The hottest Quality Assurance Substack posts right now

And their main takeaways
Category
Top Technology Topics

Bugs Optional?

Software Design: Tidy First? • 1723 implied HN points • 03 Jan 25
🕹 Technology Software Development Programming Engineering Quality Assurance Project management
  1. Bugs don't have to be a normal part of software development. Some teams manage to almost eliminate bugs by approaching their work differently.
  2. Instead of seeing bugs as inevitable, teams can work to understand and prevent them right from the start. This includes practices like continuous integration and team collaboration.
  3. Changing how we think about bugs from a normal part of life to something rare can help create a better work environment and improve software quality.

Are AI Coding Assistants Really Saving Developers Time? Study Suggests These Tools Don’t Increase Coding Speed.

Shenisha’s Substack • 19 implied HN points • 04 Oct 24
🕹 Technology AI Tools Software Development Coding Practices Productivity Metrics Quality Assurance
  1. AI coding tools, like GitHub Copilot, may actually slow down developers by increasing the number of bugs in their code. This raises questions about whether these tools truly help improve code quality.
  2. While some surveys show that many developers use AI tools and feel productive, a study found that these tools didn't significantly improve coding speed or help reduce burnout among developers.
  3. The rise of AI tools may require developers to spend more time reviewing the code these tools produce, which can cancel out any time they might save overall.

Software Quality

Engineering Enablement • 21 implied HN points • 12 Feb 25
🕹 Technology Software Development Engineering Practices Product Management Developer Productivity Quality Assurance
  1. Software quality has four main types: process quality, code quality, system quality, and product quality. Each type affects the others, so improving one can help improve the rest.
  2. Process quality is crucial because a good development process leads to better code quality. This means having proper testing and code reviews can help avoid defects later on.
  3. Product quality is what customers experience and it includes a product's usability and reliability. Engineers need to team up with product managers to ensure that products meet customer needs.

The N-stamp

Gordian Knot News • 109 implied HN points • 24 Jan 25
💼 Business Nuclear Energy Quality Assurance Construction Regulations
  1. The N-stamp certifies a vendor's quality assurance process but doesn't guarantee the actual quality of their products. It's more about paperwork than real product inspection.
  2. In shipbuilding, multiple independent inspection teams check quality because they want to avoid costly mistakes. This extra layer helps ensure that ships meet the specifications and are delivered on time.
  3. The nuclear industry's reliance on the N-stamp allows vendors to skip necessary inspections, leading to poor quality products. This system could result in very high costs due to failures in quality control.

Testing Too Late: A Case Study

QUALITY BOSS • 139 implied HN points • 09 Jul 24
🕹 Technology Software Quality Assurance Project management Development Testing
  1. Testing too late can cause big delays in getting software to users. If QA is behind, it creates confusion and slows down the whole process.
  2. Good communication between development and QA teams is really important. Working in separate sprints can lead to misunderstandings and more difficult bug fixes.
  3. It's essential to define when a task is 'done' to include testing. If something isn't tested, it shouldn't be considered complete, ensuring that quality stays high.
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Scrum’s Definition of Done Is Polishing Plates in a Burning Kitchen

Rethinking Software • 499 implied HN points • 20 Nov 24
🕹 Technology Software Development Agile Methodology Project management Quality Assurance Team Dynamics
  1. Scrum's Definition of Done creates extra pressure on developers to deliver perfect work, even when the process is chaotic. It doesn't fix the problems; it just shifts the blame onto the team.
  2. Instead of focusing on quality, Scrum encourages speed and follows strict checklists. This leads to developers cutting corners just to meet unrealistic deadlines.
  3. Real improvements would come from changing the whole process, like allowing more time for reflection, empowering developers, and reducing unnecessary meetings, which would promote better quality work.

A Guide for Building High-Quality Data Products

Inside Data by Mikkel Dengsøe • 16 implied HN points • 16 Jan 25
🕹 Technology Data science Product Development Quality Assurance Team Management Data Analytics
  1. Start by clearly defining how you will use data. This helps set the purpose for your data products.
  2. It's important to have clear ownership of data and understand what needs testing. This makes accountability easier.
  3. Continuously monitor and improve your data quality. Regular reviews help catch issues early and keep trust in your data.

