Pareto-Optimal Search-Based Software Engineering (POSBSE): A Literature SurveyAbdel Salam Sayyad
Paper presented at the 2nd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE’13), San Francisco, USA. May 2013.
A review of population initialization techniques for evolutionary algorithmsBorhan Kazimipour
Although various population initialization techniques have been employed in evolutionary algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap and attract more attentions from EA researchers to this crucial yet less explored area, we conduct a systematic review of the existing population initialization techniques. Specifically, we categorize initialization techniques from three exclusive perspectives, i.e., randomness, compositionality and generality. Characteristics of the techniques belonging to each category are carefully analysed to further lead to several sub-categories. We also discuss several open issues related to this research topic, which demands further in-depth investigations.
A novel hybridization of opposition-based learning and cooperative co-evoluti...Borhan Kazimipour
Opposition-based learning (OBL) and cooperative
co-evolution (CC) have demonstrated promising performance when dealing with large-scale global optimization (LSGO) problems. In this work, we propose a novel framework for hybridizing these two techniques, and investigate the performance of simple implementations of this new framework using the most recent LSGO benchmarking test suite. The obtained results verify the effectiveness of our proposed OBL-CC framework. Moreover, some advanced statistical analyses reveal that the proposed hybridization significantly outperforms its component methods in terms of the quality of finally obtained solutions.
Pareto-Optimal Search-Based Software Engineering (POSBSE): A Literature SurveyAbdel Salam Sayyad
Paper presented at the 2nd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE’13), San Francisco, USA. May 2013.
A review of population initialization techniques for evolutionary algorithmsBorhan Kazimipour
Although various population initialization techniques have been employed in evolutionary algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap and attract more attentions from EA researchers to this crucial yet less explored area, we conduct a systematic review of the existing population initialization techniques. Specifically, we categorize initialization techniques from three exclusive perspectives, i.e., randomness, compositionality and generality. Characteristics of the techniques belonging to each category are carefully analysed to further lead to several sub-categories. We also discuss several open issues related to this research topic, which demands further in-depth investigations.
A novel hybridization of opposition-based learning and cooperative co-evoluti...Borhan Kazimipour
Opposition-based learning (OBL) and cooperative
co-evolution (CC) have demonstrated promising performance when dealing with large-scale global optimization (LSGO) problems. In this work, we propose a novel framework for hybridizing these two techniques, and investigate the performance of simple implementations of this new framework using the most recent LSGO benchmarking test suite. The obtained results verify the effectiveness of our proposed OBL-CC framework. Moreover, some advanced statistical analyses reveal that the proposed hybridization significantly outperforms its component methods in terms of the quality of finally obtained solutions.
Design of experiments formulation development exploring the best practices ...Maher Al absi
Now days computer tools used in the formulation and development of pharmaceutical product. Various technique such as design of experiment are implemented for optimization of formulation and processing parameter.
A Model To Compare The Degree Of Refactoring Opportunities Of Three Projects ...acijjournal
Refactoring is applied to the software artifacts so as to improve its internal structure, while preserving its
external behavior. Refactoring is an uncertain process and it is difficult to give some units for
measurement. The amount to refactoring that can be applied to the source-code depends upon the skills of
the developer. In this research, we have perceived refactoring as a quantified object on an ordinal scale of
measurement. We have a proposed a model for determining the degree of refactoring opportunities in the
given source-code. The model is applied on the three projects collected from a company. UML diagrams
are drawn for each project. The values for source-code metrics, that are useful in determining the quality of
code, are calculated for each UML of the projects. Based on the nominal values of metrics, each relevant
UML is represented on an ordinal scale. A machine learning tool, weka, is used to analyze the dataset,
imported in the form of arff file, produced by the three projects
SCHEDULING AND INSPECTION PLANNING IN SOFTWARE DEVELOPMENT PROJECTS USING MUL...ijseajournal
This paper presents a Multi-objective Hyper-heuristic Evolutionary Algorithm (MHypEA) for the solution
of Scheduling and Inspection Planning in Software Development Projects. Scheduling and Inspection
planning is a vital problem in software engineering whose main objective is to schedule the persons to
various activities in the software development process such as coding, inspection, testing and rework in
such a way that the quality of the software product is maximum and at the same time the project make span
and cost of the project are minimum. The problem becomes challenging when the size of the project is
huge. The MHypEA is an effective metaheuristic search technique for suggesting scheduling and inspection
planning. It incorporates twelve low-level heuristics which are based on different methods of selection,
crossover and mutation operations of Evolutionary Algorithms. The selection mechanism to select a lowlevel
heuristic is based on reinforcement learning with adaptive weights. The efficacy of the algorithm has
been studied on randomly generated test problem.
