Adam Tornhill

As generative AI is expected to increase global code volumes, the importance of maintainability from a human perspective will become even greater. Various methods have been developed to identify the most important maintainability issues, including aggregated metrics and advanced Machine Learning (ML) models. This study benchmarks several maintainability prediction approaches, including State-of-the-Art (SotA) ML, SonarQube's Maintainability Rating, CodeScene's Code Health, and Microsoft's… Visa mer

As generative AI is expected to increase global code volumes, the importance of maintainability from a human perspective will become even greater. Various methods have been developed to identify the most important maintainability issues, including aggregated metrics and advanced Machine Learning (ML) models. This study benchmarks several maintainability prediction approaches, including State-of-the-Art (SotA) ML, SonarQube's Maintainability Rating, CodeScene's Code Health, and Microsoft's Maintainability Index. Our results indicate that CodeScene matches the accuracy of SotA ML and outperforms the average human expert. Visa mindre

This paper received the prestigious Best Paper Award at the International Conference on Technical Debt 2024.
Our research explored how the quality of source code affects business outcomes. Key questions include how code health relates to defect counts and development time, and how different levels of code health impact value creation for the business. From there we developed a statistical model which lets software companies estimate their Return-On-Investment if code quality is improved.

Jack the Ripper and legacy codebases have more in common than you’d think. Inspired by forensic psychology methods, you can apply strategies to identify problems in your existing code, assess refactoring direction, and understand how your team influences the software architecture. With its unique blend of criminal psychology and code analysis, Your Code as a Crime Scene arms you with the techniques you need to take on any codebase, no matter what programming language you use.

The… Visa mer

Jack the Ripper and legacy codebases have more in common than you’d think. Inspired by forensic psychology methods, you can apply strategies to identify problems in your existing code, assess refactoring direction, and understand how your team influences the software architecture. With its unique blend of criminal psychology and code analysis, Your Code as a Crime Scene arms you with the techniques you need to take on any codebase, no matter what programming language you use.

The original Your Code as a Crime Scene from 2014 pioneered techniques for understanding the intersection of people and code. This new edition reflects a decade of additional experience from hundreds of projects. Updated techniques, novel case studies, and extensive new material adds to the strengths of this cult classic. Visa mindre

This report is the conclusion of a benchmark study of the most popular Large
Language Models (LLMs) and their ability to generate code for refactoring
tasks. We aim to illustrate the current standards and limitations, and seek to
show new methodologies with higher confidence results.

This research paper establishes a correlation between code quality and a business impact. This study provides evidence that code quality cannot be dismissed as a 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.

Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that’s just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the… Visa mer

Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that’s just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the techniques build on behavioral data that you already have: your version-control system. Join the fight for better code! Visa mindre

Jack the Ripper and legacy codebases have more in common than you’d think. Inspired by forensic psychology methods, this book teaches you strategies to predict the future of your codebase, assess refactoring direction, and understand how your team influences the design. With its unique blend of forensic psychology and code analysis, this book arms you with the strategies you need, no matter what programming language you use.

Simplicity, power and consistency in the age of the web.

Patterns in C is a collection of idioms, design and architectural patterns in the C programming language. The book highlights the value of patterns as an excellent tool for communication and reasoning. The book provides a C programmer with techniques to benefit from the growing body of knowledge captured in patterns.