This document outlines Ali Ouni's Ph.D. defense presentation on recommending software refactoring using mono-objective and multi-objective approaches. The presentation includes the following key points:
1. It provides context on the need for automated software refactoring recommendation systems to address challenges in manually refactoring code.
2. It describes Ouni's research methodology which involves detecting code smells, generating refactoring recommendations using mono-objective and multi-objective search-based techniques, and evaluating the approaches.
3. It covers code smell detection including generating detection rules using genetic programming from code smell examples, and evaluating the detection approach on several systems.
4. It outlines the presentation including discussing
Who Should Review My Code? A file-location based code-reviewer recommendation approach for modern code review.
This research study is presented at the 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER2015)
Find more information and preprint at patanamon.com
Who Should Review My Code? A file-location based code-reviewer recommendation approach for modern code review.
This research study is presented at the 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER2015)
Find more information and preprint at patanamon.com
Revisiting Code Ownership and Its Relationship with Software Quality in the S...The University of Adelaide
This work was presented at The 38th International Conference on Software Engineering (ICSE2016).
Abstract: Code ownership establishes a chain of responsibility for modules in large software systems. Although prior work uncovers a link between code ownership heuristics and software quality, these heuristics rely solely on the authorship of code changes. In addition to authoring code changes, developers also make important contributions to a module by reviewing code changes. Indeed, recent work shows that reviewers are highly active in modern code review processes, often suggesting alternative solutions or providing updates to the code changes. In this paper, we complement traditional code ownership heuristics using code review activity. Through a case study of six releases of the large Qt and OpenStack systems, we find that: (1) 67%-86% of developers did not author any code changes for a module, but still actively contributed by reviewing 21%-39% of the code changes, (2) code ownership heuristics that are aware of reviewing activity share a relationship with software quality, and (3) the proportion of reviewers without expertise shares a strong, increasing relationship with the likelihood of having post-release defects. Our results suggest that reviewing activity captures an important aspect of code ownership, and should be included in approximations of it in future studies.
Ph.D. Thesis Defense: Studying Reviewer Selection and Involvement in Modern ...The University of Adelaide
Patanamon's Ph.D. thesis defense at Graduate School of Infomation Science, Nara Institute of Science and Technology, Japan. The thesis title is Studying Reviewer Selection and Involvement in Modern Code Review Processes. This presentation takes 20 minutes.
Code review is one of the crucial software activities where developers and stakeholders collaborate with each other in order to assess software changes. Since code review processes act as a final gate for new software changes to be integrated into the software product, an intense collaboration is necessary in order to prevent defects and produce a high quality of software products. Recently, code review analytics has been implemented in projects (for example, StackAnalytics4 of the OpenStack project) to monitor the collaboration activities between developers and stakeholders in the code review processes. Yet, due to the large volume of software data, code review analytics can only report a static summary (e.g., counting), while neither insights nor instant suggestions are provided. Hence, to better gain valuable insights from software data and help software projects make a better decision, we conduct an empirical investigation using statistical approaches. In particular, we use the large-scale data of 196,712 reviews spread across the Android, Qt, and OpenStack open source projects to train a prediction model in order to uncover the relationship between the characteristics of software changes and the likelihood of having poor code review collaborations. We extract 20 patch characteristics which are grouped along five dimensions, i.e., software changes properties, review participation history, past involvement of a code author, past involvement of reviewers, and review environment dimensions. To validate our findings, we use the bootstrap technique which repeats the experiment 1,000 times. Due to the large volume of studied data, and an intensive computation of characteristic extraction and find- ing validation, the use of the High-Performance-Computing (HPC) re- sources is mandatory to expedite the analysis and generate insights in a timely manner. Through our case study, we find that the amount of review participation in the past and the description length of software changes are a significant indicator that new software changes will suffer from poor code review collaborations [2017]. Moreover, we find that the purpose of introducing new features can increase the likelihood that new software changes will receive late collaboration from reviewers. Our findings highlight the need for the policies of software change submission that monitor these characteristics in order to help software projects improve the quality of code reviews processes. Moreover, based on our findings, future work should develop real-time code review analytics implemented on HPC resources in order to instantly provide insights and suggestions to software projects
Review Participation in Modern Code Review: An Empirical Study of the Android...The University of Adelaide
This work empirically investigates the factors influence review participation in the MCR process. Through a case study of the Android, Qt, and OpenStack open source projects, we find that the amount of review participation in the past is a significant indicator of patches that will suffer from poor review participation. Moreover, the description length of a patch and the purpose of introducing new features also share a relationship with the likelihood of receiving poor review participation.
