Life as a Random Oracle Model: How We Cache Our Social Interactions

Understanding the Random Oracle Model

For those who are new to this term "Random Oracle Model," let me give a gist.

Given a query, this model returns a result. But how does it return? If it has already seen the query, it just returns the result in O(1) time; otherwise, it does a lookup operation in evaluating and returning the result.

It can be interpreted as a form of permanent caching and is used in almost all cryptographic algorithms. For more info, check this Wikipedia article.

The Human Random Oracle

Then I thought about the way we live our lives. It sounded similar to me. Maybe these models were invented by those who were able to model these data structures based on their personal life—or I'm just a douche :)

Anyway, here's the thing: everyone should have similar examples in their life. We come across many people in our lives. We maintain a cache for those people with whom we want to always move or respond. For others, it's just a random response or no response.

Random Oracles in Interviews

Consider you're attending an interview. The interviewer asks a question which you've already come across. Now what would you do? Would you behave like a random oracle model? :)

Would you answer the question instantly as you know the solution already, or drag out the time doing fake thinking, returning some false positives similar to a bloom filter... and finally give the solution?

I would suggest notifying the interviewer that you've already come across this question and use ROM in your head to provide the answer directly. But many people don't do that. They act like they've seen it for the first time.

To be frank, I was educated by my undergrad college seniors not to respond quickly though I knew the answer...

Social Caching and Response Mechanisms

Let's consider another example: your friend introduces you to their friend. Do we immediately consider the new person a friend? I guess not. Most of us just remember them, and when we see them on another occasion, we greet them and that's it. We maintain a cache for this person, but we're responding to them with answers which may or may not satisfy them.

A Case Study in Social Oracle Failure

Recently, one of my friends came across this situation. Let's use notations for privacy:

Let A, B, C be three persons defined as follows:

• A - My friend
• B - A's friend
• C - B's friend who is not A

The following events took place:

1. C had gone to his home country for vacation.
2. A had asked B to get some items from persons who are returning from that country.
3. B informs C.
4. C brought those items as requested by B.
5. Now C brings those items back.
6. A queries B and reaches C's house.

Now, whenever someone visits your house, it's common to greet them with drinks or sweets, learn about them, and rejoice with them if there are any common moments. In this case, A was taken aback by C's behavior:

C: "Oh. It was you. Good. Good... Okay. Here is your item which was requested by B. Have it." A: "Thanks for bringing it. [Some pleasant conversation]"

// C and A stare at each other for some time. A expects C to welcome him and ask him to take a seat.

C: "Make yourself comfortable. Take some sweets [pointing to some room]." C leaves the scene. A: Perplexed on what to do, leaves.

Why did C behave like that?

1. Probably C had already known about A that he is difficult through some other person D.
2. He was so busy that he didn't have the courtesy to explain to A.
3. He himself observed A and made a quick judgment. ...or whatever.

Maybe you can justify that I'm in the wrong here, so is A, and that's the reason C behaved like that.

If any of the above cases were true, C should not have brought those items for A when informed by B. It's better to avoid getting committed rather than taking on such tasks and making the situation awkward.

This could be compared with stories a programmer takes for implementation: either take a requirement and implement it correctly, or don't take it at all.

The Courtesy Protocol

Random Reader: "I already have lots of friends. I don't want anyone new in my group." My answer: "Yeah, buddy. Sure. But one should have the courtesy to politely decline the new person."

Is that the reason Facebook came up with lists, groups (secret, closed, etc.), and the ability to block updates from people who are still on your friend list? :)

Coming Back to the Original Theory

Are we violating the Random Oracle Model in our lives?

Now you might ask why we need to follow the Random Oracle Model. I'm not advising anyone to follow this model. I just noticed that our life design patterns are akin to this.

I guess all of us are selfish in one way or another.

We use the model only when it benefits us, or we behave in a way similar to existing models :)

It can be business, personal, or anything.

The Ultimate Question

So one more question arises: Is life deterministic enough to be accommodated into some model?

What do you think about this?

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[For readers who made it through this philosophical exploration, thank you very much for visiting my blog. Please post comments on what you feel as well as suggestions so that I can improve my writing.]

Is Life Deterministic or Non-Deterministic?

I feel life is a deterministic-polynomial time solvable Turing machine :P in the way it has been to me till this time.

Things happen which have a trigger in the past and the loop keeps on running. Oh yeah, who pulled the trigger?? Some unknown void pointer which happens to be the unseen God :)

Don't think I'm an atheist :)

My mind core dumped and I thought I would post the stack trace here :)

Sarcasm: The Ultimate Social Encryption Algorithm

Sarcasm is an encryption technique used by relatively smart people to keep idiots out of their conversations. It may also be used to belittle and mock them.

The encryption and decryption technique of sarcasm is inbuilt in many humans.

