STAG’s re-engineering of test practices and process standardization drives tangible benefits for a global leader in wireless communication, enabling it to achieve 60% reduction in testing cycle time and 30% increase in productivity.
STAG’s assessment for test case potency of a cloud-based trading software helps reduce
regression test cases by 28% and regression cycle time by 40% for an award-winning B2B
e-commerce company.
STAG transforms the test process to enable effective product assessment and certification of product fitness for beta release, which helps protect the investment in product development for a leading Fleet Management solution provider.
The intelligent automation strategy and tool selection by STAG reduced testing cycle time by 70% and license costs by 60% for a healthcare IT company. STAG analyzed test artifacts, classified test cases, developed an automation architecture using TestComplete tool, and automated 326 test cases. This robust automation framework cut testing effort from 50 to 12 hours. STAG also trained the client's team, providing additional savings versus outside training costs.
This document outlines a structured and scientific approach to designing tests for user stories. It discusses four types of entities to test: individual user stories, sets of user stories for an epic, sets of user stories that form a flow, and sets of user stories across releases. It also describes eight levels of quality to test for. The approach involves first understanding what to test and what criteria to test for. Test cases are then designed using techniques like thinking and proving correctness statically or executing and evaluating dynamically. Conditions that govern behavior are extracted to develop test scenarios that stimulate different behaviors.
This is the webinar recording on the topic ‘Test Case Immunity’- Optimize testing. In this webinar we have conveyed an interesting idea of measuring “Test Case Immunity” to logically assess what test cases to drop by so that we can 'do none'
This outlines FIVE key application scenarios of validation using doSmartQA, a smart probing assistant to test deeply & rapidly.
It facilitates rapid testing in short sessions of Recon, Explore & Recoup, based on HyBIST -
‘Hypothesis Based Immersive Session Testing’, an intellectual practice of probing.
“Despite all the testing we do, field issues do not seem to abate. Sometimes it is a few serious issues that cause us to react intensely, sometimes it is a bunch of simple issues that make us consume bandwidth. Clearly the backlog is building up, with debts to be serviced, straining capacity to deliver new ideas.”
This is what I hear from senior engineering managers of product companies. How do you go about fixing this? Well, I have seen a flurry of activity to identify root cause(s) and address them. They help to set focus, but fizzle out.
Analysing 'quality of technical debt’ to understand types of issues that leak enables practical actions, rather than jumping into the ‘reason of why’ (root cause). Smart QA it is, to do failure analytics differently, to ‘tighten the purse’.
Technical debt is indeed a serious drain on engineering capacity, forcing one to fix issues at the expense of building revenue yielding new features. Smart failure analytics visualises problems well, enabling clear actions to strengthen practice and reduce debt significantly.
If you are “choked by technical debt”, then you may find our SmartQA consulting (stagsoftware.com/smartqa) interesting, where we unshackle your practice so that you can exploit technology.
"We track a lot of metrics related to progress of development and quality every sprint, like backlogs, technical debt, velocity, task status etc. What is not very evident is the 'quality of movement' i.e. how well done, so that we create less debt as we move. How can I get a better insight of the quality of tests done and a more objective measure of product quality?"
Extrinsic metrics are easier to measure and give visibility of direction, progress, speed and external feel of product quality. Intrinsic metrics are deeper, harder to measure but can give greater insight into the quality of work. Measuring this requires a good structure and organisation of test artefacts. The benefit - a greater insight into effectiveness of outcome and therefore lower technical debt & greater acceleration, don't you think?
Metrics can be classified as measuring work progress, work quality, product quality and practice quality. Except for the first one on work progress where we have a lot of measures facilitated by project and test management tools, the others depend on test organisation and clarity of types of issues to uncover. 'Quality Levels' based on HBT (Hypothesis Based Testing) provides a strong foundation for these, enabling you to assess potential test effectiveness, judge product quality objectively and fine tune practice quality .