This full article of this work is published in the Empirical Software Engineering journal. Available online at http://dx.doi.org/10.1007/s10664-016-9452-6
This research study is presented at the 7th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE2014)
Abstract: Effectively performing code review increases the quality of software and reduces occurrence of defects. However, this requires reviewers with experiences and deep understandings of system code. Manual selection of such reviewers can be a costly and time-consuming task. To reduce this cost, we propose a reviewer recommendation algorithm determining file path similarity called FPS algorithm. Using three OSS projects as case studies, FPS algorithm was accurate up to 77.97%, which significantly outperformed the previous
approach.
Find more information and preprint at patanamon.com
Adoption of Software Testing in Open Source Projects - A Preliminary Study on...Pavneet Singh Kochhar
In this study, we explore 50,000 projects and investigate
the correlation between the presence of test cases and various project development characteristics, including the lines of code and the size of development teams.
This research is presented at the 12th Working Conference on Mining Software Repositories (MSR2015)
Abstract: Software code review is a well-established software quality practice. Recently, Modern Code Review (MCR) has been widely adopted in both open source and industrial projects. To evaluate the impact that characteristics of MCR practices have on software quality, this paper comparatively studies MCR practices in defective and clean source code files. We investigate defective files along two perspectives: 1) files that will eventually have defects (i.e., future-defective files) and 2) files that have historically been defective (i.e., risky files). Through an empirical study of 11,736 reviews of changes to 24,486 files from the Qt open source system, we find that both future-defective files and risky files tend to be reviewed less rigorously than their clean counterparts. We also find that the concerns addressed during the code reviews of both defective and clean files tend to enhance evolvability, i.e., ease future maintenance (like documentation), rather than focus on functional issues (like incorrect program logic). Our findings suggest that although functionality concerns are rarely addressed during code review, the rigor of the reviewing process that is applied to a source code file throughout a development cycle shares a link with its defect proneness.
Software analytics (for software quality purpose) is a statistical or machine learning classifier that is trained to identify defect-prone software modules. The goal of software analytics is to help software engineers prioritize their software testing effort on the most-risky modules and understand past pitfalls that lead to defective code. While the adoption of software analytics enables software organizations to distil actionable insights, there are still many barriers to broad and successful adoption of such analytics systems. Indeed, even if software organizations can access such invaluable software artifacts and toolkits for data analytics, researchers and practitioners often have little knowledge to properly develop analytics systems. Thus, the accuracy of the predictions and the insights that are derived from analytics systems is one of the most important challenges of data science in software engineering.
In this work, we conduct a series of empirical investigation to better understand the impact of experimental components (i.e., class mislabelling, parameter optimization of classification techniques, and model validation techniques) on the performance and interpretation of software analytics. To accelerate a large amount of compute-intensive experiment, we leverage the High-Performance-Computing (HPC) resources of Centre for Advanced Computing (CAC) from Queen’s University, Canada. Through case studies of systems that span both proprietary and open- source domains, we demonstrate that (1) realistic noise does not impact the precision of software analytics; (2) automated parameter optimization for classification techniques substantially improve the performance and stability of software analytics; and (3) the out-of- sample bootstrap validation technique produces a good balance between bias and variance of performance estimates. Our results lead us to conclude that the experimental components of analytics modelling impact the predictions and associated insights that are derived from software analytics. Empirical investigations on the impact of overlooked experimental components are needed to derive practical guidelines for analytics modelling.
Cross-project Defect Prediction Using A Connectivity-based Unsupervised Class...Feng Zhang
Defect prediction on projects with limited historical data has attracted great interest from both researchers and practitioners. Cross-project defect prediction has been the main area of progress by reusing classifiers from other projects. However, existing approaches require some degree of homogeneity (e.g., a similar distribution of metric values) between the training projects and the target project. Satisfying the homogeneity requirement often requires significant effort (currently a very active area of research).
An unsupervised classifier does not require any training data, therefore the heterogeneity challenge is no longer an issue. In this paper, we examine two types of unsupervised classifiers: a) distance-based classifiers (e.g., k-means); and b) connectivity-based classifiers. While distance-based unsupervised classifiers have been previously used in the defect prediction literature with disappointing performance, connectivity-based classifiers have never been explored before in our community.