Testing of artificial intelligence; AI quality engineering skils - an introdu...Rik Marselis
Testing of AI will require a new skillset related to interpreting a system’s boundaries or tolerances. Indeed, as our paper points out, the complex functioning of an AI system means, amongst other things, that the focus of testing shifts from output to input to verify a robust solution. Also we introduce the 6 angles of quality for Artificial Intelligence and Robotics.
This paper was written by Humayun Shaukat, Toni Gansel and Rik Marselis.
Software testing effort estimation with cobb douglas function a practical app...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This presentation is about a lecture I gave within the "Software systems and services" immigration course at the Gran Sasso Science Institute, L'Aquila (Italy): http://cs.gssi.it/.
http://www.ivanomalavolta.com
The methods of exploratory testing has gained significant attention in industry and research in the last years. However, as many “buzzword" technologies, the introduction and application of exploratory testing is not straightforward. Exploratory testing it is not only black or white - scripted or exploratory - but also all shades of grey in between. Within the EASE industrial excellence center, we have executed an industrial workshop on exploratory testing, that helps providing understanding of how to choose feasible levels of exploration in exploratory testing. We will present the concepts of levels of exploration in exploratory testing, the outcomes of the workshop, along with relevant empirical research findings on exploratory testing.
Design of experiments formulation development exploring the best practices ...Maher Al absi
Now days computer tools used in the formulation and development of pharmaceutical product. Various technique such as design of experiment are implemented for optimization of formulation and processing parameter.
A Model To Compare The Degree Of Refactoring Opportunities Of Three Projects ...acijjournal
Refactoring is applied to the software artifacts so as to improve its internal structure, while preserving its
external behavior. Refactoring is an uncertain process and it is difficult to give some units for
measurement. The amount to refactoring that can be applied to the source-code depends upon the skills of
the developer. In this research, we have perceived refactoring as a quantified object on an ordinal scale of
measurement. We have a proposed a model for determining the degree of refactoring opportunities in the
given source-code. The model is applied on the three projects collected from a company. UML diagrams
are drawn for each project. The values for source-code metrics, that are useful in determining the quality of
code, are calculated for each UML of the projects. Based on the nominal values of metrics, each relevant
UML is represented on an ordinal scale. A machine learning tool, weka, is used to analyze the dataset,
imported in the form of arff file, produced by the three projects
SCHEDULING AND INSPECTION PLANNING IN SOFTWARE DEVELOPMENT PROJECTS USING MUL...ijseajournal
This paper presents a Multi-objective Hyper-heuristic Evolutionary Algorithm (MHypEA) for the solution
of Scheduling and Inspection Planning in Software Development Projects. Scheduling and Inspection
planning is a vital problem in software engineering whose main objective is to schedule the persons to
various activities in the software development process such as coding, inspection, testing and rework in
such a way that the quality of the software product is maximum and at the same time the project make span
and cost of the project are minimum. The problem becomes challenging when the size of the project is
huge. The MHypEA is an effective metaheuristic search technique for suggesting scheduling and inspection
planning. It incorporates twelve low-level heuristics which are based on different methods of selection,
crossover and mutation operations of Evolutionary Algorithms. The selection mechanism to select a lowlevel
heuristic is based on reinforcement learning with adaptive weights. The efficacy of the algorithm has
been studied on randomly generated test problem.
