Issue #390

Issue #390
pointer.io


Friday 17th February's issue is presented by QA Wolf

In-house QA can take years to scale. QA Wolf takes weeks. QA Wolf will write, run, and maintain your automated end-to-end test suite — and get you to 80% test coverage in 4 months.

Against Overwhelm

- Paolo André

#Leadership #Management #CareerAdvice


tl;dr: “Throughout my entire engineering management career, what percentage of the time did I spend in a state of overwhelm?” Paolo provides the tools to prevent you to become intentional with how you spend your time and energy: (1) Clarify what goals, and how they align with your team and company, so you have a framework to decide how to not spend your time. (2) Use the Energy Audit to create visibility on where your time, attention and energy are going. (3) Given your goals, focus on leverage instead of productivity. Use the modified Eisenhower Matrix to define what’s truly important and a multiplier of your input. (4) With all of the above, design your ideal week and overlay each actual week on top of it. Push yourself to reduce the gap, and use the two as a means to reflect and improve weekly. (5) Whatever you do, focus on that thing only.

What Is ChatGPT Doing… and Why Does It Work?

- Stephen Wolfram

#GPT #ML


tl;dr: "My purpose here is to give a rough outline of what’s going on inside ChatGPT—and then to explore why it is that it can do so well in producing what we might consider to be meaningful text. I should say at the outset that I’m going to focus on the big picture of what’s going on—and while I’ll mention some engineering details, I won’t get deeply into them.”

The Only Guide To Automated End-To-End Testing You’ll Ever Need

#Management #Testing #Guide


tl;dr: If you’re looking for automated test coverage, there are a few options to consider: in-house, traditional outsourcing, or Test Coverage as a Service. We wrote this guide to help you find a solution that aligns with your product, team size, budget, and overall testing needs.


Promoted by QA Wolf

5 Tips To Creating A (Good) Pull Request
- Danijela Vrzan

#Git #BestPractice


tl;dr: (1) Keep it short. (2) Add more information i.e. the what, why and screenshots. (3) Leave in-line code comments. (4) Assign people or groups as reviewers. (5) Let your colleagues know your PR is ready for review.




“When done well, software is invisible.”


- Bjarne Stroustrup




Big Data Is Dead

- Jordan Tigani

#Data


tl;dr: This post will make the case that the era of Big Data is over. It had a good run, but now we can stop worrying about data size and focus on how we’re going to use it to make better decisions. I’ll show a number of graphs; these are all hand-drawn based on memory. If I did have access to the exact numbers, I wouldn’t be able to share them. But the important part is the shape, rather than the exact values.

10 Web Development Trends In 2023
- Robin Wieruch

#IndustryTrend


tl;dr: Robin discusses (1) Meta frameworks. (2) Application and rendering patterns. (3) Serverless at the edge. (4) Database renaissance (5) JavaScript runtimes. And more.

Content Delivery Network (CDN): Explained In Simple Words
- Animesh Gaitonde

#CDN #Architecture


tl;dr: “In this article, we will understand what a CDN is, why it is needed and how it works. Also, we will see how websites can accelerate their content delivery by harnessing a CDN.”

Code With Swearing Is Better Code
- Jamie Zawinski

#Entertaining


tl;dr: “We find that open source code containing swearwords exhibit significantly better code quality than those not containing swearwords under several statistical tests. We hypothesise that the use of swearwords constitutes an indicator of a profound emotional involvement of the programmer with the code and its inherent complexities, thus yielding better code based on a thorough, critical, and dialectic code analysis process.”


Recommended Reading

Recommended Reading: Quastor


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Notable GitHub Repos
  • Keep: Alerting. By developers, for developers.

  • Promptable: Build LLM apps in Typescript/Javascript.

  • Colossal-AI: Making big AI models cheaper, easier, and more scalable.

  • LowCodeEngine: Enterprise-class low-code technology stack with scale-out design.


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