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Discover how static code analysis serves as a strategic tool to prevent technical debt accumulation in software development. Explore the scientific approach of static analysis tools in identifying and mitigating potential sources of technical debt, empowering software engineering managers and developers to uphold code quality and streamline development processes.

In this article, we explore strategies for reducing code complexity to improve collaboration, efficiency, and project outcomes, ensuring a streamlined and efficient codebase.

Learn how to effectively manage technical debt in your codebase and transform chaos into clarity. Discover strategies for identifying, prioritizing, and resolving technical debt, ensuring a cleaner, more efficient codebase for improved productivity and innovation.

In this article, we delve into what code complexity is, how to measure it, and explore effective strategies to reduce it from the perspective of new and old technologies.

As projects scale up, so does the challenge of maintaining code quality, minimizing bugs, and ensuring scalability. This article explores how AI can help in reducing code complexity.

This exploration delves into the scientific methodologies behind identifying technical debt, emphasizing the role of code smells as indicators and the application of static code analysis tools.

In the software development realm, the future promises both challenges and innovative solutions for managing technical debt. As software engineering continuously evolves, the intersection of emerging technologies and progressive practices is reshaping how we handle the complexities of technical debt.

In the dynamic sphere of software development, grappling with technical debt in legacy systems is an imperative challenge. Software engineering directors, managers, and engineers face the intricate task of mitigating technical debt accumulated in aging codebases.

This guide explores proactive strategies to prevent the creation of technical debt, emphasizing the importance of code reviews, automated testing, and the principles of clean code.

This article delves into the estimated global cost of technical debt and explores strategies for preventing its accrual, with a focus on the importance of clean code.

In this article, we'll explore the significance of clean code in preventing technical debt and discuss the role of AI code review tools in maintaining code cleanliness.

In the realm of software development, accumulating technical debt is a pervasive challenge. Technical debt refers to the compromises made during the development process, often leading to suboptimal code quality, bugs ...

In today's data-driven world, networks and graphs are fundamental for modeling complex relationships and dependencies. Graph Neural Networks (GNNs) have emerged as a transformative approach to understanding and analyzing graph-structured data.

This blog post delves into the concept of technical debt in software development and how AI code reviews can proactively prevent it. It emphasizes the benefits of AI code reviews and demonstrates their role in maintaining code quality and reducing development costs.

In this beginner's guide, we will demystify AI code reviews, explaining what they are, why they matter, and how they differ from traditional code reviews.

In the ever-evolving landscape of software development, where innovation is relentless and demands for efficient, high-quality code are unceasing, the role of AI in streamlining code review processes has become pivotal.

In the rapidly evolving landscape of software development, the integrity and quality of code are paramount - AI code review is here to help.

While manual code reviews have been a staple in the software development process, they are not without their challenges.

As Metabob's AI code review extension for VS Code started supporting JavaScript, we analyzed an open-source e-commerce application for testing. This blog covers example detections from the analyzed app.

Software engineers and developers are typically among the most expensive labor forces within organizations. The average base salary for software engineers in San Francisco was $167K a year. Because of this, it is unsurprising that one of the main priorities...

As software developers and data scientists, we have had whole weeks burnt on codebase maintenance. We've had bugs in our codebase that dated back to when ...

Debugging Python code is often a challenging and time-consuming task. This article explores tooling that can help developers to debug Python code in VS Code more effectively.

Today, we sit down with Metabob DevOps Manager, Sako Mammadov, to hear about his journey to Metabob and why he feels Metabob’s tool is so influential.

Upon doing research for this post, we were thinking of the ways friends at certain FAANG companies talked about their work. Often nonchalantly, they describe their days as mostly consisting of working 3-4 hours, checking off their work tickets and punching out 40 full-time hours...

When talking to different members of engineering teams through research efforts at work, it has become apparent that code reviews take an awful lot of time from engineers’ daily work hours...

Working with Compilers can come with its learning curves. To truly get acclimated and to make sure that you are translating languages accurately and with little uncertainty, we’ve compiled (pun very much intended) a list of must-know vocabulary to get you started on the right foot!

Coding has become the necessary currency of the new job market. From high budget campaigns with former President Barack Obama encouraging Americans to learn computer science, to Apple’s new collaboration with the Boys & Girls Club of America to launch a new coding program, computer science is being taught earlier and earlier and has now become an essential part of a well-rounded education.

A topic model is a type of algorithm that scans a set of documents (known in the field of Natural Language Processing/NLP as a corpus), examines how words and phrases co-occur in them, and automatically “learns” groups or clusters of words that best characterize those documents. These sets of words often appear...

As we all are aware, debugging and maintaining code is a daunting and time consuming task, especially when you are working on a number of different projects. Metabob helps you to identify and fix bugs as quickly as possible.

Software maintenance is an expensive activity in the software lifecycle. Last minute change requests push developers to make “band-aid fixes” setting aside good design and implementation...

During the current times of software development, it is rarer and rarer for bugs to make it all the way to production. However, this doesn’t mean that organizations are not paying a high price for fixing bugs.

Coding sprints are one of the best ways to improve software development consistently and at a good pace, without making incredibly big changes all at once. This article is going to answer some questions one may have about coding sprints, how to plan them, and their relevance.

There are dozens of developer productivity tools on the market looking to ensure productive, effective metrics for dev teams big and small...

After being a developer for so long - Fortran in 1979 followed by Pascal, C, Java, and settling on python in 1997 - I’m no stranger to memory leaks and spikes. I still love hunting down bugs . . .

Previously, we mentioned the need for Topic Modeling. One common application is an email filter. You train the model by feeding it many emails, each one labeled as “spam” or “urgent” or “work-related” or “promotion” or “social.”  . . .