COMPARATIVE STUDY OF SOFTWARE ESTIMATION TECHNIQUES ijseajournal
Many information technology firms among other organizations have been working on how to perform estimation of the sources such as fund and other resources during software development processes. Software development life cycles require lot of activities and skills to avoid risks and the best software estimation technique is supposed to be employed. Therefore, in this research, a comparative study was conducted, that consider the accuracy, usage, and suitability of existing methods. It will be suitable for the project managers and project consultants during the whole software project development process. In this project technique such as linear regression; both algorithmic and non-algorithmic are applied. Model, composite and regression techniques are used to derive COCOMO, COCOMO II, SLIM and linear multiple respectively. Moreover, expertise-based and linear-based rules are applied in non-algorithm methods. However, the technique needs some advancement to reduce the errors that are experienced during the software development process. Therefore, this paper in relation to software estimation techniques has proposed a model that can be helpful to the information technology firms, researchers and other firms that use information technology in the processes such as budgeting and decision-making processes.
Optimizing Effort Parameter of COCOMO II Using Particle Swarm Optimization Me...TELKOMNIKA JOURNAL
Estimating the effort and cost of software is an important activity for software project managers. A poor estimate (overestimates or underestimates) will result in poor software project management. To handle this problem, many researchers have proposed various models for estimating software cost. Constructive Cost Model II (COCOMO II) is one of the best known and widely used models for estimating software costs. To estimate the cost of a software project, the COCOMO II model uses software size, cost drivers, scale factors as inputs. However, this model is still lacking in terms of accuracy. To improve the accuracy of COCOMO II model, this study examines the effect of the cost factor and scale factor in improving the accuracy of effort estimation. In this study, we initialized using Particle Swarm Optimization (PSO) to optimize the parameters in a model of COCOMO II. The method proposed is implemented using the Turkish Software Industry dataset which has 12 data items. The method can handle improper and uncertain inputs efficiently, as well as improves the reliability of software effort. The experiment results by MMRE were 34.1939%, indicating better high accuracy and significantly minimizing error 698.9461% and 104.876%.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-gormish
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Michael Gormish, Research Manager at Clarifai, presents the "Machine Learning- based Image Compression: Ready for Prime Time?" tutorial at the May 2019 Embedded Vision Summit.
Computer vision is undergoing dramatic changes because deep learning techniques are now able to solve complex non-linear problems. Computer vision pipelines used to consist of hand engineered stages mathematically optimized for some carefully chosen objective function. These pipelines are being replaced with machine- learned stages or end-to-end learning techniques where enough ground truth data is available.
Similarly, for decades image compression has relied on hand crafted algorithm pipelines, but recent efforts using deep learning are reporting higher image quality than that provided by conventional techniques. Is it time to replaced discrete cosine transforms with machine-learned compression techniques?
This talk examines practical aspects of deep learned image compression systems as compared with traditional approaches. Gormish considers memory, computation and other aspects, in addition to rate-distortion, to see when ML-based compression should be considered or avoided. He also discusses approaches using a combination of machine learned and traditional techniques.
THEMATIC TOPIC 1. Making Healthy Choices - Speaker 1Joni Vatuvatu
Please find presentations for THEMATIC TOPIC 1. Making Healthy Choices. Its been converted to Windows Media Video files. Apologies for any convenience. PPT files can always be collected from your youth officers.
COMPARATIVE STUDY OF SOFTWARE ESTIMATION TECHNIQUES ijseajournal
Many information technology firms among other organizations have been working on how to perform estimation of the sources such as fund and other resources during software development processes. Software development life cycles require lot of activities and skills to avoid risks and the best software estimation technique is supposed to be employed. Therefore, in this research, a comparative study was conducted, that consider the accuracy, usage, and suitability of existing methods. It will be suitable for the project managers and project consultants during the whole software project development process. In this project technique such as linear regression; both algorithmic and non-algorithmic are applied. Model, composite and regression techniques are used to derive COCOMO, COCOMO II, SLIM and linear multiple respectively. Moreover, expertise-based and linear-based rules are applied in non-algorithm methods. However, the technique needs some advancement to reduce the errors that are experienced during the software development process. Therefore, this paper in relation to software estimation techniques has proposed a model that can be helpful to the information technology firms, researchers and other firms that use information technology in the processes such as budgeting and decision-making processes.
