The team has made progress on their device to detect irregularities in perishable goods. They have taken images of moldy strawberries and gotten the robotic arm motor to work in two directions. Tasks completed include getting the motor to work in one direction and creating a database of non-moldy strawberries. Ongoing tasks are designing and testing the robotic arm and image processing. Upcoming tasks are starting tests on the schematic diagram and acquiring all image data for testing the algorithm.
Auto-completing Bug Reports for Android ApplicationsKevin Moran
The modern software development landscape has seen a shift in focus toward mobile applications as tablets and smartphones near ubiquitous adoption. Due to this trend, the complexity of these “apps” has been increasing, making development and maintenance challenging. Additionally, current bug tracking systems are not able to effectively support construction of reports with actionable information that directly lead to a bug’s resolution. To address the need for an improved reporting system, we introduce a novel solution, called FUSION, that helps users auto-complete reproduction steps in bug reports for mobile apps. FUSION links user-provided information to program artifacts extracted through static and dynamic analysis performed before testing or release. The approach that FUSION employs is generalizable to other current mobile software platforms, and constitutes a new method by which off-device bug reporting can be conducted for mobile software projects. In a study involving 28 participants we applied FUSION to support the maintenance tasks of reporting and reproducing defects from 15 real-world bugs found in 14 open source Android apps while qualitatively and qualitatively measuring the user experience of the system. Our results demonstrate that FUSION both effectively facilitates reporting and allows for more reliable reproduction of bugs from reports compared to traditional issue tracking systems by presenting more detailed contextual app information.
Mobile App Testing: Design Automation Patterns You Should UseTechWell
In mobile app development, better test design is important to project velocity and user satisfaction. Jon Hagar explores underused or poorly practiced test design automation approaches that you should employ in development and testing. Jon begins by defining the domain of mobile app software and examines common industry patterns of product failures. He then shares three approaches you can use to speed development and improve quality for native, web-based, and hybrid apps. The methods examined—each supported with detailed checklists—are combinatorial testing, model-based testing, and user experience testing. Jon explains when, where, and how each testing approach can be used to support improved testing and to benefit the whole team. In addition to mobile apps, you and your team can use these same three approaches in other software environments to reduce technical debt during development.
Software robots like monkey provide a quick way to validate your application. With robots on new cloud testing services, it is easier than ever to get started testing your app without even having written any tests. In this talk, I will introduce a few tools from both academia and industry, and then cover the basics of how these tools work. You will learn about the strengths and limitations these tools and how to use them effectively to maximize code coverage and catching failures.
SourceWarp: A scalable, SCM-driven testing and benchmarking approach to support data-driven and agile decision making for CI/CD tools and DevOps platforms. This is a presentation we gave at the the 4th ACM/IEEE International Conference on Automation of Software Test (AST 2023) https://conf.researchr.org/home/ast-2023. Additional information about SourceWarp can be found in the blog post https://about.gitlab.com/blog/2023/04/13/data-driven-decision-making-with-sourcewarp/.
