r/AskProgramming

Do you think my friend has a point here?

My friend works at a small company with only 1 full-time developer and 1 freelance developer. They have a codebase with around 200k LOC but only 2–3 unit tests lol

Their philosophy is basically, “Our end users are our tests.” When employees find bugs, they report them, and the developers fix them.

My friend also argues that many devs write unit tests just to make them pass or achieve test coverage, often focusing on happy paths while ignoring edge cases that could cause real problems.

In his context, the company only builds internal tools/ apps for employees.

He believes that having no unit tests can actually be a reasonable decision for a small company because the time saved by not writing tests can instead be spent shipping features that makes money, and work life eaiser for employees

IMO, I wouldn't say he's wrong based on his context.

But I'd love to hear from you with real experience.

Does my friend actually have a valid point, or is having almost no tests just technical debt waiting to bite them in the ass even though they follow "Our end users are our tests" lol

Ps. the FT dev has worked in a start up only and got like 1-2 yoe

How would I store 3 different answers to the same 3 questions asked using a for loop. I know how to store one answer, but not all three while still using the for loop

I'm working on an app and want to integrate a chatbot that understands users' natural language requests and provides relevant, personalized responses based on existing data.

I already have a MongoDB database containing scraped content from various online sources.

What would be the best approach to build this?

RAG with embeddings and a vector database?

Querying MongoDB directly using filters?

An LLM with tool/function calling?

Or a hybrid approach?

I'm interested in how you'd design the architecture, retrieve relevant information, and generate accurate responses grounded in the available data.

What technologies and architecture would you recommend, and why? I'd appreciate hearing about your experience building similar systems.

Hey guys, I often find interesting projects on GitHub. Getting them running is usually fine, but when I want to understand how something works or make my own changes, I get completely lost in the codebase.

Mature projects have so many abstractions, design patterns, error handling, and logic spread across different files that I never know where to start or how deep to go.

I once spent a whole week using AI to walk me through a project starting from main(). I kept diving into details, and by the end, I barely remembered anything.

Someone also suggested drawing flowcharts to understand the code, but the more I drew, the bigger and messier they became.

How do experienced developers approach unfamiliar codebases when they actually want to understand and modify them?

How do you decide what to read, what to skip, and when you understand enough to start making changes? And has AI genuinely helped you with this?

Any advice or personal experiences would be greatly appreciated. Thanks in advance!

Hey everyone,

I was taking a look at the TIOBE Index today. I hadn't checked it in a while, and I was surprised to see how much Python has dropped.

It's down by roughly 8 percentage points compared to a year ago, which seems like the first really significant contraction after years of pretty consistent growth.

What's even more interesting is that I don't see another language gaining a similar amount of ground.

I don't use Python myself, so I'm curious: what do you think is behind this decline? Is it actually meaningful, or is it mostly an artifact of how the TIOBE index is calculated?

I’ve been seeing a lot of word around about the “design engineer” in software. I understand it’s a vague concept and I’m not that interested in the flare of the label. What I do want to understand is how a frontend dev can have a better understanding of interfaces with the ability to reimagine conventions or instate new ones.
Is there a place to start?

I’m not a beginner programmer, but I’m relatively new to scientific programming. I’ve recently started doing scientific research with a professor, and a significant part of my work involves writing simulations, modeling physical systems and mathematical equations computationally, and developing algorithms to analyze or reproduce these systems.

I’m interested in becoming much stronger at this side of programming, particularly in areas like numerical methods, computational physics, mathematical modeling, simulation, and scientific computing.

For those of you with experience in scientific programming, what would you recommend as the best way to build these skills? I’d especially appreciate recommendations for textbooks, courses, projects, libraries, or other resources that helped you make the transition from general programming to scientific/computational programming.

I’m comfortable with programming fundamentals, so I’m primarily looking for resources that go beyond the basics and focus on the actual mathematics, algorithms, and computational techniques behind scientific programming.

Any advice or recommendations would be greatly appreciated!