Optimizing Effort Parameter of COCOMO II Using Particle Swarm Optimization Me...TELKOMNIKA JOURNAL
Estimating the effort and cost of software is an important activity for software project managers. A poor estimate (overestimates or underestimates) will result in poor software project management. To handle this problem, many researchers have proposed various models for estimating software cost. Constructive Cost Model II (COCOMO II) is one of the best known and widely used models for estimating software costs. To estimate the cost of a software project, the COCOMO II model uses software size, cost drivers, scale factors as inputs. However, this model is still lacking in terms of accuracy. To improve the accuracy of COCOMO II model, this study examines the effect of the cost factor and scale factor in improving the accuracy of effort estimation. In this study, we initialized using Particle Swarm Optimization (PSO) to optimize the parameters in a model of COCOMO II. The method proposed is implemented using the Turkish Software Industry dataset which has 12 data items. The method can handle improper and uncertain inputs efficiently, as well as improves the reliability of software effort. The experiment results by MMRE were 34.1939%, indicating better high accuracy and significantly minimizing error 698.9461% and 104.876%.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-gormish
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Michael Gormish, Research Manager at Clarifai, presents the "Machine Learning- based Image Compression: Ready for Prime Time?" tutorial at the May 2019 Embedded Vision Summit.
Computer vision is undergoing dramatic changes because deep learning techniques are now able to solve complex non-linear problems. Computer vision pipelines used to consist of hand engineered stages mathematically optimized for some carefully chosen objective function. These pipelines are being replaced with machine- learned stages or end-to-end learning techniques where enough ground truth data is available.
Similarly, for decades image compression has relied on hand crafted algorithm pipelines, but recent efforts using deep learning are reporting higher image quality than that provided by conventional techniques. Is it time to replaced discrete cosine transforms with machine-learned compression techniques?
This talk examines practical aspects of deep learned image compression systems as compared with traditional approaches. Gormish considers memory, computation and other aspects, in addition to rate-distortion, to see when ML-based compression should be considered or avoided. He also discusses approaches using a combination of machine learned and traditional techniques.
THEMATIC TOPIC 1. Making Healthy Choices - Speaker 1Joni Vatuvatu
Please find presentations for THEMATIC TOPIC 1. Making Healthy Choices. Its been converted to Windows Media Video files. Apologies for any convenience. PPT files can always be collected from your youth officers.
With estimates that the global population will expand by 2.7 billion by 2050, …, pressure is mounting for farmers to lift yields by 50 per cent to keep abreast of growth in global demand.
We need to create conditions for innovation and then invest so that innovation moves from the lab to the farmer’s fields.
The Australian food industry as a whole supports 317,000 direct jobs, and a flow through of
about 1.6 million jobs. Yet Australian food producing and manufacturing sectors have
struggled to receive the recognition and support they deserve. Australia’s food
manufacturing exports are still very strong, worth $17 billion a year, more than education and
tourism. Australia also sits on the edge of a very fast growing and immense opportunity to
feed the booming middle class of Asia which is forecast to grow from 500 million people to 3
billion people in the coming decadesii.With the inevitable change of diet that increasing
affluence brings to our Asian neighbours we can expect to see a shift towards a more protein
rich diet and a desire to enjoy the good food, wine and cheer that many of us in Australia
enjoy every day.
Innovation in the food industry is sorely needed to meet the changing lives and needs of
today’s consumers, customers and communities.
Business innovation and international business need to be high on your priorities so you can
do more with less and learn from the fast emerging mega-markets in our region and their
immense demand potential for the Australian Food Industry.
Dermott Dowling is the founding Director of @Creatovate www.creatovate.com.au
Innovation & International Consultancy. Creatovate consult to businesses on how to create
and embed innovation processes and craft international business strategy, market entry
plans and set up or outsource international business services.
Global food challenge Australian international business opportunityCreatovate Pty Ltd
Guest lecture to International Business students on global food challenge and opportunity for Australian International Food Businesses including a case study on Berri Indonesia.
The future is “uncertain” and certain
By 2050 9.5 billion of us will be hungry!