Testing of artificial intelligence; AI quality engineering skils - an introdu...Rik Marselis
Testing of AI will require a new skillset related to interpreting a system’s boundaries or tolerances. Indeed, as our paper points out, the complex functioning of an AI system means, amongst other things, that the focus of testing shifts from output to input to verify a robust solution. Also we introduce the 6 angles of quality for Artificial Intelligence and Robotics.
This paper was written by Humayun Shaukat, Toni Gansel and Rik Marselis.
Software testing effort estimation with cobb douglas function a practical app...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This presentation is about a lecture I gave within the "Software systems and services" immigration course at the Gran Sasso Science Institute, L'Aquila (Italy): http://cs.gssi.it/.
http://www.ivanomalavolta.com
The methods of exploratory testing has gained significant attention in industry and research in the last years. However, as many “buzzword" technologies, the introduction and application of exploratory testing is not straightforward. Exploratory testing it is not only black or white - scripted or exploratory - but also all shades of grey in between. Within the EASE industrial excellence center, we have executed an industrial workshop on exploratory testing, that helps providing understanding of how to choose feasible levels of exploration in exploratory testing. We will present the concepts of levels of exploration in exploratory testing, the outcomes of the workshop, along with relevant empirical research findings on exploratory testing.
Benchmarking languages for evolutionary computationJuan J. Merelo
A poster presented at ECTA/IJCCI 2016 with our research on evolutionary algorithms. Paper sources and data at https://github.com/geneura-papers/2016-ea-languages-PPSN/releases/tag/v1.0ECTA
Machine Learning Model Validation (Aijun Zhang 2024).pdfAijun Zhang
Developing an effective AI/ML model risk management program, with topics covering
- Understanding machine learning lifecycle in banking
- Understanding key elements of machine learning model validation
- Testing modules for conceptual soundness
- Testing modules for outcome analysis
- Developing inherently interpretable benchmark models
- Developing the automated pipeline for streamlined validation
- Enabling automated validation and monitoring for dynamically updating models
This is the Dissertation Part-I in support of my intended research work. It has presentation in support of my research methodology, timelines and expected results
Yusuke Goto (iwate Pref. Univ.) and Shingo Takahashi (Waseda Univ.)
How Scenario Analysis Can Contribute to ABMS Validation
The 7th International Workshop on Agent-based Approaches in Economic and Social Complex Systems
January 17, 2012 (Osaka, Japan)
Online performance modeling and analysis of message-passing parallel applicat...MOCA Platform
Although the evolution of hardware is improving at an incredible rate, the advances in
parallel software have been hampered for many reasons. Developing an efficient parallel
application is still not an easy task. Our thesis is that many performance problems and their reasons can be quickly located and explained with automated techniques that work on unmodified parallel applications. This work identifies main obstacles for such diagnosis and presents a two-step approach for addressing them. In this approach, the application is automatically modeled and diagnosed during its execution.
First, we introduce an online performance modeling technique that enables automated discovery of causal execution flows through communication and computational activities in message-passing parallel programs. Second, we present a systematic approach to online performance analysis. The automated
analysis uses online model to quickly identify the most important performance problems,
and correlate them with application source code. Our technique is able to discover causal
dependences between the problems, infer their root causes in some scenarios and explain
them to developers. In this work, we focus on diagnosing scientific MPI parallel applications and their communication and computational problems although the approach can be extended to support other classes of activities and programming models.
We have evaluated our approach on a variety of scientific parallel applications. In all scenarios, our online performance modeling technique proved effective for low-overhead capturing of program’s behavior and facilitated performance understanding. With our automated, model-based performance analysis approach, we were able to easily identify the most severe performance problems during application execution, and locate their root causes without previous knowledge of application internals.
