are independent.
The following provides an introduction to Function Point Analysis and is followed by further discussion of
potential benefits.
Introduction to Function Point Analysis
One of the initial design criteria for function points was to provide a mechanism that both software
developers and users could utilize to define functional requirements. It was determined that the best way
to gain an understanding of the users' needs was to approach their problem from the perspective of how
they view the results an automated system produces. Therefore, one of the primary goals of Function
Point Analysis is to evaluate a system's capabilities from a user's point of view. To achieve this goal, the
analysis is based upon the various ways users interact with computerized systems. From a user's
perspective a system assists them in doing their job by providing five (5) basic functions. Two of these
address the data requirements of an end user and are referred to as Data Functions. The remaining
three address the user's need to access data and are referred to as Transactional Functions.
The Five Components of Function Points
Data Functions
Internal Logical Files
External Interface Files
Transactional Functions
External Inputs
External Outputs
External Inquiries
2. Internal Logical Files - The first data function allows users to utilize data they are responsible for
maintaining. For example, a pilot may enter navigational data through a display in the cockpit prior to
departure. The data is stored in a file for use and can be modified during the mission. Therefore the pilot
is responsible for maintaining the file that contains the navigational information. Logical groupings of
data in a system, maintained by an end user, are referred to as Internal Logical Files (ILF).
External Interface Files - The second Data Function a system provides an end user is also related to
logical groupings of data. In this case the user is not responsible for maintaining the data. The data
resides in another system and is maintained by another user or system. The user of the system being
counted requires this data for reference purposes only. For example, it may be necessary for a pilot to
reference position data from a satellite or ground-based facility during flight. The pilot does not have the
responsibility for updating data at these sites but must reference it during the flight. Groupings of data
from another system that are used only for reference purposes are defined as External Interface Files
(EIF).
The remaining functions address the user's capability to access the data contained in ILFs and EIFs.
This capability includes maintaining, inquiring and outputting of data. These are referred to as
Transactional Functions.
External Input - The first Transactional Function allows a user to maintain Internal Logical Files (ILFs)
through the ability to add, change and delete the data. For example, a pilot can add, change and delete
navigational information prior to and during the mission. In this case the pilot is utilizing a transaction
referred to as an External Input (EI). An External Input gives the user the capability to maintain the data
in ILF's through adding, changing and deleting its contents.
External Output - The next Transactional Function gives the user the ability to produce outputs. For
example a pilot has the ability to separately display ground speed, true air speed and calibrated air
speed. The results displayed are derived using data that is maintained and data that is referenced. In
function point terminology the resulting display is called an External Output (EO).
External Inquiries - The final capability provided to users through a computerized system addresses the
requirement to select and display specific data from files. To accomplish this a user inputs selection
information that is used to retrieve data that meets the specific criteria. In this situation there is no
manipulation of the data. It is a direct retrieval of information contained on the files. For example if a pilot
displays terrain clearance data that was previously set, the resulting output is the direct retrieval of
stored information. These transactions are referred to as External Inquiries (EQ).
In addition to the five functional components described above there are two adjustment factors that need
to be considered in Function Point Analysis.
Functional Complexity - The first adjustment factor considers the Functional Complexity for each
unique function. Functional Complexity is determined based on the combination of data groupings and
data elements of a particular function. The number of data elements and unique groupings are counted
and compared to a complexity matrix that will rate the function as low, average or high complexity. Each
of the five functional components (ILF, EIF, EI, EO and EQ) has its own unique complexity matrix. The
following is the complexity matrix for External Outputs.
3. 1-5 DETs 6 - 19 DETs 20+ DETs
0 or 1 FTRs L L A
2 or 3 FTRs L A H
4+ FTRs A H H
Complexity UFP
L (Low) 4
A (Average) 5
H (High) 7
Using the examples given above and their appropriate complexity matrices, the function point count for
these functions would be:
Function Name Function Type
Record
Element Type
Data
Element Type
File Types
Referenced
Unadjusted
FPs
Navigational
data
ILF 3 36 n/a 10
Positional
data
EIF 1 3 n/a 5
Navigational
data - add
EI n/a 36 1 4
Navigational
data - change
EI n/a 36 1 4
Navigational
data - delete
EI n/a 3 1 3
Ground speed
display
EO n/a 20 3 7
Air speed
display
EO n/a 20 3 7
Calibrated air
speed display
EO n/a 20 3 7
Terrain clearance
display
EQ n/a 1 1 3
Total unadjusted count 50 UFPs
All of the functional components are analyzed in this way and added together to derive an Unadjusted
Function Point count.
Value Adjustment Factor - The Unadjusted Function Point count is multiplied by the second adjustment
factor called the Value Adjustment Factor. This factor considers the system's technical and operational
4. characteristics and is calculated by answering 14 questions. The factors are:
1. Data Communications
The data and control information used in the application are sent or received over communication
facilities.
2. Distributed Data Processing
Distributed data or processing functions are a characteristic of the application within the application
boundary.