However, by 2030 2 billion of us will be overweight and 1 billion obese.
Consolidation of manufacturers will continue at faster rates and retailers albeit more challenging in global retail.
Expect a significant step up from the competition in your home market when you go abroad to build your business.
This surprise talk was given on 2014-06-03 at Riviera.rb.
The slides are really just up for reference: unless you're a sociopathic genius with an uncanny cultural fit, you're really not going to understand much without the speech.
Going global in food and beverage manufacturing, marketing and retailing is easy is it not? The big get bigger and fewer in number. The little guys keep popping up in their local niches. The middle gets squeezed. Its not all beer and skittles expanding your exports in Asia and its even harder if you are a retailer. The opportunity is there for business to capture in the long run we have more hungry mouths to feed and innovation is sorely needed to grow and feed the population sustainably.
This video is presented by USEP's BSCS student Melissa B. Carpio under Mr. ND Arquillano as a partial fulfilment for Elective 4 -E-Commerce.
It talks about:
*Introduction to e-business and e-commerce
*E-commerce fundamentals
*E-business infrastructure
*E-environment
*Supply chain management
*E-marketing
*Customer relationship management
*Change management
*Analysis and design
*M-Commerce
*Management of mobile commerce services
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
USING FACTORY DESIGN PATTERNS IN MAP REDUCE DESIGN FOR BIG DATA ANALYTICSHCL Technologies
Though insights from Big Data gives a breakthrough to make better business decision, it poses its own set of challenges. This paper addresses the gap of Variety problem and suggest a way to seamlessly handle data processing even if there is change in data type/processing algorithm. It explores the various map reduce design patterns and comes out with a unified working solution (library). The library has the potential to ‘adapt’ itself to any data processing need which can be achieved by Map Reduce saving lot of man hours and enforce good practices in code.
Is Multicore Hardware For General-Purpose Parallel Processing Broken? : NotesSubhajit Sahu
Highlighted notes of article while studying Concurrent Data Structures, CSE:
Is Multicore Hardware For General-Purpose Parallel Processing Broken?
By Uzi Vishkin
Communications of the ACM, April 2014, Vol. 57 No. 4, Pages 35-39
10.1145/2580945
Why would you want to use cloud for your Planning and Budgeting needsJade Global
“Cloud” is becoming the latest buzzword everywhere. Not only in technology, but in every business, executives are wondering how exactly they can benefit from the Cloud. At the same time, they do not want to stir up the comfort level of their company’s current user base.
Development of resource-intensive applications in Visual C++PVS-Studio
The article will familiarize application developers with tasks given them by the mass introduction of 64-bit multi-core processors symbolizing revolutionary increase of computing power available for an average user. It will also touch upon the problems of effective use of hardware resources for solving everyday applied tasks within the limits of Windows x64 operating system
Development of resource-intensive applications in Visual C++Andrey Karpov
The article will familiarize application developers with tasks given them by the mass introduction of 64-bit multi-core processors symbolizing revolutionary increase of computing power available for an average user. It will also touch upon the problems of effective use of hardware resources for solving everyday applied tasks within the limits of Windows x64 operating system
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
With estimates that the global population will expand by 2.7 billion by 2050, …, pressure is mounting for farmers to lift yields by 50 per cent to keep abreast of growth in global demand.
We need to create conditions for innovation and then invest so that innovation moves from the lab to the farmer’s fields.
The Australian food industry as a whole supports 317,000 direct jobs, and a flow through of
about 1.6 million jobs. Yet Australian food producing and manufacturing sectors have
struggled to receive the recognition and support they deserve. Australia’s food
manufacturing exports are still very strong, worth $17 billion a year, more than education and
tourism. Australia also sits on the edge of a very fast growing and immense opportunity to
feed the booming middle class of Asia which is forecast to grow from 500 million people to 3
billion people in the coming decadesii.With the inevitable change of diet that increasing
affluence brings to our Asian neighbours we can expect to see a shift towards a more protein
rich diet and a desire to enjoy the good food, wine and cheer that many of us in Australia
enjoy every day.
Innovation in the food industry is sorely needed to meet the changing lives and needs of
today’s consumers, customers and communities.