Robotic Harvesting of Fruiting Vegetables, “Acceleration by Simulation”Redmond R. Shamshiri
Robotic Harvesting of Fruiting Vegetables, “Acceleration by Simulation”
Presented at the Acceleration Workshop Robotics & Crop Sensing in Greenhouses, 11-12 September 2017. Delf University of Technology, The Netherlands
Robotic Harvesting with NOVABOT innovative manipulator
https://youtu.be/R38IoVcOVt0
Robotic Harvesting with multiple SCARA manipulators
https://youtu.be/TLLW3S-55ls
Robotic Harvesting with Array of Linear Actuators
https://youtu.be/iFu7FAxLvmg
Robotic Harvesting with fanuc lr mate 200id (Visual Servo Control in V-REP, ROS, MATLAB)
https://youtu.be/BwRBUeB812s
Robotic Harvesting, Simulation of Environment and Fruit/Plant Scan
https://youtu.be/XD3J7b0cDGM
Advanced Visual Servo Control in V-REP for Robotic harvesting of sweet pepper
https://youtu.be/VupoirQOL0Y
Robotic Harvesting of Sweet Pepper, Ubuntu, V-REP, ROS Environment Setup
https://youtu.be/tKagjNQ9FW4
Real-time, robust and rapid red-pepper fruit detection with Matlab
https://youtu.be/rFV6Y5ivLF8
Talk
https://youtu.be/QZawPeg3wEQ
Auto-completing Bug Reports for Android ApplicationsKevin Moran
The modern software development landscape has seen a shift in focus toward mobile applications as tablets and smartphones near ubiquitous adoption. Due to this trend, the complexity of these “apps” has been increasing, making development and maintenance challenging. Additionally, current bug tracking systems are not able to effectively support construction of reports with actionable information that directly lead to a bug’s resolution. To address the need for an improved reporting system, we introduce a novel solution, called FUSION, that helps users auto-complete reproduction steps in bug reports for mobile apps. FUSION links user-provided information to program artifacts extracted through static and dynamic analysis performed before testing or release. The approach that FUSION employs is generalizable to other current mobile software platforms, and constitutes a new method by which off-device bug reporting can be conducted for mobile software projects. In a study involving 28 participants we applied FUSION to support the maintenance tasks of reporting and reproducing defects from 15 real-world bugs found in 14 open source Android apps while qualitatively and qualitatively measuring the user experience of the system. Our results demonstrate that FUSION both effectively facilitates reporting and allows for more reliable reproduction of bugs from reports compared to traditional issue tracking systems by presenting more detailed contextual app information.
Mobile App Testing: Design Automation Patterns You Should UseTechWell
In mobile app development, better test design is important to project velocity and user satisfaction. Jon Hagar explores underused or poorly practiced test design automation approaches that you should employ in development and testing. Jon begins by defining the domain of mobile app software and examines common industry patterns of product failures. He then shares three approaches you can use to speed development and improve quality for native, web-based, and hybrid apps. The methods examined—each supported with detailed checklists—are combinatorial testing, model-based testing, and user experience testing. Jon explains when, where, and how each testing approach can be used to support improved testing and to benefit the whole team. In addition to mobile apps, you and your team can use these same three approaches in other software environments to reduce technical debt during development.
Software robots like monkey provide a quick way to validate your application. With robots on new cloud testing services, it is easier than ever to get started testing your app without even having written any tests. In this talk, I will introduce a few tools from both academia and industry, and then cover the basics of how these tools work. You will learn about the strengths and limitations these tools and how to use them effectively to maximize code coverage and catching failures.
SourceWarp: A scalable, SCM-driven testing and benchmarking approach to support data-driven and agile decision making for CI/CD tools and DevOps platforms. This is a presentation we gave at the the 4th ACM/IEEE International Conference on Automation of Software Test (AST 2023) https://conf.researchr.org/home/ast-2023. Additional information about SourceWarp can be found in the blog post https://about.gitlab.com/blog/2023/04/13/data-driven-decision-making-with-sourcewarp/.
Robotic Harvesting of Fruiting Vegetables, “Acceleration by Simulation”Redmond R. Shamshiri
Robotic Harvesting of Fruiting Vegetables, “Acceleration by Simulation”
Presented at the Acceleration Workshop Robotics & Crop Sensing in Greenhouses, 11-12 September 2017. Delf University of Technology, The Netherlands
Robotic Harvesting with NOVABOT innovative manipulator
https://youtu.be/R38IoVcOVt0
Robotic Harvesting with multiple SCARA manipulators
https://youtu.be/TLLW3S-55ls
Robotic Harvesting with Array of Linear Actuators
https://youtu.be/iFu7FAxLvmg
Robotic Harvesting with fanuc lr mate 200id (Visual Servo Control in V-REP, ROS, MATLAB)
https://youtu.be/BwRBUeB812s
Robotic Harvesting, Simulation of Environment and Fruit/Plant Scan
https://youtu.be/XD3J7b0cDGM
Advanced Visual Servo Control in V-REP for Robotic harvesting of sweet pepper
https://youtu.be/VupoirQOL0Y
Robotic Harvesting of Sweet Pepper, Ubuntu, V-REP, ROS Environment Setup
https://youtu.be/tKagjNQ9FW4
Real-time, robust and rapid red-pepper fruit detection with Matlab
https://youtu.be/rFV6Y5ivLF8
Talk
https://youtu.be/QZawPeg3wEQ
OSMC 2016 - Application Performance Management with Open-Source-Tooling by M...NETWAYS
Mario Mann ist Consultant bei der NovaTec Consulting GmbH. Seit seinem erfolgreichen Studium der Informatik ist er als Performance Engineer bei einer Großbank im Einsatz. Parallel dazu entwickelt er an inspectIT mit und ist an Themen rund um APM - Application Performance Management - engagiert.