Curious about this, especially from people early in their careers (or who remember being there).

Most of us learn to code by building things from scratch: tutorials, class projects, personal apps. Then the first real task at a job or internship is usually "here's the existing codebase, fix this bug" or "add this feature."

When that happened to you, what was actually the hardest part?
- Not knowing where to start reading?
- Understanding how the files/folders connect?
- Figuring out where the bug actually lives?
- Being afraid to break something?
- Something else entirely?

And if you got past it, what helped most? Would love to hear from both juniors and seniors.

Hi! I'm working on a personal project where I'm making my own 2D animation software.

The idea is to eventually have features such as a drawing canvas, layers, a timeline, brushes, vector and bitmap tools, and animation features. I'd like it to run on Windows, with the possibility of supporting other platforms in the future.

I'm currently trying to decide which programming language and framework would be the best fit for this kind of application.

For people who have experience developing graphics software, animation tools, drawing applications, or similar programs:

What programming language and framework would you recommend, and why?

I'm particularly interested in rendering performance, canvas/drawing capabilities, GPU acceleration, handling larger projects, and keeping the codebase manageable as the software grows.

I'm not looking for someone to develop it for me. I'm mainly looking for advice before I get too far into the project.

Thanks!

Hello everyone.

I have begun developing an engine for binary/hex manipulation in C#. I've only ever coded in CMD situations and Python - so an absolute amature - but i'm learning the flow of C#.

The original idea came about due to me wanting to learn ECU mapping, but that is an expensive venture in itself. A WinOLS 5 licence from EVC Technology is £1,250, and the definition files used to describe binary addresses, maps, scalars and other ECU data can also be extremely expensive. While this may not be a huge issue for dedicated tuners who use the software professionally, it sure as hell is a lot for DIYers like me.

The main goal of this project is to make binary manipulation and ECU calibration more accessible to people who are learning. I want the software to be useful not only as a tool for editing files, but also as a way of understanding what is actually happening within a binary. Rather than hiding everything behind a complicated interface, I want to provide tools that allow users to explore addresses, data structures, scalars, maps and checksums while learning how they work.

The project will be developed with support for different uses in mind, not just ECUs, while keeping the underlying engine as flexible and reusable as possible. ECU files are currently the main focus because that's what originally motivated me to start the project, but there is no reason the underlying engine couldn't eventually be used for other types of binary data.

Currently, I'm at a stage where I have a GUI and can read .BIN files in hexadecimal. Of course, there is still a lot of work needed before the actual manipulation and editing side of things is properly implemented, but I'm willing to put the work in.

However, I'm in need of some suggestions and information on what I may need to implement, and what features or file formats I should support.

Since I'm developing this alone, I don't exactly have a team sitting behind me saying, “Oh, you should add support for SNES ROM dumps!” or whatever.

So if anyone has experience with binary manipulation, ECU calibration, ROM hacking, reverse engineering, or anything else involving binary files, I'd be interested to hear what features you think would be useful.

Suggestions for file formats, definition formats, checksum systems, visualisation methods, editing tools, ECU support or even completely unrelated uses for the engine are all welcome.

The project is still in its early stages, but I'm hoping to build something that is genuinely useful for learning and experimentation, while keeping it free and accessible.
The power to do these sort of things should be fed to the world for free, not hidden behind a 1 year license that costs as much as a new smart fridge.

TIA for any suggestions.

The Github repo is here

Hey everyone,

I’m an Android developer with \~5 years of experience. For the last 8 months, I’ve been coding almost entirely with Claude Code.

I’ve been very productive, delivered impressive results, and my company is happy. But I feel like I’m not learning as much anymore. There are parts of my codebase that I barely understand because Claude implemented them, even though they work perfectly.

Recently, I had a technical interview with some relatively simple coding. My mind completely froze and I ended up quitting.

It made me realize I might be becoming too dependent on AI.

Has anyone experienced this?

How do you balance using AI heavily while still maintaining and improving your actual coding skills?