Business innovation and international business need to be high on your priorities so you can
do more with less and learn from the fast emerging mega-markets in our region and their
immense demand potential for the Australian Food Industry.
Dermott Dowling is the founding Director of @Creatovate www.creatovate.com.au
Innovation & International Consultancy. Creatovate consult to businesses on how to create
and embed innovation processes and craft international business strategy, market entry
plans and set up or outsource international business services.
Global food challenge Australian international business opportunityCreatovate Pty Ltd
Guest lecture to International Business students on global food challenge and opportunity for Australian International Food Businesses including a case study on Berri Indonesia.
The future is “uncertain” and certain
By 2050 9.5 billion of us will be hungry!
However, by 2030 2 billion of us will be overweight and 1 billion obese.
Consolidation of manufacturers will continue at faster rates and retailers albeit more challenging in global retail.
Expect a significant step up from the competition in your home market when you go abroad to build your business.
This surprise talk was given on 2014-06-03 at Riviera.rb.
The slides are really just up for reference: unless you're a sociopathic genius with an uncanny cultural fit, you're really not going to understand much without the speech.
Going global in food and beverage manufacturing, marketing and retailing is easy is it not? The big get bigger and fewer in number. The little guys keep popping up in their local niches. The middle gets squeezed. Its not all beer and skittles expanding your exports in Asia and its even harder if you are a retailer. The opportunity is there for business to capture in the long run we have more hungry mouths to feed and innovation is sorely needed to grow and feed the population sustainably.
This video is presented by USEP's BSCS student Melissa B. Carpio under Mr. ND Arquillano as a partial fulfilment for Elective 4 -E-Commerce.
It talks about:
*Introduction to e-business and e-commerce
*E-commerce fundamentals
*E-business infrastructure
*E-environment
*Supply chain management
*E-marketing
*Customer relationship management
*Change management
*Analysis and design
*M-Commerce
*Management of mobile commerce services
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
USING FACTORY DESIGN PATTERNS IN MAP REDUCE DESIGN FOR BIG DATA ANALYTICSHCL Technologies
Though insights from Big Data gives a breakthrough to make better business decision, it poses its own set of challenges. This paper addresses the gap of Variety problem and suggest a way to seamlessly handle data processing even if there is change in data type/processing algorithm. It explores the various map reduce design patterns and comes out with a unified working solution (library). The library has the potential to ‘adapt’ itself to any data processing need which can be achieved by Map Reduce saving lot of man hours and enforce good practices in code.
Is Multicore Hardware For General-Purpose Parallel Processing Broken? : NotesSubhajit Sahu
Highlighted notes of article while studying Concurrent Data Structures, CSE:
Is Multicore Hardware For General-Purpose Parallel Processing Broken?
By Uzi Vishkin
Communications of the ACM, April 2014, Vol. 57 No. 4, Pages 35-39
10.1145/2580945
Why would you want to use cloud for your Planning and Budgeting needsJade Global
“Cloud” is becoming the latest buzzword everywhere. Not only in technology, but in every business, executives are wondering how exactly they can benefit from the Cloud. At the same time, they do not want to stir up the comfort level of their company’s current user base.
Development of resource-intensive applications in Visual C++PVS-Studio
The article will familiarize application developers with tasks given them by the mass introduction of 64-bit multi-core processors symbolizing revolutionary increase of computing power available for an average user. It will also touch upon the problems of effective use of hardware resources for solving everyday applied tasks within the limits of Windows x64 operating system
Development of resource-intensive applications in Visual C++Andrey Karpov
The article will familiarize application developers with tasks given them by the mass introduction of 64-bit multi-core processors symbolizing revolutionary increase of computing power available for an average user. It will also touch upon the problems of effective use of hardware resources for solving everyday applied tasks within the limits of Windows x64 operating system
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Why migrate from ibm cognos planning to tm1 ?Intellium
IBM Cognos Enterprise Planning (IBM Cognos EP) was the leading choice for budgeting and forecasting for financial analysts who would like to streamline their financial planning process. However, the core of the IBM Cognos EP application was built more than a decade ago, and lacks the scalability and flexibility necessary to effectively manage increasing volumes of financial data that are now common in most organizations. Scalability, speed and maintenance challenges are often addressed by limiting the design to a lesser granular level.