Some humans are capable of encrypting a message using sarcasm in O(1) time, while some take O(n^2), where n is the number of characters in the message. Some idiots are also capable of encrypting messages with sarcasm, but it is very rare, as they need O(2^n) time in most cases to encrypt a message of length n.

Decryption, on the other hand is a bit tedious. The most brilliant minds on this planet take about O(log n) time to decrypt any sarcastic message in worst case; although the average time needed by them is still O(1). The average intelligent being takes about O(n^3) time to decrypt a sarcastic message. Idiots on the other hand, are completely off chart when it comes to decryption. The smartest idiots are capable of decrypting sarcastic messages in O(5^n) time, because they're counting with fingers on one hand only; although the average idiot is not capable of deciphering a sarcastic message in his/her lifetime.

It's a sick sad world with intelligent people keeping their information and techniques secret encrypted with sarcasm and idiots can't have access to it to become intelligent even if they want to. Ah, the irony of it!

No, this is not meant to demonstrate sarcasm.

Software Diversity as a Security Measure: Can Unique Executables Prevent Attacks?

We're constantly hearing news about cyberattacks on major companies like Facebook, LinkedIn, and Twitter. One common vulnerability often cited is issues with the Java plugin that allow attackers to penetrate systems. While Oracle regularly releases patches, I've been wondering: are these just temporary fixes, or do we need more fundamental approaches to software security?

Last month, I had the opportunity to attend a fascinating colloquium by Dr. Michael Franz from UC Irvine, held at UT Dallas. His talk, titled "Software Immunity via Large Scale Diversification," presented a novel approach to cybersecurity that got me thinking about the future of software protection.

The Concept: A "Multicompiler" for Software Diversity

Dr. Franz and his team have been investigating compiler-generated software diversity as a defense mechanism against attacks. The core idea is surprisingly elegant: imagine an App Store containing a diversification engine (a "multicompiler") that automatically generates a unique version of every program for each user.

Here's the fascinating part - all these different versions of the same program behave identically from the end-user's perspective, but they implement their functionality in subtly different ways under the hood. The compiler introduces variations in memory layout, code sequences, and other implementation details based on a seed value (similar to how cryptographic algorithms work).

Why This Approach Could Be Revolutionary

The security benefits of this approach are compelling:

1. Attack Dilution: Any specific attack would succeed only on a small fraction of targets since each user has a uniquely compiled version.
2. Increased Attack Complexity: Attackers would need to develop a large number of different exploits and would have no way of knowing which specific attack would succeed on which target.
3. Resistant to Reverse Engineering: This approach makes it much more difficult for attackers to generate attack vectors by reverse engineering security patches.

According to Dr. Franz, his team has already built a prototype multicompiler capable of diversifying large software distributions such as the Chromium web browser or a complete Linux distribution. He mentioned that this technique is currently being deployed at Mozilla.

Practical Challenges

While the concept is promising, it does introduce some practical challenges:

Patch Management: The process makes patching more complex, as updates need to be customized for each user. Companies would need to track the versions running for every user, retrieve the seed used in the original executable, and generate a new executable based on either the existing seed or a new one.

Error Reporting: When every binary is unique, how do you handle error reports? Traditional error reporting relies on identical binaries to identify patterns.

Resource Requirements: Generating unique versions for millions of users could require significant computational resources.

Could This Really Work?

The question remains: can we really enhance security by creating unique executables for every user? The approach certainly introduces a new dimension to security - moving from a monoculture where all systems share the same vulnerabilities to a diverse ecosystem where attacks can't easily scale.

It reminds me of biological diversity in nature, where genetic variation helps populations survive diseases that might otherwise wipe out a genetically uniform group.

The concept leverages a fundamental asymmetry in cybersecurity: attackers need to find just one vulnerability to succeed, while defenders need to protect against all possible attacks. By introducing diversity, we force attackers to develop multiple exploits for the same vulnerability, significantly raising their costs and reducing their success rate.

Dr. Franz and his team have clearly thought through various aspects of this approach, but as with any security innovation, time will tell how effective it proves in real-world scenarios.

What's Your Take?

I'm curious about your thoughts on this approach. Could software diversity be the key to building more resilient systems? What other challenges might arise in implementing such a system at scale?

Let's observe how this develops as time progresses. Perhaps we're witnessing the early stages of a fundamental shift in how we approach software security - moving from a model of "patch and hope" to one of built-in resilience through diversity.

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For those interested in learning more, you can find Dr. Michael Franz's research at http://www.ics.uci.edu/~franz/.

Elegant Software Design: Principles for Maintainable Applications

In my journey as a software engineer, I've discovered that writing code that merely functions is the easy part. The real challenge lies in crafting code that remains maintainable and adaptable as systems evolve. Today, I'd like to share some design principles that have proven invaluable when building robust applications.

