Coder Legion - Recent posts tagged sustainablesoftwareengineering

Before optimizing code, optimize the process

Wed, 14 Jan 2026 13:43:19 +0000

For a long time, I thought improvement in tech mainly meant better code.
Cleaner architecture.
Faster queries.
Lower latency.
Better models.

But recently, while working on process optimization in a real business environment, I realized something uncomfortable:
Most inefficiency doesn’t start in software.
It starts before software.
In workflows.
In approvals.
In unclear ownership.
In unnecessary steps.
In tools chosen without a real problem to solve.

I’ve seen processes where the real system wasn’t the application — it was a chain of spreadsheets, emails, manual reviews, and duplicated work.
And no matter how good the software was, it was being built on top of something already heavy.

That experience changed how I think about responsible and sustainable software.

We often ask:
Can we build it?
Can we automate it?
Can we scale it?

But much less often do we stop to ask:
Is this process worth scaling at all?

Because if a process is unclear or wasteful, software doesn’t fix it.

It only makes it run faster.
The more I work on optimization, the more I’m convinced that:

Responsible software starts before software.

It starts with understanding:
what real friction we’re removing
what human effort we’re saving
and what resources we’re about to commit
Sometimes the most responsible decision isn’t to build a smarter system.

It’s to build a lighter one.
Or even to remove steps instead of adding tools.

Optimization taught me that a big part of sustainability — technical and human — comes from not building what we don’t need.

And that’s a lesson I didn’t learn from code.
I learned it from processes.

I’d love to hear how others think about responsible and sustainable systems.

Don’t hesitate to reach out or share your perspective.

GitHub: github.com/fadydesoky

I No Longer See Software as “Just Software”

Fri, 09 Jan 2026 15:32:32 +0000

How research and green software engineering changed the way I see code

For a long time, I thought software engineering was only about features, performance, and shipping products.

Today, I realize it’s much deeper than that.

A small shift in perspective

I used to measure good software by how fast it runs, how clean the UI looks, and how many users it serves.

But after working on topics like GNSS-based traffic modeling and green software engineering, something changed.

I started asking different questions:

• How much energy does this system consume?

• What invisible resources are being wasted?

• Who is affected by the decisions we make in code?

That’s when software stopped being “just software” to me.

Software writes real-world consequences

When you model traffic data, you’re not just optimizing routes — you’re influencing pollution, time, safety, and city behavior.

When you analyze software energy consumption, you’re not just profiling code — you’re touching sustainability, infrastructure load, and environmental impact.

Code doesn’t stay on the screen.
It moves into streets, servers, electricity grids, and human lives.

⚙️ Engineering is no longer neutral

Every design choice has a cost.

• One inefficient loop multiplied by millions of users

• One always-on service running 24/7

• One poorly planned system scaled too fast

Software engineers are now part of global systems, not isolated applications.

And whether we notice it or not, we are shaping:

• energy consumption

• digital behavior

• economic decisions

• and even environmental outcomes

What this changed for me

Today, when I write or analyze software, I don’t only think about:

✔️ “Does it work?”

✔️ “Is it fast?”

I also think about:

✔️ “Is it responsible?”

✔️ “Is it efficient beyond performance?”

✔️ “Is it solving the right problem?”

Final thought

Software engineering is no longer just about building products.

It’s about designing systems that live inside the real world.

And once you truly see that —you can’t unsee it.

What questions do you have about responsible software? Drop a thought below — I’d love to hear your take.

You can find me on GitHub: https://github.com/fadydesoky

My Research Journey in Green Software and Urban Mobility — Fady Desoky Saeed Abdelaziz

Thu, 08 Jan 2026 12:08:21 +0000

This article was originally published on dev.to: https://dev.to/fadydesokysaeedabdelaziz/my-research-journey-in-green-software-and-urban-mobility-fady-desoky-saeed-abdelaziz-2img

I am Fady Desoky Saeed Abdelaziz, a Software Engineering Undergraduate, and research-oriented data analyst with a strong interest in Green Software Engineering, software energy consumption analysis, and urban mobility systems.

Over the past period, my research work has focused on understanding how software systems consume resources and energy, and how data-driven analysis can support more sustainable and efficient software development practices.

One of my key research contributions explores GNSS-based urban traffic modeling, where I analyzed traffic congestion patterns using real-world GNSS data. This work aims to provide practical insights into urban mobility challenges by modeling traffic behavior and identifying patterns that can support better planning and optimization.