The release of Cognos TM1 has provided a wide range of services for developing timely, reliable and dynamic forecasting and budgeting solutions. Users can now manipulate large data sets that support real-time reporting and give management an improved perspective on their business operations, financial metrics and operational metrics.
The Purpose of this whitepaper is to provide an overview of why and how to migrate from IBM Cognos EP to IBM Cognos TM1.
Wholesale electricity markets in the U.S. have brought significant benefits to society by maximizing social welfare while ensuring system security. Optimization models and algorithms are at the core of the software tools used to make this happen. In recent years, the Midcontinent Independent System Operator (MISO) has focused its attention on improving its market clearing software performance to enable further developments in its market products. This has largely entailed reducing solve time to ensure the timely commitment of resources and maintaining high optimality in the solutions. With rapid evolution in the power sector, MISO believes software performance will become increasingly important. The diversity of resources offering their services into MISO’s markets is growing and the portfolio of existing resources and fuel types has shifted rapidly in recent years. In turn, resource modeling requirements are becoming more complicated, system constraints more intricate, and the volume of information greater. This paper introduces the research and development of the next generation market clearing software under the Department of Energy (DOE) Advanced Research Projects Agency–Energy (ARPA-E) project to develop high performance computer based optimization engines. The goal is to position Regional Transmission Organization or Independent System Operator (RTO/ISO) for future industry evolution.
Wholesale electricity markets in the U.S. have brought significant benefits to society by maximizing social welfare while ensuring system security. Optimization models and algorithms are at the core of the software tools used to make this happen. In recent years, the Midcontinent Independent System Operator (MISO) has focused its attention on improving its market clearing software performance to enable further developments in its market products. This has largely entailed reducing solve time to ensure the timely commitment of resources and maintaining high optimality in the solutions. With rapid evolution in the power sector, MISO believes software performance will become increasingly important. The diversity of resources offering their services into MISO’s markets is growing and the portfolio of existing resources and fuel types has shifted rapidly in recent years. In turn, resource modeling requirements are becoming more complicated, system constraints more intricate, and the volume of information greater. This paper introduces the research and development of the next generation market clearing software under the Department of Energy (DOE) Advanced Research Projects Agency–Energy (ARPA-E) project to develop high performance computer based optimization engines. The goal is to position Regional Transmission Organization or Independent System Operator (RTO/ISO) for future industry evolution.
A new model for software costestimationijfcstjournal
Accurate and realistic estimation is always considered to be a great challenge in software industry.
Software Cost Estimation (SCE) is the standard application used to manage software projects. Determining
the amount of estimation in the initial stages of the project depends on planning other activities of the
project. In fact, the estimation is confronted with a number of uncertainties and barriers’, yet assessing the
previous projects is essential to solve this problem. Several models have been developed for the analysis of
software projects. But the classical reference method is the COCOMO model, there are other methods
which are also applied such as Function Point (FP), Line of Code(LOC); meanwhile, the expert`s opinions
matter in this regard. In recent years, the growth and the combination of meta-heuristic algorithms with
high accuracy have brought about a great achievement in software engineering. Meta-heuristic algorithms
which can analyze data from multiple dimensions and identify the optimum solution between them are
analytical tools for the analysis of data. In this paper, we have used the Harmony Search (HS)algorithm for
SCE. The proposed model which is a collection of 60 standard projects from Dataset NASA60 has been
assessed.The experimental results show that HS algorithm is a good way for determining the weight
similarity measures factors of software effort, and reducing the error of MRE.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Elevating Tactical DDD Patterns Through Object Calisthenics
Constraint programming
1.
2. Constraint programming
Integer programming (IP) and mixed integer programming (MIP) have served the operations research (OR) community well for
many years. They have been traditionally used to help organizations make extremely strategic decisions such as, “Should I open
a new refinery at location X or location Y?” to very tactical, yet complex, questions such as, “Which routes should I operate to
minimize my vehicle routing costs?” or “How should a baseball season be scheduled such that all teams have an equal number of
home games?”