We compare the performance of unsupervised classifiers versus supervised classifiers using data from 26 projects from three publicly available datasets (i.e., AEEEM, NASA, and PROMISE). In the cross-project setting, our proposed connectivity-based classifier (via spectral clustering) ranks as one of the top classifiers among five widely-used supervised classifiers (i.e., random forest, naive Bayes, logistic regression, decision tree, and logistic model tree) and five unsupervised classifiers (i.e., k-means, partition around medoids, fuzzy C-means, neural-gas, and spectral clustering). In the within-project setting (i.e., models are built and applied on the same project), our spectral classifier ranks in the second tier, while only random forest ranks in the first tier. Hence, connectivity-based unsupervised classifiers offer a viable solution for cross and within project defect predictions.
Data collection for software defect predictionAmmAr mobark
It is one of the important stages that software companies need it, it will be after produce the program and published, to know the reactions of the users and their impressions about the program and work on developing and improving it.
The Contents
* BACKGROUND AND RELATED WORK
* EXPERIMENTAL PLANNING
-Research Goal -Research Questions -Experimental Subjects
-Experimental Material -Tasks and Methods
-Experimental Design
عمار عبد الكريم صاحب مبارك
AmmAr Abdualkareem sahib mobark
An Empirical Study of Adoption of Software Testing in Open Source ProjectsPavneet Singh Kochhar
We study more than 20,000 non-trivial software
projects and explore the correlation of test cases with various
project development characteristics including: project size,
development team size, number of bugs, number of bug
reporters, and the programming languages of these projects.
Comparison between Test-Driven Development and Conventional Development: A Ca...IJERA Editor
In Software Engineering, different techniques and approaches are being used nowadays to produce reliable
software. The software quality relies heavily on the software testing. However, not all developers are concerned
with the testing stage of a software. This has affected the software quality and has increased the cost as well. To
avoid these issues, researchers paid a lot of effort on finding the best technique that guarantee the software
quality. In this paper we aim to explore the effectiveness of building test cases using Test-Driven Development
(TDD) technique compared with the conventional technique (Test-last). The comparison measures the
effectiveness of test cases with regard to number of defects, code coverage and test cases development duration
between TDD and Test-Last. The results has been analyzes and presented to support the best technique. On an
average, the effectiveness of test cases with regards to the selected quality factors in Test-Driven Development
(TDD) was better than the conventional technique (Test-last). TDD and conventional testing had nearly the
same percentage as result in code coverage. Moreover, the number of defects found and the test cases
development duration spent in TDD are high compared with Test-Last. The results led to suggest some
contributions and achievement that could be gained from applying TDD technique in software industry. As
using TDD as development technique in young companies can produce high quality software in less time.
DevOps is a term for a combination of various software development practices including traditional software development and information technology operations. It shortens the systems development life cycle while delivering features, fixes, and updates. This is ensured by frequent and close alignments with business objectives. It comprises a vast set of cultural philosophies, practices and tools
to increase an organization's ability to deliver applications and services at high velocity.
This document gives insights how DevOps should be designed, what services they should offer, what organizational forms can be chosen (incl. their benefits), which aspects a DevOps governance should cover, how to assess and implement DevOps (DevOps transition), which technologies are important and how processes can be designed based on proven best practices.
Agenda DevOps best practice slide deck:
- DevOps Definition and Overview
- DevOps & Agile maturity
- DevOps Transition
- DevOps Technology
- DevOps Organization
Revisiting Code Ownership and Its Relationship with Software Quality in the S...The University of Adelaide
This work was presented at The 38th International Conference on Software Engineering (ICSE2016).
Abstract: Code ownership establishes a chain of responsibility for modules in large software systems. Although prior work uncovers a link between code ownership heuristics and software quality, these heuristics rely solely on the authorship of code changes. In addition to authoring code changes, developers also make important contributions to a module by reviewing code changes. Indeed, recent work shows that reviewers are highly active in modern code review processes, often suggesting alternative solutions or providing updates to the code changes. In this paper, we complement traditional code ownership heuristics using code review activity. Through a case study of six releases of the large Qt and OpenStack systems, we find that: (1) 67%-86% of developers did not author any code changes for a module, but still actively contributed by reviewing 21%-39% of the code changes, (2) code ownership heuristics that are aware of reviewing activity share a relationship with software quality, and (3) the proportion of reviewers without expertise shares a strong, increasing relationship with the likelihood of having post-release defects. Our results suggest that reviewing activity captures an important aspect of code ownership, and should be included in approximations of it in future studies.