In parallel, I worked on research related to Green Software Engineering, specifically analyzing software resource and energy consumption. This research focuses on measuring how software systems utilize CPU, memory, and other resources, and how these metrics can be used to guide more energy-efficient software design decisions.

Through these projects, I developed a strong interest in turning raw data into meaningful insights. My approach is practical and research-driven, combining software engineering principles with data analysis techniques to address real-world problems.

Questions I’m Exploring Next
• How can energy-efficient code be automated?
• How can GNSS modeling help smart cities better?

I share my research and technical work across several platforms:

ResearchGate: https://www.researchgate.net/profile/Fady-Desoky-Saeed-Abdelaziz
Academia.edu: https://sadatacademy.academia.edu/FadyDesokySaeedAbdelaziz
Google Scholar: https://scholar.google.com/citations?view_op=list_works&hl=en&hl=en&user=kmwYy3UAAAAJ
ORCID: https://orcid.org/0009-0006-0629-7396
GitHub: https://github.com/Fadydesoky
Loop: https://loop.frontiersin.org/people/3322416/overview

I plan to use this space to share insights, research experiences, and technical projects related to Green Software Engineering, software energy analysis, and urban mobility modeling.

Green Software Engineering: Measuring Energy, Not Just Performance

Wed, 07 Jan 2026 20:56:20 +0000

This article was originally published on dev.to: https://dev.to/fadydesokysaeedabdelaziz/green-software-engineering-measuring-energy-not-just-performance-3i00

We measure speed, but what about the energy?

Most software engineers measure success using performance metrics. We optimize for speed, latency, and throughput, assuming that faster software automatically means better software. However, in 2026, an equally important question is often overlooked: how much energy does our software actually consume?

Faster software does not always mean more energy-efficient software. High CPU utilization, excessive memory usage, and inefficient execution patterns can significantly increase energy consumption, even in systems that appear highly optimized from a performance perspective. Optimizing solely for performance ignores a critical sustainability dimension that modern software systems can no longer afford to overlook.

Green Software Engineering focuses on building software that minimizes energy consumption and resource waste while maintaining acceptable levels of performance. It treats energy as a first-class metric, alongside traditional software quality attributes such as performance, reliability, and scalability. Instead of asking only how fast a system runs, Green Software Engineering encourages engineers to ask how efficiently that system uses computational resources.

Energy consumption is not always directly measurable at the hardware level, especially in cloud-based or shared environments. However, software engineers can still analyze energy-related behavior through indirect indicators such as CPU and memory utilization patterns, execution time, workload characteristics, and resource allocation strategies. These indicators provide valuable insights into how software design and implementation choices impact overall energy usage.

In my recent research work, I focus on analyzing software resource usage and energy consumption to support the development of more sustainable software systems. By combining data analysis with software engineering principles, it becomes possible to design systems that balance performance requirements with energy efficiency goals in a practical and measurable way.

Green Software Engineering is not a passing trend. It represents an essential evolution in how we design, evaluate, and maintain software systems. Understanding and measuring energy consumption today will play a key role in shaping the sustainability of software tomorrow.

Related work and experiments:
https://github.com/Fadydesoky/green-software-energy-analysis

The 32% Dividend: Why Code Efficiency is the World's Most Powerful Green Energy Source

Thu, 11 Dec 2025 05:01:00 +0000

Right now, the entire digital world is built on a fundamental, structural flaw that is costing the planet an absolute fortune in power and money.

Look around. Global electricity demand is surging at a reckless pace—far faster than we can build clean energy to meet it. By 2027, the world’s consumption is expected to jump by an unprecedented 3,500 Terawatt-hours (TWh)—that’s like adding an entire Japan’s annual energy demand, year after year.

The biggest pressure cooker? Data centers, driven by the explosive demands of Generative AI, are projected to double their electricity consumption to over 1,000 TWh by 2026. They are fighting local communities for power, and they're cooking themselves alive.

Here’s the truth: Your code is the problem, and your code is the only solution.

The Technical Rebellion: Capturing the 32% Dividend

That soaring energy demand? A huge chunk of it is waste. It’s not your hardware failing; it’s software inefficiency that forces the CPU to burn power needlessly on processes like memory Input/Output (I/O) and sloppy Garbage Collection (GC). This structural waste is where we strike.

Research has already proven that by rigorously optimizing the power-hungry operation of memory networks and data flow, an average 32% reduction in power consumption is achievable. This isn't speculation—it's a high-leverage technical benchmark proven in specialized labs.