Testing Neural Program Analyzers (ASE-LBR 2019)Rafiqul Rabin
Testing Neural Program Analyzers. Md Rafiqul Islam Rabin, Ke Wang, Mohammad Amin Alipour. 34th IEEE/ACM International Conference on Automated Software Engineering (ASE 2019). Late Breaking Results-Track. San Diego, CA, November 2019.
arXiv: https://arxiv.org/abs/1908.10711
GitHub: https://github.com/mdrafiqulrabin/tnpa-framework
Similar to Influence of the population structure on the performance of an Agent-Based Evolutionary algorithm (20)
Como triunfar con tu proyecto en un hackatónJuan J. Merelo
Guía para los proyectos participantes en el hackatón de proyectos de la UGR, donde explicamos qué hacer para atraer colaboradores en el hackatón y, si es posible, conservarlos
Introducción a HDR y Tonemapping con LuminanceJuan J. Merelo
Una breve introducción al tratamiento de imágenes HDR con esta herramienta. Desde tonemapping con una sola imagen hasta creación de imágenes HDR mediante bracketing
Enforcing Corporate Security Policies via Computational Intelligence TechniquesJuan J. Merelo
Paper presented at the SecDef workshop @GECCO 2014, by Enforcing Corporate Security Policies via Computational Intelligence Techniques
Antonio Moral is the main author of the presentation
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...NelTorrente
In this research, it concludes that while the readiness of teachers in Caloocan City to implement the MATATAG Curriculum is generally positive, targeted efforts in professional development, resource distribution, support networks, and comprehensive preparation can address the existing gaps and ensure successful curriculum implementation.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Influence of the population structure on the performance of an Agent-Based Evolutionary algorithm
1. Introduction
Model Design
The Evolvable
Agent
Experimental
Analysis
Influence of the Population Structure on the
Goals
Methodology
Analysis of
Performance of an Agent-based Evolutionary
Results
Conclusions
Algorithm
Conclusions
Future Works
J.L.J. Laredo et al.
Dpto. Arquitectura y Tecnolog´ de Computadores
ıa
Universidad de Granada
11-Sept-2010
1 / 18
2. Scope
Introduction
Model Design
The Evolvable
Agent
Experimental
Analysis
Goals • Status: Peer-to-Peer Evolutionary Computation (P2P EC)
Methodology
Analysis of
Results
represents a parallel solution for hard problems
Conclusions optimization
Conclusions
Future Works
• Modelling: Fine grained parallel EA using a P2P protocol
as underlying population structure
• Objective: Comparison of different population structures
on the EA performance
2 / 18
3. Outline
Introduction
Model Design
The Evolvable
Agent
1 Introduction
Experimental
Analysis 2 Model Design
Goals
Methodology The Evolvable Agent
Analysis of
Results
Conclusions 3 Experimental Analysis
Conclusions
Goals
Future Works
Methodology
Analysis of Results
4 Conclusions
Conclusions
5 Future Works
3 / 18
4. Introduction
Introduction
Model Design
The Evolvable
Agent
Experimental P2P EC
Analysis
Goals • Virtualization:
Methodology
Analysis of Single view at
Results
Conclusions
application level
Conclusions
• Decentralization:
Future Works
No central
management
• Massive Scalability:
Up to thousands of
computers
4 / 18
5. Population Structure as a complex network
Introduction
Panmictic Small-world Regular lattice
Model Design
The Evolvable
Agent
Experimental
Analysis
Goals
Methodology
Analysis of
Results
Conclusions
Conclusions
Future Works
5 / 18
6. Population Structure as a complex network
Introduction
Panmictic Small-world Regular lattice
Model Design
The Evolvable
Agent
Experimental
Analysis
Goals
Methodology
Analysis of
Results
Conclusions
Conclusions
Future Works
5 / 18
7. Population Structure as a complex network
Introduction
Panmictic Small-world Regular lattice
Model Design
The Evolvable
Agent
Experimental
Analysis
Goals
Methodology
Analysis of
Results
Conclusions
Conclusions
Future Works
5 / 18
8. Population Structure as a complex network
Introduction