Definition of Dumb

Rethinking Software • 249 implied HN points • 30 Nov 24
🕹 Technology Software Development Agile Methodology Project management Quality Assurance Team Dynamics
  1. The Definition of Done in Scrum can often mask real problems instead of solving them. It makes it seem like poor quality doesn't exist by placing all responsibility on the developers.
  2. Many companies stick to strict processes without recognizing their flaws. This leads to frustration among developers who are pushed to meet unrealistic expectations.
  3. Empowering developers to create their own processes might lead to better results. By trusting the team, companies can produce high-quality work without getting bogged down by rigid frameworks.

Finding Data Bugs in dbt Pull Requests

clkao@substack • 39 implied HN points • 17 Aug 24
🕹 Technology Data Engineering Software Development Open Source Machine Learning Quality Assurance
  1. Data bugs can be costly for companies, with bad data potentially costing up to 25% of their revenue. These issues often arise from problems in data-centric systems like dbt.
  2. Using dbt allows data engineers to implement software practices like version control and testing, helping to ensure the correctness of their data transformations. However, relying solely on post-processing tests has its limits.
  3. Manual spot checks are still crucial in ensuring data accuracy during code reviews. Tools like Recce aim to streamline this process, making it easier for developers to validate and document their changes.

Last Call for Quality

QUALITY BOSS • 39 implied HN points • 03 Jul 24
🕹 Technology Software Development Quality Assurance Development Practices DevOps
  1. Testing software too late can lead to more expensive and difficult fixes. It's better to catch bugs earlier in the development process.
  2. Many teams rely too much on manual testing, which can slow things down. A mix of automated and manual testing can improve quality and efficiency.
  3. Ignoring non-functional requirements like security and performance can make software unsatisfactory, even if it meets basic needs. It's important to include these factors in testing plans.

Inconsistency as a service

Gradient Ascendant • 13 implied HN points • 10 Dec 24
🕹 Technology Artificial Intelligence Software Development Engineering Quality Assurance Data processing
  1. Testing is really important for both hardware and software, especially when things can fail sometimes. In making chips, a lot of resources go into making sure they work properly.
  2. With AI like LLMs, you have to keep checking their outputs because they can be unpredictable. It's smart to set up a test system to know if what you're getting makes sense.
  3. We're still figuring out the best ways to test AI technology. Just like with traditional software, it will take time to develop good practices for making sure LLMs work well and reliably.

164 | Food Fraud Special |

The Rotten Apple • 21 implied HN points • 11 Nov 24
🍲 Food & Drink Food Safety Food Fraud Quality Assurance Supply Chain Regulations
  1. Food fraud prevention needs dedicated teams. These teams should include members from various departments to effectively address fraud risks.
  2. Underweight ingredients can be a form of food fraud if there's intent to deceive. If companies consistently deliver less than what was ordered, it could be seen as cheating customers.
  3. Staying informed about food safety and fraud trends is crucial. Changes in supply chains and economic conditions can create new opportunities for fraud.

Readers respond to TDD x Psychological Safety survey

🔮 Crafting Tech Teams • 119 implied HN points • 14 Dec 23
🕹 Technology Engineering Testing Psychological safety Quality Assurance Software Development
  1. Experts find more ways to reward themselves while they work, not because they are more disciplined.
  2. Identity and team cohesion play a significant role in TDD adoption among tech teams.
  3. TDD adoption can lead to a blameless culture, improved design, and higher quality when implemented correctly.

Productivity in Software Engineering: Beyond lines of code, the importance of experience in the development cycle

VTEX’s Tech Blog • 1 HN point • 18 Sep 24
🕹 Technology Software Engineering Productivity Developer Experience Quality Assurance Performance Metrics
  1. Productivity in software engineering is not just about how much code you write. It's more important to focus on code quality and how well the software works.
  2. At VTEX, they listen to developers to improve their work experience. This helps boost productivity by addressing the challenges developers face.
  3. Combining feedback from developers with quantitative data can help understand the impact of changes in tools and processes on productivity.

