Hardware performance monitoring counters have recently received a lot of attention. They have been used by diverse communities to understand and improve the quality of computing systems: for example, architects use them to extract application characteristics and propose new hardware mechanisms; compiler writers study how generated code behaves on particular hardware; software developers identify critical regions of their applications and evaluate design choices to select the best performing implementation. In this paper, we propose that counters be used by all categories of users, in particular non-experts, and we advocate that a few simple metrics derived from these counters are relevant and useful. For example, a low IPC (number of executed instructions per cycle) indicates that the hardware is not performing at its best; a high cache miss ratio can suggest several causes, such as conflicts between processes in a multicore environment. We also introduce a new simple and flexible user-level tool that collects these data on Linux platforms, and we illustrate its practical benefits through several use cases.
Every other week I explain basics in software testing, one of them is exploratory testing. It depends from group to group, but sometimes I have only 5-10 minutes on the topic. I love challenges! But I am also aware that I am still learning myself. This is why I asked my peers during Exploratory Testing…
Some people believe that nudges are an insult to human agency; that nudges are based on excessive trust in government; that nudges are covert; that nudges are m
The most critical intervention point to affect design at and across all physical scales (see graphic below) is to pay attention to the processes and patterns underlying their physical manifestations…
Because Internet book. Read 20 reviews from the world's largest community for readers. A linguistically informed look at how our digital world is transfo...
This post aims to discuss key monitoring discussion points and to summarise the relevant best practices when instrumenting application performance monitoring. Below are some of the areas we’ll be focusing in on… Terminology. Understand the different types of monitoring. Data collection methods. Frontend monitoring. Make it useful, then actionable. Focus on user impact. Favour organic changes over static thresholds. Send critical and noncritical alarms to different channels.
Bill Gates has become a powerful influence on publishing. An endorsement from the philanthropist and Microsoft cofounder can cause tangible sales spikes, reminiscent of the golden ticket that once came with being picked for Oprah's book club. So just what does Gates read? Quartz manually compiled all 186 of the books recommended on his blog,...
Code Example: https://github.com/vladimir-dejanovic/grpc-bank-example You heard of "new thing" called gRPC and promises that it will solve all issues for you, …
If you wanted to hand a book over to a new tester, to help them get to grips with the world of testing, what topics would you expect or like to see in it?
In the world of software development, Cem Kaner should get the highest recognition for his contribution to software testing (I will describe Kaner’s contributions in another post). In his first book…
Agile Testers are often known as Quality Analysts (QA), Software Engineers in Test, Test Engineers and QA Leads, among other variances. I've been working as an Agile QA for a while and I would like to share my point of view about how QAs work in an agile team. In this article, I will use the term QA to represent an "Agile Tester". Most people, even in agile teams, treat QAs as a sub-role or a separate role in the team. I believe this is an outdated conception. The difference between a QA and a Dev lies in the mindset.
Over the last several years we’ve seen a whole range of ideas regarding the architecture of systems. These include: Hexagonal Architecture (a.k.a. Ports and Adapters) by Alistair Cockburn and adopted by Steve Freeman, and Nat...
The brittleness of tests or specs is a recurring topic in BDD (or acceptance test-driven development, specification-by-example, or whatever you choose to call the thing where you write acceptance criteria, automate them and then make the application match). This is a tricky area, and there are probably as many styles of defining and grouping acceptance…
I recently discovered the high-performance Pandas library written in Python while performing data munging in a machine learning project. Using simple …
Introduction of a basic pattern for developing a robust road map for any organization using an example of the adoption of a Master Data Management initiative.
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