Ph.D. Thesis Defense: Studying Reviewer Selection and Involvement in Modern ...The University of Adelaide
Patanamon's Ph.D. thesis defense at Graduate School of Infomation Science, Nara Institute of Science and Technology, Japan. The thesis title is Studying Reviewer Selection and Involvement in Modern Code Review Processes. This presentation takes 20 minutes.
Code review is one of the crucial software activities where developers and stakeholders collaborate with each other in order to assess software changes. Since code review processes act as a final gate for new software changes to be integrated into the software product, an intense collaboration is necessary in order to prevent defects and produce a high quality of software products. Recently, code review analytics has been implemented in projects (for example, StackAnalytics4 of the OpenStack project) to monitor the collaboration activities between developers and stakeholders in the code review processes. Yet, due to the large volume of software data, code review analytics can only report a static summary (e.g., counting), while neither insights nor instant suggestions are provided. Hence, to better gain valuable insights from software data and help software projects make a better decision, we conduct an empirical investigation using statistical approaches. In particular, we use the large-scale data of 196,712 reviews spread across the Android, Qt, and OpenStack open source projects to train a prediction model in order to uncover the relationship between the characteristics of software changes and the likelihood of having poor code review collaborations. We extract 20 patch characteristics which are grouped along five dimensions, i.e., software changes properties, review participation history, past involvement of a code author, past involvement of reviewers, and review environment dimensions. To validate our findings, we use the bootstrap technique which repeats the experiment 1,000 times. Due to the large volume of studied data, and an intensive computation of characteristic extraction and find- ing validation, the use of the High-Performance-Computing (HPC) re- sources is mandatory to expedite the analysis and generate insights in a timely manner. Through our case study, we find that the amount of review participation in the past and the description length of software changes are a significant indicator that new software changes will suffer from poor code review collaborations [2017]. Moreover, we find that the purpose of introducing new features can increase the likelihood that new software changes will receive late collaboration from reviewers. Our findings highlight the need for the policies of software change submission that monitor these characteristics in order to help software projects improve the quality of code reviews processes. Moreover, based on our findings, future work should develop real-time code review analytics implemented on HPC resources in order to instantly provide insights and suggestions to software projects
Review Participation in Modern Code Review: An Empirical Study of the Android...The University of Adelaide
This work empirically investigates the factors influence review participation in the MCR process. Through a case study of the Android, Qt, and OpenStack open source projects, we find that the amount of review participation in the past is a significant indicator of patches that will suffer from poor review participation. Moreover, the description length of a patch and the purpose of introducing new features also share a relationship with the likelihood of receiving poor review participation.
This full article of this work is published in the Empirical Software Engineering journal. Available online at http://dx.doi.org/10.1007/s10664-016-9452-6
This research study is presented at the 7th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE2014)
Abstract: Effectively performing code review increases the quality of software and reduces occurrence of defects. However, this requires reviewers with experiences and deep understandings of system code. Manual selection of such reviewers can be a costly and time-consuming task. To reduce this cost, we propose a reviewer recommendation algorithm determining file path similarity called FPS algorithm. Using three OSS projects as case studies, FPS algorithm was accurate up to 77.97%, which significantly outperformed the previous
approach.
Find more information and preprint at patanamon.com
Adoption of Software Testing in Open Source Projects - A Preliminary Study on...Pavneet Singh Kochhar
In this study, we explore 50,000 projects and investigate
the correlation between the presence of test cases and various project development characteristics, including the lines of code and the size of development teams.