The unhindered growth of bad mobile app product management

system bashing • 137 implied HN points • 05 Jun 23
🕹 Technology User Experience Quality Assurance
  1. There is a rise in poorly made mobile apps due to the growth of bad mobile app product management.
  2. Many mobile apps have similar features and design flaws, showcasing repetitive mistakes by product managers.
  3. Consistency in user experience, from technical aspects like rotation to design elements like button styles, is lacking in many apps, pointing to a need for improvement.

Hidden Tasks of Product Management

Sarah's Newsletter • 159 implied HN points • 28 Jun 22
💼 Business Management Data-driven Quality Assurance Stakeholder engagement Leadership
  1. Product managers should oversee their company’s offering like any manager oversees people.
  2. Being data-driven is crucial for product managers. They need to question data, consider various types of data, and course correct based on data-driven decisions.
  3. Product managers play a critical role in owning quality assurance and getting stakeholder buy-in for successful product launches.

What Makes a Great Quality Engineer?

QUALITY BOSS • 39 implied HN points • 30 Oct 23
🕹 Technology Software Testing Quality Assurance Technical Skills Product Development User Experience
  1. Great quality engineers need a quality mindset. This means they care about making sure the product is useful and works well for customers, not just ticking off boxes.
  2. Some key traits of top QEs are curiosity, adaptability, and persistence. These qualities help them understand the product better and keep pushing until they get to the bottom of any issues.
  3. Effective communication and problem-solving skills are also important. This ensures they can share findings clearly and work well with other teams to improve the product.

Quality Engineering Basics: Debugging

QUALITY BOSS • 19 implied HN points • 12 Feb 24
🕹 Technology Software Testing Quality Assurance Debugging Development Tools User Experience
  1. Debugging is like being a detective; you need to find clues to solve the problem in the software. Understanding how or when a bug happens can help get it fixed faster.
  2. A good bug report includes details like when the bug occurs and what steps to reproduce it. The more information you provide, the easier it is for developers to understand and fix the issue.
  3. Trying different methods and tools can help uncover more about the bug. For example, using different browsers or versions of software can help pinpoint what's causing the problem.

GroupBy #1

VuTrinh. • 19 implied HN points • 08 Sep 23
🕹 Technology Data Engineering Architecture AI Quality Assurance Open Source
  1. Kappa architecture simplifies data processing by combining batch and stream processing. This makes handling data more efficient compared to the traditional Lambda architecture.
  2. Presto is a powerful tool for querying large datasets, and Meta has valuable insights on using it effectively. Learning from their experience can help other teams improve their data operations.
  3. Data quality is crucial in analytics, and there are specific metrics to help measure it. Keeping track of these can prevent problems that arise from poor data.

Manager or short order cook?

Sunday Letters • 59 implied HN points • 28 Aug 22
💼 Business Management Quality Assurance Organizational Behavior Leadership Engineering
  1. Organizations often say they value things like quality, but they might not really mean it. It's important to see if they make real choices based on those values.
  2. If engineers are just completing tasks without context, it can hurt quality and user experience. This 'short order cook' approach can lead to many problems.
  3. When interviewing or leading, ask if engineers can delay releases for quality issues. It’s a good way to understand how much the organization cares about quality.

Episode 36: Better Built By Burkhard

burkhardstubert • 19 implied HN points • 15 Feb 23
🕹 Technology Software Development Embedded Systems Continuous Delivery Automation Quality Assurance
  1. A Continuous Delivery pipeline helps keep software always ready for release by quickly identifying problems at various stages.
  2. The workflow consists of three main stages: Commit Stage, Acceptance Stage, and System Stage, with each stage increasing confidence in the software's reliability.
  3. It's best to start building your CD pipeline now, even if it's simple, and improve it step by step as you learn.