If you are keen on "insightful quality metrics", then you may find our SmartQA consulting (stagsoftware.com/smartqa) interesting, where we unshackle your practice so that you can see clearly and do far better.
STAG’s assessment for test case potency of a cloud-based trading software helps reduce
regression test cases by 28% and regression cycle time by 40% for an award-winning B2B
e-commerce company.
STAG transforms the test process to enable effective product assessment and certification of product fitness for beta release, which helps protect the investment in product development for a leading Fleet Management solution provider.
The intelligent automation strategy and tool selection by STAG reduced testing cycle time by 70% and license costs by 60% for a healthcare IT company. STAG analyzed test artifacts, classified test cases, developed an automation architecture using TestComplete tool, and automated 326 test cases. This robust automation framework cut testing effort from 50 to 12 hours. STAG also trained the client's team, providing additional savings versus outside training costs.
This document outlines a structured and scientific approach to designing tests for user stories. It discusses four types of entities to test: individual user stories, sets of user stories for an epic, sets of user stories that form a flow, and sets of user stories across releases. It also describes eight levels of quality to test for. The approach involves first understanding what to test and what criteria to test for. Test cases are then designed using techniques like thinking and proving correctness statically or executing and evaluating dynamically. Conditions that govern behavior are extracted to develop test scenarios that stimulate different behaviors.
This is the webinar recording on the topic ‘Test Case Immunity’- Optimize testing. In this webinar we have conveyed an interesting idea of measuring “Test Case Immunity” to logically assess what test cases to drop by so that we can 'do none'
This outlines FIVE key application scenarios of validation using doSmartQA, a smart probing assistant to test deeply & rapidly.
It facilitates rapid testing in short sessions of Recon, Explore & Recoup, based on HyBIST -
‘Hypothesis Based Immersive Session Testing’, an intellectual practice of probing.
“Despite all the testing we do, field issues do not seem to abate. Sometimes it is a few serious issues that cause us to react intensely, sometimes it is a bunch of simple issues that make us consume bandwidth. Clearly the backlog is building up, with debts to be serviced, straining capacity to deliver new ideas.”
This is what I hear from senior engineering managers of product companies. How do you go about fixing this? Well, I have seen a flurry of activity to identify root cause(s) and address them. They help to set focus, but fizzle out.
Analysing 'quality of technical debt’ to understand types of issues that leak enables practical actions, rather than jumping into the ‘reason of why’ (root cause). Smart QA it is, to do failure analytics differently, to ‘tighten the purse’.
Technical debt is indeed a serious drain on engineering capacity, forcing one to fix issues at the expense of building revenue yielding new features. Smart failure analytics visualises problems well, enabling clear actions to strengthen practice and reduce debt significantly.
If you are “choked by technical debt”, then you may find our SmartQA consulting (stagsoftware.com/smartqa) interesting, where we unshackle your practice so that you can exploit technology.
"We track a lot of metrics related to progress of development and quality every sprint, like backlogs, technical debt, velocity, task status etc. What is not very evident is the 'quality of movement' i.e. how well done, so that we create less debt as we move. How can I get a better insight of the quality of tests done and a more objective measure of product quality?"
Extrinsic metrics are easier to measure and give visibility of direction, progress, speed and external feel of product quality. Intrinsic metrics are deeper, harder to measure but can give greater insight into the quality of work. Measuring this requires a good structure and organisation of test artefacts. The benefit - a greater insight into effectiveness of outcome and therefore lower technical debt & greater acceleration, don't you think?
Metrics can be classified as measuring work progress, work quality, product quality and practice quality. Except for the first one on work progress where we have a lot of measures facilitated by project and test management tools, the others depend on test organisation and clarity of types of issues to uncover. 'Quality Levels' based on HBT (Hypothesis Based Testing) provides a strong foundation for these, enabling you to assess potential test effectiveness, judge product quality objectively and fine tune practice quality .