Our mission is to take that research-grade, hard-won 32% Dividend and make it universal. Our O(1) Compute technology—starting with the publicly available, highly optimized Near O(1) FSM_API—is engineered to align perfectly with the CPU, making power efficiency the default, not the afterthought. We turn concepts confined to academic papers into the foundation of a Dynamic Software architecture.

This is the coder’s mandate: We transition software from prioritizing peak throughput at any cost to prioritizing power efficiency per useful transaction.

⚡ The Triple-Threat Impact: What The 32% Really Means

When you inject 32% computational efficiency into the global Information and Communications Technology (ICT) load, the results are nothing short of revolutionary. This isn't just about saving money; it's about solving a global infrastructure and climate crisis.

1. The Climate and Grid Lifeline: Guaranteed TWh Savings

The 32% efficiency dividend acts as a guaranteed, instant source of Zero-Carbon Energy Capacity, offering critical relief to a grid struggling to keep up with digital growth.

Metric	Baseline (2024 Estimate)	The O(1) Solution	Ultimate Impact
Global ICT Annual Energy Load	1,200 TWh	384 TWh Avoided	A 32% permanent reduction in digital energy demand.
2024 Global Electricity Demand Increase	1,172 TWh	384 TWh Offset	Eliminates 32.7% of all new global electricity demand in 2024.
Energy Avoided Method	Marginal Fossil Fuel Generation	Guaranteed Zero-Carbon, Zero-Loss	Bypasses all electrical system energy losses (generation, transmission, distribution).

2. The Data Center Multiplier: Total Facility Power Reduction

Data centers pay for inefficiency twice: once for the compute (IT equipment is 42% of power draw) and again for the cooling systems (37% of power draw).

A 32% reduction in the IT load translates to a compounded power reduction across the entire facility:

System	Inefficiency Reduced	Power Savings Multiplier	Real-World Benefit
Data Centers (Facility Wide)	IT Load (32%), Cooling Load (32%)	~32% Total Facility Power Reduction	Provides superior, faster energy reduction than expensive hardware retrofits (like liquid cooling).

3. The End-User Battery Revolution: The 47% Multiplier

For every developer, gamer, and mobile user, the most visible win is battery life. When a device’s consumption is reduced by 32%, the active battery runtime is extended by approximately 47%.

Device Type	Baseline Active Runtime	Efficiency Gain	Projected New Runtime
Average Laptop	6.0 hours	32% Reduction	~8.8 hours
Average Smartphone	15.0 hours	32% Reduction	~22.1 hours

This means fewer charging cycles, a massive reduction in battery degradation, a longer device lifespan, and a much-needed decrease in global e-waste.

⚙️ The Coder's Mandate: Join the Digital Rebellion

The successful realization of the 32% Dividend rests entirely on a systemic shift in how we engineer code. We are the critical infrastructure now, and the engineering paradigm must evolve to reflect the acute energy pressure globally.

This isn't a secret held hostage by the giants. This is a Digital Rebellion you can join right now:

The Blueprint is Free: Our groundbreaking FSM architecture—the Near O(1) foundation of this movement—is Free and Open Source (FOSS) under the MIT License. You are invited to study it, hack it, and use it immediately to begin building structurally efficient applications.
Maximum Reach: This pure C# technology is ready for all your deployments, reaching everything from the newest cloud platforms all the way back to the venerable .NET Framework 4.7 on legacy systems.
Shameless Plug for Unity: For our fellow Unity developers, this same FSM system is already integrated and available for you to plug-and-play into your games and simulations on the Unity Asset Store.

The mathematical evidence is absolute. By integrating this core efficiency into your projects, you are taking a stand for a healthier grid, a cooler planet, and a more sustainable digital future. You are building the social and technical pressure required to force the entire industry to beg for help in becoming less wasteful.

We must make energy waste visible, measurable, and an unacceptable engineering constraint.

The rebellion begins with your code.

Resources & Code:

NuGet Package (Non-Unity Core):
TheSingularityWorkshop.FSM_API

GitHub Repository:
https://github.com/TrentBest/FSM_API

Simple Demos Repository (Run the Stress Test):
https://github.com/TrentBest/SimpleDemos

Support Our Work:

Patreon Page:
https://www.patreon.com/c/TheSingularityWorkshop

Support Us (PayPal Donation):
https://www.paypal.com/donate/?hosted_button_id=3Z7263LCQMV9J

We'd love to hear your thoughts! Please Like this post, Love the code, and Share your feedback or what you've built with the API in the comments.