Thanks to the advances in IP/MIP solver technology and availability of cheap computing power, the optimization community has
been able to solve most of these questions to near optimality. However, many other questions remain intractable for IP/MIP
formulations because of their computational complexity. Optimization of these problems by nature requires a multi-faceted
approach.
Some classes of optimization problems, such as linear programming models, can be solved by an all-purpose method, but most
problems need individual attention. Typically, the secret to solving a problem is to take advantage of its particular structure. The
result is a proliferation of optimization methods. This imposes an obvious burden on anyone who seeks the right method and
software to solve a given problem. Also, the various disciplines (such as IP, constraint programming, heuristic optimization, etc.)
continue to move in largely separate orbits. This not only imposes the inconvenience of becoming familiar with multiple solvers,
but it passes up the advantages of integrated problem solving.
Recent research has shown that there is much to be gained by exploiting the complementary strengths of different approaches to
optimization. Mathematical programmers are experts at relaxation techniques and polyhedral analysis. Constraint programming
(CP) is distinguished by its inference techniques and modeling power. Rather than choose between these, one would like to have
them both available to attack a given problem. Some problems submit to a single approach, but others benefit from the more
flexible modeling and orders-of-magnitude speedup in computation that can occur when ideas from different fields are combined.
The advantages of integrated methods are being demonstrated in terms of the several problems such as sports tournament
scheduling, just in time (JIT) job scheduling and chemical process optimization that could not be solved easily earlier but can now
be solved in a reasonable timeframe using integrated methods.
3. Need for Integrating IP and CP
CP techniques are good at “inference tasks” that involve reducing the domain of the variables. However, they lack the support of
relaxations that IP has. Moreover, IP methodology also benefits from the extensive use of duality theory. Each technique has its
strong and weak points. It is up to the O.R. practitioner to skillfully combine these techniques in a way that they complement each
other.
Traditionally, scheduling and sequencing problems in the manufacturing sector have been solved using IP. However, a glance at
Pochet’s [Pochet & Wolsey, 2006] standard monograph on IP for scheduling indicates that these problems seldom have a
structure that is favorable. In most cases, the complex business constraints so essential in real-life applications obscure the nice
structure of the bare problem. CP has special constraints that perfectly map to these business constraints, and therefore there are
advantages not only in solving the problem but also in modeling it.
Let’s take an example from the airline industry where there are a certain number of planes arriving at an airport at the same time.
Each of these planes has to go to a different gate. Representing this constraint using IP requires some skill, as we have to look at
each pair of flights and then say that of the pair only one flight can be assigned to a particular gate. However, CP has an “all
different” constraint that is designed to tackle such situations. It simply says that each of these planes has to go to a different gate
– this is as close to plain English as possible.
CP on the other hand suffers from limitations in terms of the number of variables it can handle. Large numbers of variables
present in a constraint make propagation more difficult. This is not only a limitation of the current software that is used for CP but
also a limitation of the methodology in some sense. IP methodology has the ability to handle literally billions of variables through
the use of techniques like column generation. IP techniques also benefit from the concepts of duality and LP relaxations that help
provide best bounds on the solution and thus help us track how far from the goal one is.
Another benefit that IP has over CP currently is its legacy: IP techniques have been around for many more years than CP, and
this has led to the development of robust IP solvers that can solve industry-level problems rapidly. However, with O.R.
practitioners’ interest in CP growing, constraint-based solvers will soon catch up.
How IP and CP combine to produce a more powerful approach
Aside from computational advantages, an integrated approach provides a richer modeling environment that can result in simpler
models and less debugging. The full repertoire of global constraints used in CP is potentially available, as are nonlinear
expressions used in continuous global optimization. Frequent use of metaconstraints not only simplifies the model but also allows
the solver to exploit problem structure. Effective integrated modeling draws from a large library of metaconstraints and
presupposes that the user has some familiarity with this library. For instance, the library may contain a constraint that defines
piecewise linear costs, a constraint that requires flow balance in a network, a constraint that prevents scheduled jobs from
overlapping and so forth. Each constraint is written with parameters that specify the shape of the function, the structure of the
network or the processing times of the jobs. When sitting down to formulate a model, the user would browse the library for
constraints that appear to relate to the problem at hand. Integrated modeling therefore places the burden of identifying problem
structure on the user, and in so doing it takes full advantage of the human capacity for pattern recognition. Users identify highly
structured subsets of constraints, which allow the solver to apply the best-known analysis of these structures to solve the problem
4. efficiently. In addition, only certain metaconstraints tend to occur in a given problem domain. This means that only a relevant
portion of the library must be presented to a practitioner in that domain.