OSMC 2016 | Application Performance Management with Open-Source-Tooling by Ma...NETWAYS
In vielen Softwareprojekten wissen häufig nicht nur Anwender, sondern auch Entwickler nicht, warum sich die Anwendung nicht verhält wie erwartet. Wieso ist meine Anwendung so langsam? Warum ist die Anwendung gerade jetzt nicht verfügbar? An Performance-Tests wurde während der Entwicklung nicht gespart. Aber selbst die innovativste Software ist nutzlos, wenn die Performance und Verfügbarkeit nicht gewährleistet ist. Was kann also das Problem sein? Abhilfe schafft in solchen Fällen die Integration von Application Performance Management (APM) in den Entwicklungsprozess und den Betrieb. Kommerzielle APM Lösungen bieten oft sehr umfassende und mächtige Werkzeuge, die allerdings mit entsprechend hohen Kosten verbunden sind und die Kunden in einen Vendor Lock-in drängen. Die Sicherstellung der Softwareperformance muss aber weder teuer noch proprietär sein. In diesem Vortrag zeigen wir die Wichtigkeit und den Umfang des Themengebiets APM auf und gehen auf die Frage ein, wie man mit Open-Source-Werkzeugen unterschiedliche Belange rund um das Thema APM adressieren kann. Fokussiert auf Java-basierte Unternehmenssoftware beleuchten wir unterschiedliche Dimensionen und Aspekte von APM und illustrieren diese anhand von konkreten Beispielen. Dabei zeigen wir für unterschiedliche Aspekte von APM, wie Open-Source-Werkzeuge sinnvoll miteinander kombiniert werden können, um die Performance der Anwendung in unterschiedlichen Phasen des Softwarelebenszyklus sicherzustellen. Die Zuhörer dieses Vortrags lernen Alternativen zu den oft schwergewichtigen, kommerziellen APM-Lösungen kennen und bekommen Ideen an die Hand, welche Open-Source-Werkzeuge wie und in welcher Kombination sinnvoll angewendet werden können, um bestimmte Ziele zu erreichen.
Creative Automation - All you need to know. Automated testing of look and feel for your responsive websites with Galen Framework. Approach, Scenarios, Features etc.
Exploring the upside of risk: optimize the IT portfolioMichel de Goede
How to innovate your business model when you're rooted in traditional work methods and legacy while being overtaken by reality with IoT, BYOD, staff shortages, EV's, decentral energy production and IT security problems? Presentation delivered at the IT Strategy Governance and Transformation Forum, Amsterdam on 13 October 2014
1. Status Report #5Food DIPTeam 11Device that detects irregularities in perishable goods before distribution Brandy Alger Travis Ayers Josue Figueroa Joaquin Labrado
2. Overall Need for Design Prevention of food poisoning epidemic, recalls, and packaging money loss for packing bad food. Design Milestones Images of moldy strawberries taken (02/25) Robotic arm motor working two directions(02/30) Image Processing Algorithm done (02/30)
3. Tasks Completed Motor working in one direction Data base for non-moldy strawberries Conveyor belt found Frequent visits to SwRI Weekly meetings with business team
4. Ongoing Tasks Design and test for Robotic Arm and Image Processing Finish arm build to test sensors Go to SwRI and acquire several different samples of moldy strawberries. Meet with business team Fix motor to work in two directions Finish Algorithm for image processing
5. Upcoming Tasks Start and test schematic/flow diagram of Robotic Arm and Image Processor Robotic Arm: Design a PID controller and test Accelerometer. Image Processor: acquire all data into data base for algorithm testing Fix conveyor belt to fit design specifications