Improving data quality in online studies

UX Psychology • 19 implied HN points • 23 Nov 21
🔬 Science Data Quality Data Collection Quality Assurance
  1. In online studies, factors like distractions, poor equipment, and cheating can impact data quality.
  2. Engagement levels, accuracy, outliers, and speed of responses are key indicators to assess data quality in online studies.
  3. Strategies like consistency measures, attention checks, bot detection, and serious response checks can help improve data quality in online studies.

Getting Started as a Quality Engineer

QUALITY BOSS • 0 implied HN points • 08 Dec 23
🕹 Technology Software Testing Quality Assurance
  1. Start with exploratory testing to learn the basics of software quality. You can practice this by using any application you regularly use.
  2. Once you find bugs, learn how to document and report them properly. This practice is key to getting recognized in the quality engineering field.
  3. Familiarize yourself with essential tools like APIs and Chrome DevTools, especially if you want to move into automation. Free online courses can help you build your skills.

Quality Engineering Basics: Bug Reporting

QUALITY BOSS • 0 implied HN points • 19 Dec 23
🕹 Technology Software Testing Quality Assurance Development Process
  1. A good bug report should have a clear title that describes the issue. This helps others understand the problem quickly without needing to read everything.
  2. Including steps to reproduce the bug is essential. This allows developers to see the issue themselves and figure out how to fix it.
  3. Adding relevant details like environment information, expected vs. actual results, and visual aids like screenshots makes the report more useful and helps prioritize the fix.

On Managing Risk in Software Projects

Anant’s Newsletter • 0 implied HN points • 19 Jun 24
🕹 Technology Software Development Project management User Experience Quality Assurance Risk management
  1. Understand user needs clearly to avoid creating features that don't solve problems; involve users early in testing to catch issues.
  2. Ensure all teams understand their roles and dependencies to prevent surprises; clarify API contracts and dependencies early on.
  3. Plan integration and testing carefully; start integrating early and create detailed testing plans to ensure everything works before launch.

Quality Engineering Basics: Automated vs. Manual

QUALITY BOSS • 0 implied HN points • 11 Mar 24
🕹 Technology Software Testing Automation Quality Assurance Risk management Frameworks
  1. Deciding which tests to automate or run manually is important. You should look at the risk level and necessary effort for each test.
  2. Using a scoring system can help prioritize tests. This involves scoring impact, likelihood, frequency, and the effort required for manual or automated testing.
  3. Starting small with your scoring approach is a good idea. You can adjust the numbers until you find what works best for your testing needs.

Quality Engineering Basics: Prioritizing Bugs

QUALITY BOSS • 0 implied HN points • 18 Mar 24
🕹 Technology Software Development Quality Assurance Project management Automation
  1. Understanding how to prioritize bugs is key for efficient quality engineering. It's important to have a common agreement on what each priority level means.
  2. Using a matrix to categorize bugs by their scope and impact can help in deciding their priority. This method allows teams to see which bugs are more urgent and need immediate attention.
  3. Automation tools, like GitHub actions, can streamline the bug prioritization process. They can help automatically assign priority based on set parameters, saving time and reducing errors.

Quality Engineering Basics: Exploratory Testing

QUALITY BOSS • 0 implied HN points • 26 Feb 24
🕹 Technology Software Testing Quality Assurance Product Development User Experience
  1. Exploratory testing is a flexible approach that doesn't need detailed preparation. It lets testers use their skills and creativity to find bugs efficiently.
  2. Using test charters can help focus exploratory testing. You can define what to explore, how to explore it, and what you want to learn.
  3. To improve your testing, think about worst-case scenarios for your product. Coming up with nightmare headlines can help guide your exploratory testing efforts.

Meet Bug, the QUALITY BOSS Mascot

QUALITY BOSS • 0 implied HN points • 06 Nov 23
🕹 Technology Software Quality Assurance Development Leadership Women in Tech
  1. The mascot is a firefly named Bug, symbolizing the journey towards achieving high quality. Bug is meant to guide and inspire everyone to reach excellence.
  2. The term 'bug' usually refers to problems in software, but here it's reimagined as a positive force for growth. Each bug is seen as a chance to improve and learn.
  3. Bug not only represents quality but also highlights unique experiences in the tech industry, especially for women. This fosters a community focused on exploration and learning.