Practical Applications
IP and CP have already been used in an integrated fashion to solve a wide variety of practical problems. In some cases the
results have been dramatic. Problems that could not be solved by IP or CP alone could be solved using an integrated approach.
In other cases there has been a significant reduction in run-time or a huge improvement in solution quality due to an integrated
approach.
One of the first applications of this integrated approach was to schedule Major League Baseball games in the United States. The
business constraints on the sequence of home and away matches made the problem intractable to a purely IP-based approach.
So the problem was split into a “master problem” and a “sub-problem.” IP techniques were used to solve the master problem while
CP was used for the sub-problem. This combined strategy helped to solve the problem involving eight teams for the first time.
Another interesting application is automatic recording of broadcast content. Such a recorder tries to match a given user profile
with the information submitted by the different TV channels. For example, a user may be interested in thrillers, the more recent the
better. The digital video recorder is supposed to record programs such that the user’s satisfaction is maximized. As the number of
channels may be enormous (more than 100 digital channels are possible), a service that automatically provides an individual
selection is highly appreciated. In this context, two restrictions have to be met. First, the storage capacity is limited, and second,
only one video can be recorded at a time. An integrated approach using relaxed solutions from IP along with CP is up to 10 times
faster than MIP, which in turn outperforms pure CP.
Scheduling is one area where CP is known to be stronger than IP. In traditional job-scheduling problems, there is a penalty only
for finishing the job later than the scheduled end time, not for finishing it earlier. However in just in time (JIT) scheduling, jobs that
finish early are also penalized. For this problem, CP consistently outperforms IP. However, combined use of IP-based relaxations
and CP for a class of JIT scheduling problems enabled 67 out of 90 instances to be solved while CP alone could solve only 12.
In another application for call-center scheduling, utilizing CP for the master problem and LP for the sub-problem solved twice as
many instances as the original MIP formulation. Extremely encouraging results were obtained for a Polypropylene batch-
scheduling problem. In this case the roles were reversed, and MIP was used for the master problem while CP was used for the
sub-problem. This approached solved a previously insoluble problem in 10 minutes.
From these practical examples it is apparent that coupling the powerful constraint propagation approach of CP with relaxations
from MIP is fundamentally changing the way practitioners use O.R. to solve problems. One of the key areas where the integrated
approach is adding value is in scheduling problems in hospitals. In particular, the Nurse Scheduling Problem is characterized by
the complexity of its business constraints. In this case, apart from benefits in solution run-time, CP cuts down the model
formulation time significantly. Before CP arrived, modeling this problem in MIP was considered a very difficult task requiring
advanced skills and experience in building models. The CP formulations for this case are quite compact and do not require the
services of very highly skilled O.R. analysts. Ease in modeling also translates into faster development, thereby reducing the to-
market time for O.R. solutions.
5. Soon, O.R. practitioners across industries will start using CP in conjunction with IP/MIP to solve a variety of high-impact
optimization problems such as assortment optimization, sales-force territory alignment and SKU rationalization. A new
methodology, constraint integer programming (CIP), which integrates IP and CP, is also emerging.
Is the Additional Complexity Worth It?
One of the key limitations in using the integrated framework is that the burden of integrating the solvers to some extent still
resides upon the user. Though current commercial packages provide for scripting functionality to connect one type of solver to
another, there is a lack of a truly integrated language that by looking at the formulations would decide by itself the best way to
decompose and solve the problem. Development of such an integrated modeling framework is the need of the hour.
O.R. is more than anything else a practical approach to problem solving. We already know that O.R. problems cannot be solved
by sitting in hallowed academic portals without knowing what happens on the ground. We must steer clear of over-reliance on any
particular technique because each technique has its limitations and we might lose out on what the other technique has to offer. It
is clear that the future belongs to those who smartly use a combination of techniques that complement each other, and CIP is
already showing us the way.