CodeScene

Ready to start your weekend with some interesting webinars? We've got you covered. 💪 Our Principal Researcher, Markus Borg, talks about "The Quest for Evidence-Based Tech Debt" in this interesting webinar in collaboration with NFJS. Tune in 🎧 https://hubs.ly/Q02Fc8Bc0 Technical debt is an established concept in the software industry. Developers know that “quick and dirty” will return and haunt you later. The interest is the extra effort you must dedicate to future development because of previous shortcuts. However, awareness of code issues rarely leads to action, and the debt is not paid off – typically because implementing new features gets higher priority. What if we could cast a light on the technical debt interest rates? In this webinar, we will discuss the business impact of poor code quality. The findings originate from original research and our ongoing quest for evidence-based technical debt management. You will leave the webinar with a new perspective on the costs of technical debt – ready to motivate the next refactoring campaign! #technicaldebt #codequality #softwareengineering

Can you calculate the costs of technical debt to optimize your software delivery? Yes, you can. 🚀 Did you like the slides? Download the whitepaper right here: https://lnkd.in/dHHF2q-Z Also read "Code Quality: Debunking the Speed vs Quality Myth with Empirical Data": https://lnkd.in/dghGfZAM #technicaldebt #codequality #softwaremetrics #refactoring

CodeScene integrates with pull requests to provide feedback and detect code quality issues via an automated code review. It's a popular integration that helps development teams by serving as a quality gate and early feedback loop. 🚀 Set quality gates. Only merge healthy code No matter what baseline you start from, you never want to see a decline in code health. Specify quality gates that trigger in case some code declines in health. 🚀React to potential problems. Get early warnings Get early warnings when new complex code is written, and detect the absence of expected changes that might indicate bugs. 🚀Automate code review process. Save time Prioritize code reviews based on the risk of the commits. CodeScene's risk classification lets you prioritize your code reviews and focus your time where it's needed the most. You can spend less time on reviewing code with low risk and passing quality gates. #codereviews #pullrequest #codequality #technicaldebt

How do you ensure Code Quality in the Age of AI? CodeScene's Lead Data Scientist Enys Mones and Product Owner Peter Anderberg spoke at a recent goto summit about the addressing potential risks with AI coding assistants, and the difference between refactoring vs refuctoring your code base.

Ready for the weekend? As usual, we've prepared a knowledge booster for you! 🎧 How Technical Problems Cause Organizational Friction, by Adam Tornhill, GOTO conference: https://hubs.ly/Q02F2GdZ0 Prioritizing Technical Debt as if Time & Money Matters https://hubs.ly/Q02F2lxr0 #codequality #technicaldebt #softwaremetrics #softwareengineering

What is the business impact of code quality? This quantitative study of 39 proprietary production codebases from various industries and domains by Adam Tornhill and Markus Borg shows that a healthy codebase enables a faster time-to-market while minimizing rework. In their research, Tornhill and Borg show that: "By analyzing activity in 30,737 files, we find that low-quality code contains 15 times more defects than high-quality code. Furthermore, resolving issues in low-quality code takes, on average, 124% more time in development. Finally, we report that issue resolutions in low-quality code involve higher uncertainty, manifested as 9 times longer maximum cycle times. This study provides evidence that code quality cannot be dismissed as a mere technical concern. With 15 times fewer defects, twice the development speed, and substantially more predictable issue resolution times, the business advantage of high-quality code should be unmistakably clear." The full study: Cornell University, Adam Tornhill, Markus Borg, Code Red: The Business Impact of Code Quality -- A Quantitative Study of 39 Proprietary Production Codebases https://lnkd.in/duiibud4 Download the whitepaper here: https://lnkd.in/dYamm5sD #codequality #technicaldebt #refactoring #softwareengineering #softwaremetrics

What are the organizational metrics that you need to get right in any software project? 🚀 In this demonstration, we'll explore essential techniques and key organizational metrics crucial for the success of your software projects. Using the Svelte codebase, a JavaScript framework tailored for open-source development, as our focal point, we'll examine how we can mitigate the risk of the Bus Factor by analyzing metrics that depict the distribution of knowledge within the Svelte codebase. A notable metric we'll examine is "knowledge islands", which indicates the extent of key person dependencies within the codebase. In Svelte's scenario, we observe a relatively low "knowledge islands" metric, heightening the risk associated with the Bus Factor. The "What's my Bus Factor?" metric on the dashboard reveals that a staggering 79% of the code is authored by a single developer. The Bus Factor signifies the number of individuals who can depart before the code becomes incomprehensible and challenging to maintain. In this context, losing the sole developer responsible for 79% of the code would likely result in significant difficulties. To mitigate the risk posed by the Bus Factor, we explore effective techniques and strategies in the tutorial. Additionally, we simulate the consequences of the Bus Factor to gain deeper insights into its impact across various code segments. #softwaremetrics #softwareengineering

Ready for the weekend and perhaps your vacation? Are you looking for some useful podcasts and tutorials to tune into? We've got you covered. 🎧 Fireside Chat "Optimizing Developer Productivity" with Sandro Mancuso and Adam Tornhill https://hubs.ly/Q02F2jSR0 Refactoring With AI In this episode of the Technology Podcast, Adam Tornhill, CTO and Founder of CodeScene, joins Thoughtworks' Rebecca Parsons (CTO Emerita), Birgitta Böckeler (Global Lead for AI-assisted software delivery) and Martin Fowler (Chief Scientist and author of the influential Refactoring book) to discuss all things AI and code. From refactoring and code quality to the benefits and limitations of coding assistants, this is an essential conversation for anyone that wants to understand how AI is going to shape the way we build software. https://hubs.ly/Q02F2jRV0 Happy Friday! 🌸 #aicoding #ai #refactoring #developerproductivity #codequality

Can we successfully refactor code using AI? A benchmark study of the most popular Large Language Models (LLMs) examined their ability to generate code for refactoring. Using over 100,000 JavaScript refactoring samples, the study shows that current solutions only refactor correctly 37% of the time. Using a fact-checking validation layer, researchers introduced a new solution that rejects incorrect refactorings, improving 98% of the remaining code while retaining the original behavior. #aicoding #refactoring #ai #javascript #codequality

How do you know if technical debt is slowing down your development team? CodeScene visualizes each file as a circle, in different colors - green, yellow, and red. The colors reflect our Code Health Metric. 💚 Healthy pieces of code are categorized as green, making them easy to maintain and develop further. 🌕 Yellow code is problematic; it poses risks when working with it, and tasks in these areas will take much longer to complete. 🔴 The red category represents code with a severe degree of technical debt. But how do you know what to prioritize and fix first? ☑️ This is how CodeScene separates itself from other tools on the market. CodeScene can prioritize your technical debt based on how your team works with the code. ☑️ We call these Refactoring targets. CodeScene takes all the red code and looks for prioritized refactoring targets - code that is frequently changed with low code health. 🚀 We analyze a file to understand why the code is unhealthy and identify the code smells that are making it unhealthy, as well as give you recommendations on how you can refactor and remediate these code smells. 🚀 Using CodeScene's high-level dashboards with Code Health KPIs, you can track progress over time, monitor your code health, see where you've started to degrade in code quality, and include this information in your retrospectives. 🚀 What parts of the codebase are getting better or worse? Where do you need to focus, and what parts are starting to become too hard to work with and too expensive to maintain? #technicaldebt #codequality #softwareengineering #softwaremetrics