If you are keen on "insightful quality metrics", then you may find our SmartQA consulting (stagsoftware.com/smartqa) interesting, where we unshackle your practice so that you can see clearly and do far better.
“As we embrace faster release cycles, testing has become a bottleneck. Yes, we have embraced automation as the way forward. We have a huge regression suite and therefore a big backlog for automation, a tough balance to speed up and yet maintain the fast paced release rhythm. What can I do?”
Automated tests are great to monitor a system’s health. Rather than just use regression as the candidate for automation, key flows that signify the pulse of a system's health are superior, don’t you think? And, this won’t create a huge backlog for automation, right?
Most often I have seen automation embraced as the solution to speed up testing. Conceptually correct it is, the problem is - what makes it worth the while to automate? Automated tests have to be in sync with the product and are therefore not a one time effort.
Choosing the right ones implies, it needs to be at the level of user flow, and be a clear indicator of health. Unless test scenarios are well structured and organised, choosing the right ones will turn out to be difficult, and ultimately weigh you down. It then becomes a pursuit of catching up with automation rather than making it work for you.
The goal is not 100% automation, it really is no leakage of defects. Automated tests are really ‘checks’ that assess key paths for good health (correctness) while intelligent human tests are focused on finding issues(robustness). A harmonious balance between these two enables clean code to be delivered without being weighed down by automation.
If you are “weighed down by automation“, then you may find our SmartQA consulting (stagsoftware.com/smartqa) interesting, where we unshackle your practice so that you can exploit technology.
Inspired by how the world is handling Covid19, this slideshare lists actions taken and criteria met to contain the pandemic and correlate this to how we can deliver clean code for large scale software systems. This article focuses on the process flow and criteria for delivering clean code.
The document outlines 7 thinking tools to help with rapid testing:
1. Landscaper - Do a survey to understand the big picture
2. Persona map - Map out who uses what
3. Scope map - Map out user expectations
4. Interaction map - Map what may affect what
5. Environment map - Map test environments
6. Scenario creator - Create test scenarios
7. Dashboard - Stop, analyze, and refine
These tools are part of an immersive session testing approach using reconnaissance, exploration, and rest/recovery phases to facilitate rapid yet thorough scientific exploration. A related SaaS tool called doSmartQA will offer these tools and interested users can email the founder for
Agile and automation have been great enablers to doing tests faster. How we can accelerate further to accomplish more by doing less is the objective of this webinar.
“Left-shifting” by smart decomposition of dev testing aided by smart lightweight aids to perform rapid dev testing will be the takeaways of this webinar.
Three ideas to regression test smarter and outline THREE AIDS to do this.
AID #1: Fault propagation analyser - Figure out how what-to-retest by doing a smarter impact analysis using a scientific approach to understanding fault propagation due to change.
AID #2 : Automation analyser - Ensure scenarios are fit-to-automate so that they are easily scriptable and easily maintainable
AID #3 : Yield analyser : Figure out how much not to regress by analysing defect yields over time to understand what parts of the system have been hardened
Well, automation is an obvious choice, ensure that the scenarios are “fit enough for automation” so that you don’t end spend much effort maintaining the scripts to be in sync with every change.
Drawing inspiration from Atul Gawande's book "The checklist manifesto", T Ashok, CEO, STAG Software, explores at how we can exploit the power of checklist to delivering good quality code.
Drawing inspiration from Atul Gawande's book "The checklist manifesto", T Ashok, CEO, STAG Software, explores at how we can exploit the power of checklist to delivering good quality code.
This document discusses how to establish a clear baseline for testing user stories. It defines a baseline as a cartesian product of "what to test" and "test for what". What to test includes individual user stories and collections of user stories spanning epics. Test for what refers to acceptance criteria such as functionality, performance, security, and usability. Different types of tests are mapped to these criteria. Together, what to test and test for what form the baseline, and applying strategies like thinking and proving or executing and evaluating tests establishes a clear approach to validating user stories.