Panmictic Small-world Regular lattice
Model Design
The Evolvable
Agent
Experimental
Analysis
Goals
Methodology
Analysis of
Results n(n−1)
2
log(n) n
Conclusions
Conclusions
Future Works
5 / 18
9. Outline
Introduction
Model Design
The Evolvable
Agent
1 Introduction
Experimental
Analysis 2 Model Design
Goals
Methodology The Evolvable Agent
Analysis of
Results
Conclusions 3 Experimental Analysis
Conclusions
Goals
Future Works
Methodology
Analysis of Results
4 Conclusions
Conclusions
5 Future Works
6 / 18
10. The Evolvable Agent Model
Introduction
Model Design Design principles
The Evolvable
Agent • Agent based approach
Experimental
Analysis
• Fine grain parallelization
Goals • Spatially structured EA
Methodology
Analysis of • Local selection
Results
Conclusions
Conclusions
Future Works
7 / 18
11. The Evolvable Agent Model
Introduction
Model Design Design principles
The Evolvable
Agent • Agent based approach
Experimental
Analysis
• Fine grain parallelization
Goals • Spatially structured EA
Methodology
Analysis of • Local selection
Results
Conclusions
Conclusions
Future Works
7 / 18
12. Outline
Introduction
Model Design
The Evolvable
Agent
1 Introduction
Experimental
Analysis 2 Model Design
Goals
Methodology The Evolvable Agent
Analysis of
Results
Conclusions 3 Experimental Analysis
Conclusions
Goals
Future Works
Methodology
Analysis of Results
4 Conclusions
Conclusions
5 Future Works
8 / 18
13. Goals and Test-Cases
Introduction
Model Design
The Evolvable
Agent
Experimental Goal
Analysis
Goals • Comparison of performances using different population
Methodology
Analysis of
Results
structures
Conclusions
Conclusions
Ring Watts-Strogatz Newscast
Future Works
9 / 18
14. Outline
Introduction
Model Design
The Evolvable
Agent
1 Introduction
Experimental
Analysis 2 Model Design
Goals
Methodology The Evolvable Agent
Analysis of
Results
Conclusions 3 Experimental Analysis
Conclusions
Goals
Future Works
Methodology
Analysis of Results
4 Conclusions
Conclusions
5 Future Works
10 / 18
15. Experimental settings
Introduction
Model Design
The Evolvable
Agent
Experimental
Analysis • 2-Trap. L=12...60
Goals
Methodology • Population size
Analysis of
Results • Estimated by bisection
Conclusions • Selectorecombinative
Conclusions
Future Works
GA (Mutation less)
• Minimum population
size able to reach 0.98
of SR
• Uniform Crossover
• Binary Tournament
11 / 18
16. Outline
Introduction
Model Design
The Evolvable
Agent
1 Introduction
Experimental
Analysis 2 Model Design
Goals
Methodology The Evolvable Agent
Analysis of
Results
Conclusions 3 Experimental Analysis
Conclusions
Goals
Future Works
Methodology
Analysis of Results
4 Conclusions
Conclusions
5 Future Works
12 / 18
17. Population Structure
Introduction
Model Design
The Evolvable
Agent
Experimental Settings
Analysis
Goals Problem instance: 2-trap
Methodology
Analysis of
Results
Pop. Size: Tuning Algorithm
Conclusions No Mutation
Conclusions
Future Works
13 / 18
18. Population Structure
Introduction
Model Design Settings
The Evolvable
Agent
Problem instance: L=60 2-trap
Experimental
Analysis Pop. Size: 135
Goals
Methodology
Max. Eval: 5535
1
Analysis of
Results Mutation: Bit-flip Pm = L
Conclusions
Conclusions
Future Works
14 / 18
19. Conclusions
Introduction
Model Design
The Evolvable
Agent
Experimental
Analysis
Goals • Regular lattices require of smaller population sizes
Methodology
Analysis of
Results
... BUT a bigger number of evaluations to find a solution.
Conclusions • Different small-world methods produce an equivalent
Conclusions
Future Works
performance
...That’s good! Many P2P protocol are designed to work
as small-world networks
(i.e. Interoperability/Migration between P2P platforms)
15 / 18
20. Future Works
Introduction
Model Design
The Evolvable
Agent
Experimental
Analysis
Goals
Methodology
Analysis of
Results • Validation of the model in a real P2P infrastructure
Conclusions
Conclusions
• Exploration of other P2P protocols as population
Future Works structures
• Extension of the P2P concept to other metaheuristics
16 / 18