This research is presented at the 12th Working Conference on Mining Software Repositories (MSR2015)
Abstract: Software code review is a well-established software quality practice. Recently, Modern Code Review (MCR) has been widely adopted in both open source and industrial projects. To evaluate the impact that characteristics of MCR practices have on software quality, this paper comparatively studies MCR practices in defective and clean source code files. We investigate defective files along two perspectives: 1) files that will eventually have defects (i.e., future-defective files) and 2) files that have historically been defective (i.e., risky files). Through an empirical study of 11,736 reviews of changes to 24,486 files from the Qt open source system, we find that both future-defective files and risky files tend to be reviewed less rigorously than their clean counterparts. We also find that the concerns addressed during the code reviews of both defective and clean files tend to enhance evolvability, i.e., ease future maintenance (like documentation), rather than focus on functional issues (like incorrect program logic). Our findings suggest that although functionality concerns are rarely addressed during code review, the rigor of the reviewing process that is applied to a source code file throughout a development cycle shares a link with its defect proneness.
Software analytics (for software quality purpose) is a statistical or machine learning classifier that is trained to identify defect-prone software modules. The goal of software analytics is to help software engineers prioritize their software testing effort on the most-risky modules and understand past pitfalls that lead to defective code. While the adoption of software analytics enables software organizations to distil actionable insights, there are still many barriers to broad and successful adoption of such analytics systems. Indeed, even if software organizations can access such invaluable software artifacts and toolkits for data analytics, researchers and practitioners often have little knowledge to properly develop analytics systems. Thus, the accuracy of the predictions and the insights that are derived from analytics systems is one of the most important challenges of data science in software engineering.
In this work, we conduct a series of empirical investigation to better understand the impact of experimental components (i.e., class mislabelling, parameter optimization of classification techniques, and model validation techniques) on the performance and interpretation of software analytics. To accelerate a large amount of compute-intensive experiment, we leverage the High-Performance-Computing (HPC) resources of Centre for Advanced Computing (CAC) from Queen’s University, Canada. Through case studies of systems that span both proprietary and open- source domains, we demonstrate that (1) realistic noise does not impact the precision of software analytics; (2) automated parameter optimization for classification techniques substantially improve the performance and stability of software analytics; and (3) the out-of- sample bootstrap validation technique produces a good balance between bias and variance of performance estimates. Our results lead us to conclude that the experimental components of analytics modelling impact the predictions and associated insights that are derived from software analytics. Empirical investigations on the impact of overlooked experimental components are needed to derive practical guidelines for analytics modelling.
Cross-project Defect Prediction Using A Connectivity-based Unsupervised Class...Feng Zhang
Defect prediction on projects with limited historical data has attracted great interest from both researchers and practitioners. Cross-project defect prediction has been the main area of progress by reusing classifiers from other projects. However, existing approaches require some degree of homogeneity (e.g., a similar distribution of metric values) between the training projects and the target project. Satisfying the homogeneity requirement often requires significant effort (currently a very active area of research).
An unsupervised classifier does not require any training data, therefore the heterogeneity challenge is no longer an issue. In this paper, we examine two types of unsupervised classifiers: a) distance-based classifiers (e.g., k-means); and b) connectivity-based classifiers. While distance-based unsupervised classifiers have been previously used in the defect prediction literature with disappointing performance, connectivity-based classifiers have never been explored before in our community.
We compare the performance of unsupervised classifiers versus supervised classifiers using data from 26 projects from three publicly available datasets (i.e., AEEEM, NASA, and PROMISE). In the cross-project setting, our proposed connectivity-based classifier (via spectral clustering) ranks as one of the top classifiers among five widely-used supervised classifiers (i.e., random forest, naive Bayes, logistic regression, decision tree, and logistic model tree) and five unsupervised classifiers (i.e., k-means, partition around medoids, fuzzy C-means, neural-gas, and spectral clustering). In the within-project setting (i.e., models are built and applied on the same project), our spectral classifier ranks in the second tier, while only random forest ranks in the first tier. Hence, connectivity-based unsupervised classifiers offer a viable solution for cross and within project defect predictions.
Data collection for software defect predictionAmmAr mobark
It is one of the important stages that software companies need it, it will be after produce the program and published, to know the reactions of the users and their impressions about the program and work on developing and improving it.
The Contents
* BACKGROUND AND RELATED WORK
* EXPERIMENTAL PLANNING
-Research Goal -Research Questions -Experimental Subjects
-Experimental Material -Tasks and Methods
-Experimental Design
عمار عبد الكريم صاحب مبارك
AmmAr Abdualkareem sahib mobark
An Empirical Study of Adoption of Software Testing in Open Source ProjectsPavneet Singh Kochhar
We study more than 20,000 non-trivial software
projects and explore the correlation of test cases with various
project development characteristics including: project size,
development team size, number of bugs, number of bug
reporters, and the programming languages of these projects.