Part1 of Tri-webinar series consisting of three webinars commencing with 'How-to question to understand an user story and identify gaps', moving onto 'How-to set clear baseline' to ensure an effective strategy, and finally culminating with 'How-to design test scenarios/cases' using a scientific and disciplined approach
"Language shapes the way you think" was the topic of the talk presented by T Ashok, CEO STAG Software, to a group of test professionals at a Pune-based IT services and solutions provider on June 16, 2014.
The document describes STAG Software's HBT Quality Visualization Tool. The tool allows users to assess quality across three areas in 3 sentences:
1) Are test assets good? It evaluates the quality of test cases by analyzing factors like applicable test types, test case counts by importance and quality level, and positive/negative ratios.
2) Have we assessed completely? It measures the quality of execution by analyzing execution metrics like percentages completed by test, entity, quality level, and progress over cycles.
3) How good are the outcomes? It determines the quality of the product/application by calculating a cleanliness index based on passed and total test cases, and analyzing performance by entity, cleanliness criteria, and
This presentation on Hypothesis Based Testing (HBT) was delivered by Mr Satvik Kini, Associate Quality Manager, Suite Test Centre, SAP Labs India Pvt. Ltd at STeP-IN Forum webinar on Dec 19, 2013.
The document outlines an approach called "Descriptive-Prescriptive" for better problem solving. It involves first describing a problem by connecting elements and details to understand it fully ("Analysis"), then prescribing rules and conditions to formulate a solution ("Synthesis"). This approach can be applied to test baselining, strategy formulation, test design, and reporting. Diagrams and examples are provided to illustrate applying description and prescription at different stages. The approach forms the basis of a personal test methodology called HBT, which uses six stages and eight disciplines of thinking.
The document describes a three-step approach to improving defect yield in testing:
1. Conduct a potency assessment to determine which types of defects are being targeted by current test cases and if any important types are missing.
2. Perform potential defect type re-targeting to add new test cases to cover additional defect types identified as missing.
3. Enhance existing test cases through potency improvement to ensure they are complete in uncovering defects.
An article by T Ashok, Founder & CEO, STAG Software,where he highlights that metrics can help drive change in behavior to do better.This article was published in the TeaTime with Testers, Feb-Mar 2013 issue of ezine.
STAG Software presented a webinar on Mar 14, 2013 on the topic - Agile Sutra "Do more by doing less, Prevent rather than detect". The webinar was hosted by T Ashok, Founder & CEO, STAG Software and Architect of HBT.
The webinar outlines how HBT (Hypothesis Based Testing) can enable you to "do more by doing less" via enhanced defect prevention ability rather than find more.
STAG’s unique engineering approach to designing test cases enabled detection of critical defects and improved product maturity of a mobile phone application of a global embedded telecom solution provider, enabling go-to-market with high confidence.
T Ashok, Founder & CEO of STAG Software says that the resolution to deliver great quality software is necessary to meet this and requires effort from developer and tester. It requires one to comply with certain conditions and ensure that they are not violated. Read the full article that was published in the January 2013 issue of ezine - Tea Time with Testers.
STAG certifies an eLearning product ‘deploy-ready’ after extensive LSPS evaluation, enabling our partner to successfully deploy it at the world's largest publicly funded health services organization.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
“As we embrace faster release cycles, testing has become a bottleneck. Yes, we have embraced automation as the way forward. We have a huge regression suite and therefore a big backlog for automation, a tough balance to speed up and yet maintain the fast paced release rhythm. What can I do?”
Automated tests are great to monitor a system’s health. Rather than just use regression as the candidate for automation, key flows that signify the pulse of a system's health are superior, don’t you think? And, this won’t create a huge backlog for automation, right?