3. Performance
Application performance objectives, stated or approved by the user, in either response or throughput,
influence (or will influence) the design, development, installation and support of the application.
4. Heavily Used Configuration
A heavily used operational configuration, requiring special design considerations, is a characteristic of
the application.
5. Transaction Rate
The transaction rate is high and influences the design, development, installation and support.
6. On-line Data Entry
On-line data entry and control information functions are provided in the application.
7. End -User Efficiency
The on-line functions provided emphasize a design for end-user efficiency.
8. On-line Update
The application provides on-line update for the internal logical files.
9. Complex Processing
Complex processing is a characteristic of the application.
10. Reusability
The application and the code in the application have been specifically designed, developed and
supported to be usable in other applications.
11. Installation Ease
Conversion and installation ease are characteristics of the application. A conversion and installation plan
and/or conversion tools were provided and tested during the system test phase.
12. Operational Ease
Operational ease is a characteristic of the application. Effective start-up, backup and recovery
procedures were provided and tested during the system test phase.
13. Multiple Sites
The application has been specifically designed, developed and supported to be installed at multiple sites
for multiple organizations.
5. 14. Facilitate Change
The application has been specifically designed, developed and supported to facilitate change.
Each of these factors is scored based on their influence on the system being counted. The resulting
score will increase or decrease the Unadjusted Function Point count by 35%. This calculation provides
us with the Adjusted Function Point count.
An Approach to Counting Function Points
There are several approaches used to count function points. Q/P Management Group, Inc. has found
that a structured workshop conducted with people who are knowledgeable of the functionality provided
through the application is an efficient, accurate way of collecting the necessary data. The workshop
approach allows the counter to develop a representation of the application from a functional perspective
and educate the participants about function points.
Function point counting can be accomplished with minimal documentation. However, the accuracy and
efficiency of the counting improves with appropriate documentation. Examples of appropriate
documentation are:
Design specifications
Display designs
Data requirements (Internal and External)
Description of user interfaces
Function point counts are calculated during the workshop and documented with both a diagram that
depicts the application and worksheets that contain the details of each function discussed.
Benefits of Function Point Analysis
Organizations that adopt Function Point Analysis as a software metric realize many benefits including:
improved project estimating; understanding project and maintenance productivity; managing changing
project requirements; and gathering user requirements. Each of these is discussed below.
Estimating software projects is as much an art as a science. While there are several environmental
factors that need to be considered in estimating projects, two key data points are essential. The first is
the size of the deliverable. The second addresses how much of the deliverable can be produced within a
defined period of time. Size can be derived from Function Points, as described above. The second
requirement for estimating is determining how long it takes to produce a function point. This delivery rate
can be calculated based on past project performance or by using industry benchmarks. The delivery rate
is expressed in function points per hour (FP/Hr) and can be applied to similar proposed projects to
estimate effort (i.e. Project Hours = estimated project function points FP/Hr).
Productivity measurement is a natural output of Function Points Analysis. Since function points are
technology independent they can be used as a vehicle to compare productivity across dissimilar tools
and platforms. More importantly, they can be used to establish a productivity rate (i.e. FP/Hr) for a
specific tool set and platform. Once productivity rates are established they can be used for project
estimating as described above and tracked over time to determine the impact continuous process
improvement initiatives have on productivity.
In addition to delivery productivity, function points can be used to evaluate the support requirements for
maintaining systems. In this analysis, productivity is determined by calculating the number of function
6. points one individual can support for a given system in a year (i.e. FP/FTE year). When compared with
other systems, these rates help to identify which systems require the most support. The resulting
analysis helps an organization develop a maintenance and replacement strategy for those systems that
have high maintenance requirements.
Managing Change of Scope for an in-process project is another key benefit of Function Point Analysis.
Once a project has been approved and the function point count has been established, it becomes a
relatively easy task to identify, track and communicate new and changing requirements. As requests
come in from users for new displays or capabilities, function point counts are developed and applied
against the rate. This result is then used to determine the impact on budget and effort. The user and the
project team can then determine the importance of the request against its impact on budget and
schedule. At the conclusion of the project the final function point count can be evaluated against the
initial estimate to determine the effectiveness of requirements gathering techniques. This analysis helps
to identify opportunities to improve the requirements definition process.
Communicating Functional Requirements was the original objective behind the development of function
points. Since it avoids technical terminology and focuses on user requirements it is an excellent vehicle
to communicate with users. The techniques can be used to direct customer interviews and document the
results of Joint Application Design (JAD) sessions. The resulting documentation provides a framework
that describes user and technical requirements.
In conclusion, Function Point Analysis has proven to be an accurate technique for sizing, documenting
and communicating a system's capabilities. It has been successfully used to evaluate the functionality of
real-time and embedded code systems, such as robot based warehouses and avionics, as well as
traditional data processing. As computing environments become increasingly complex, it is proving to be
a valuable tool that accurately reflects the systems we deliver and maintain.