Comparison between Test-Driven Development and Conventional Development: A Ca...IJERA Editor
In Software Engineering, different techniques and approaches are being used nowadays to produce reliable
software. The software quality relies heavily on the software testing. However, not all developers are concerned
with the testing stage of a software. This has affected the software quality and has increased the cost as well. To
avoid these issues, researchers paid a lot of effort on finding the best technique that guarantee the software
quality. In this paper we aim to explore the effectiveness of building test cases using Test-Driven Development
(TDD) technique compared with the conventional technique (Test-last). The comparison measures the
effectiveness of test cases with regard to number of defects, code coverage and test cases development duration
between TDD and Test-Last. The results has been analyzes and presented to support the best technique. On an
average, the effectiveness of test cases with regards to the selected quality factors in Test-Driven Development
(TDD) was better than the conventional technique (Test-last). TDD and conventional testing had nearly the
same percentage as result in code coverage. Moreover, the number of defects found and the test cases
development duration spent in TDD are high compared with Test-Last. The results led to suggest some
contributions and achievement that could be gained from applying TDD technique in software industry. As
using TDD as development technique in young companies can produce high quality software in less time.
DevOps is a term for a combination of various software development practices including traditional software development and information technology operations. It shortens the systems development life cycle while delivering features, fixes, and updates. This is ensured by frequent and close alignments with business objectives. It comprises a vast set of cultural philosophies, practices and tools
to increase an organization's ability to deliver applications and services at high velocity.
This document gives insights how DevOps should be designed, what services they should offer, what organizational forms can be chosen (incl. their benefits), which aspects a DevOps governance should cover, how to assess and implement DevOps (DevOps transition), which technologies are important and how processes can be designed based on proven best practices.
Agenda DevOps best practice slide deck:
- DevOps Definition and Overview
- DevOps & Agile maturity
- DevOps Transition
- DevOps Technology
- DevOps Organization
Explore the benefits of a collaborative DevOps approach and learn how to implement DevOps in your organization. Discover DevOps best practices every developer should know.
The DevOps Training Program will furnish you with in-depth knowledge on different DevOps tools like Jenkins, Docker, Git, Maven, ANT, Ansible, Selenium, Jira, Vagrant, Kubernetes and Nagios. This training is totally involved and structured in a manner to assist you with turning into a guaranteed DevOps Engineer through best practices in Continuous Development, Continuous Testing, Configuration Management and Continuous Integration, lastly, Continuous Monitoring of software project development life cycle.
DevOps and continuous delivery can improve software quality and reduce risk by offering opportunities for testing and some non-obvious benefits to the software development cycle. By taking advantage of cloud computing and automated deployment, throughput can be improved while increasing the amount of testing and ensuring high quality. This article points out some of these opportunities and offers suggestions for making the most of them.
DevOps For Everyone: Bringing DevOps Success to Every App and Every Role in y...Siva Rama Krishna Chunduru
Understand DevOps and it's fitment to various types of applications.
Understand various Organization Roles after Org-restructure.
Understand the way to measure the success.
DevOps in Software Development Solutions_ Benefits and Best PracticesTyrion Lannister
From improved collaboration to increased agility and quality, DevOps offers a range of advantages that can revolutionize software development and drive business success.
Regression Testing: Maintaining Software Integrity Over TimeUncodemy
In the ever-evolving world of software development, ensuring that your software maintains its integrity over time is paramount. As new features are added, bugs are fixed, and changes are implemented, there's always a risk of introducing new issues into your codebase.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Advanced Flow Concepts Every Developer Should KnowPeter Caitens
Tim Combridge from Sensible Giraffe and Salesforce Ben presents some important tips that all developers should know when dealing with Flows in Salesforce.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Strategies for Successful Data Migration Tools.pptxvarshanayak241
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
How to Position Your Globus Data Portal for Success Ten Good Practices
A Mono- and Multi-objective Approach for Recommending Software Refactoring
1. Department of Computer Science and Operations Research
A mono- and Multi-objective Approach for
Recommending Software Refactoring
Ali Ouni
Ph.D. Defense
Advisors: Houari Sahraoui (Université de Montréal, Canada)
Marouane Kessentini (University of Michigan, USA)
12 November 2014