Most often I have seen automation embraced as the solution to speed up testing. Conceptually correct it is, the problem is - what makes it worth the while to automate? Automated tests have to be in sync with the product and are therefore not a one time effort.
Choosing the right ones implies, it needs to be at the level of user flow, and be a clear indicator of health. Unless test scenarios are well structured and organised, choosing the right ones will turn out to be difficult, and ultimately weigh you down. It then becomes a pursuit of catching up with automation rather than making it work for you.
The goal is not 100% automation, it really is no leakage of defects. Automated tests are really ‘checks’ that assess key paths for good health (correctness) while intelligent human tests are focused on finding issues(robustness). A harmonious balance between these two enables clean code to be delivered without being weighed down by automation.
If you are “weighed down by automation“, then you may find our SmartQA consulting (stagsoftware.com/smartqa) interesting, where we unshackle your practice so that you can exploit technology.
Inspired by how the world is handling Covid19, this slideshare lists actions taken and criteria met to contain the pandemic and correlate this to how we can deliver clean code for large scale software systems. This article focuses on the process flow and criteria for delivering clean code.
The document outlines 7 thinking tools to help with rapid testing:
1. Landscaper - Do a survey to understand the big picture
2. Persona map - Map out who uses what
3. Scope map - Map out user expectations
4. Interaction map - Map what may affect what
5. Environment map - Map test environments
6. Scenario creator - Create test scenarios
7. Dashboard - Stop, analyze, and refine
These tools are part of an immersive session testing approach using reconnaissance, exploration, and rest/recovery phases to facilitate rapid yet thorough scientific exploration. A related SaaS tool called doSmartQA will offer these tools and interested users can email the founder for
Agile and automation have been great enablers to doing tests faster. How we can accelerate further to accomplish more by doing less is the objective of this webinar.
“Left-shifting” by smart decomposition of dev testing aided by smart lightweight aids to perform rapid dev testing will be the takeaways of this webinar.
Three ideas to regression test smarter and outline THREE AIDS to do this.
AID #1: Fault propagation analyser - Figure out how what-to-retest by doing a smarter impact analysis using a scientific approach to understanding fault propagation due to change.
AID #2 : Automation analyser - Ensure scenarios are fit-to-automate so that they are easily scriptable and easily maintainable
AID #3 : Yield analyser : Figure out how much not to regress by analysing defect yields over time to understand what parts of the system have been hardened
Well, automation is an obvious choice, ensure that the scenarios are “fit enough for automation” so that you don’t end spend much effort maintaining the scripts to be in sync with every change.
Drawing inspiration from Atul Gawande's book "The checklist manifesto", T Ashok, CEO, STAG Software, explores at how we can exploit the power of checklist to delivering good quality code.
Drawing inspiration from Atul Gawande's book "The checklist manifesto", T Ashok, CEO, STAG Software, explores at how we can exploit the power of checklist to delivering good quality code.
This document discusses how to establish a clear baseline for testing user stories. It defines a baseline as a cartesian product of "what to test" and "test for what". What to test includes individual user stories and collections of user stories spanning epics. Test for what refers to acceptance criteria such as functionality, performance, security, and usability. Different types of tests are mapped to these criteria. Together, what to test and test for what form the baseline, and applying strategies like thinking and proving or executing and evaluating tests establishes a clear approach to validating user stories.
Part1 of Tri-webinar series consisting of three webinars commencing with 'How-to question to understand an user story and identify gaps', moving onto 'How-to set clear baseline' to ensure an effective strategy, and finally culminating with 'How-to design test scenarios/cases' using a scientific and disciplined approach
"Language shapes the way you think" was the topic of the talk presented by T Ashok, CEO STAG Software, to a group of test professionals at a Pune-based IT services and solutions provider on June 16, 2014.
The document describes STAG Software's HBT Quality Visualization Tool. The tool allows users to assess quality across three areas in 3 sentences:
1) Are test assets good? It evaluates the quality of test cases by analyzing factors like applicable test types, test case counts by importance and quality level, and positive/negative ratios.
2) Have we assessed completely? It measures the quality of execution by analyzing execution metrics like percentages completed by test, entity, quality level, and progress over cycles.
3) How good are the outcomes? It determines the quality of the product/application by calculating a cleanliness index based on passed and total test cases, and analyzing performance by entity, cleanliness criteria, and
This presentation on Hypothesis Based Testing (HBT) was delivered by Mr Satvik Kini, Associate Quality Manager, Suite Test Centre, SAP Labs India Pvt. Ltd at STeP-IN Forum webinar on Dec 19, 2013.
The document outlines an approach called "Descriptive-Prescriptive" for better problem solving. It involves first describing a problem by connecting elements and details to understand it fully ("Analysis"), then prescribing rules and conditions to formulate a solution ("Synthesis"). This approach can be applied to test baselining, strategy formulation, test design, and reporting. Diagrams and examples are provided to illustrate applying description and prescription at different stages. The approach forms the basis of a personal test methodology called HBT, which uses six stages and eight disciplines of thinking.
The document describes a three-step approach to improving defect yield in testing:
1. Conduct a potency assessment to determine which types of defects are being targeted by current test cases and if any important types are missing.
2. Perform potential defect type re-targeting to add new test cases to cover additional defect types identified as missing.
3. Enhance existing test cases through potency improvement to ensure they are complete in uncovering defects.
An article by T Ashok, Founder & CEO, STAG Software,where he highlights that metrics can help drive change in behavior to do better.This article was published in the TeaTime with Testers, Feb-Mar 2013 issue of ezine.
STAG Software presented a webinar on Mar 14, 2013 on the topic - Agile Sutra "Do more by doing less, Prevent rather than detect". The webinar was hosted by T Ashok, Founder & CEO, STAG Software and Architect of HBT.
The webinar outlines how HBT (Hypothesis Based Testing) can enable you to "do more by doing less" via enhanced defect prevention ability rather than find more.
STAG’s unique engineering approach to designing test cases enabled detection of critical defects and improved product maturity of a mobile phone application of a global embedded telecom solution provider, enabling go-to-market with high confidence.
T Ashok, Founder & CEO of STAG Software says that the resolution to deliver great quality software is necessary to meet this and requires effort from developer and tester. It requires one to comply with certain conditions and ensure that they are not violated. Read the full article that was published in the January 2013 issue of ezine - Tea Time with Testers.
STAG certifies an eLearning product ‘deploy-ready’ after extensive LSPS evaluation, enabling our partner to successfully deploy it at the world's largest publicly funded health services organization.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
Efficient Test Practice Reduces Cycle Time by 60%
1. CASE STUDY
Efficient Test Practice Reduces
Cycle Time by 60%
STAG’s re-engineering of test practices and process
standardization drives tangible benefits for a
global leader in wireless communication, enabling
it to achieve 60% reduction in testing cycle time
and 30% increase in productivity.
Domain/Category -
Technology - C++, PERL
Mobile / Wireless Telecom
CUSTOMER AND PRODUCT BACKGROUND
The customer is the India Development Center (IDC) of a world leader in 3G and next-generation mobile technologies.
The product in question was a video sharing application that was developed at the IDC using C/C++. The application was
intended for sharing or storing videos on mobile phones with or without Packet Switched (PS) / Circuit Switched (CS) calls.
The application used Session Initiation Protocol (SIP) for signaling and Real Time Protocol (RTP) for streaming.
PROBLEM STATEMENT
The product components from different development centers were integrated at the IDC and then sent out for field-testing
at an overseas site. The client discovered that the field-testing QA team spent considerable amount of time detecting
system-level defects, leading to an increase in field testing effort and, therefore, delays in product release. The client sought
the help of a specialist partner to fix this anomaly immediately and arrest defect escapes to field.