The Foundation of Good Design

At its essence, good software design is about managing complexity. As systems grow, complexity naturally increases. Without intentional design decisions, this complexity becomes overwhelming, leading to bugs, development friction, and technical debt.

As Ralph Johnson once said, "Before software can be reusable, it first has to be usable." This simple statement captures the importance of thoughtful design in creating sustainable software systems.

SOLID Principles

The SOLID principles provide an excellent framework for creating maintainable code. Let's explore each one:

Single Responsibility Principle

A class or module should have only one reason to change. This principle encourages us to design components that are focused on a single concern, making them easier to understand, test, and maintain.

When I first started programming, I often created large, monolithic classes that handled multiple concerns - validation, database operations, email notifications, and logging all in one place. Eventually, I learned that separating these responsibilities into distinct components made my code significantly more maintainable.

For example, instead of a massive UserManager class that handles everything, we might have a UserValidator, UserRepository, NotificationService, and ActivityLogger, each with a clear, focused responsibility.

Open/Closed Principle

Software entities should be open for extension but closed for modification. This means we should be able to add new functionality without changing existing code.

This principle has saved me countless hours of debugging. By designing interfaces that can be extended with new implementations, I can add features without risking regression bugs in existing functionality.

Consider payment processing - if we design our system properly, adding support for a new payment method (like cryptocurrency) shouldn't require modifying our existing credit card or PayPal processing code.

Liskov Substitution Principle

Subtypes should be substitutable for their base types without altering the correctness of the program. This principle ensures that inheritance hierarchies are designed properly.

I've seen many inheritance hierarchies that violate this principle, creating subtle bugs. For instance, a Square class that inherits from Rectangle might seem logical, but could break code that expects to set width and height independently.

Interface Segregation Principle

Clients should not be forced to depend on interfaces they don't use. It's better to have many small, specific interfaces than one large, general-purpose interface.

This principle has helped me create more flexible and decoupled systems. By defining focused interfaces, components only need to implement what they actually use, reducing unnecessary dependencies.

For example, rather than having a single FileHandler interface with methods for reading, writing, compressing, and encrypting, we might have separate Reader, Writer, Compressor, and Encryptor interfaces.

Dependency Inversion Principle

High-level modules should not depend on low-level modules. Both should depend on abstractions. Additionally, abstractions should not depend on details; details should depend on abstractions.

This principle has been transformative for my approach to software design. By depending on abstractions rather than concrete implementations, I can easily swap out components without changing the core business logic.

For instance, a UserService might depend on a DataStore interface rather than directly on MongoDB or PostgreSQL implementations, making it easy to change the underlying storage mechanism.

Practical Design Patterns

Beyond SOLID principles, several design patterns have proven particularly useful in my projects:

Factory Pattern

The Factory pattern provides a way to create objects without specifying the exact class of object that will be created. This pattern helps decouple object creation from the code that uses the objects.

I've found this pattern especially useful when the exact type of object needed isn't known until runtime, or when object creation involves complex logic.

Strategy Pattern

The Strategy pattern defines a family of algorithms, encapsulates each one, and makes them interchangeable. This pattern allows the algorithm to vary independently from clients that use it.

I've used this pattern extensively for implementing different business rules, sorting algorithms, or pricing strategies that can be selected dynamically based on context.

Decorator Pattern

The Decorator pattern allows behavior to be added to individual objects, either statically or dynamically, without affecting the behavior of other objects from the same class.

This pattern has helped me add cross-cutting concerns like logging, caching, or access control to existing functionality without modifying the core components.

Observer Pattern

The Observer pattern defines a one-to-many dependency between objects so that when one object changes state, all its dependents are notified and updated automatically.

This pattern has been invaluable for building event-driven systems and user interfaces, where changes in one component need to be reflected in others.

Design Principles in Practice

While these principles and patterns provide valuable guidelines, applying them effectively requires judgment and context. Here are some practical insights I've gained:

Balance is Key

Overengineering is just as problematic as underengineering. I've learned to strike a balance between applying design principles and keeping solutions simple.

Early in my career, I fell into the trap of applying patterns everywhere, creating unnecessary complexity. Now I recognize that sometimes a straightforward approach is best, especially for simpler problems.

Evolve Your Design

Perfect design rarely happens upfront. Instead, I've found that good design emerges through continuous refactoring and adaptation as requirements become clearer.

I now practice incremental design, starting with simpler solutions and gradually introducing patterns and abstractions as complexity increases.

Consider the Team

Design decisions should account for the team's expertise and familiarity with different patterns. The most elegant design is worthless if the team struggles to understand and maintain it.

I've learned to collaborate with team members when making design decisions, ensuring everyone understands and buys into the approach.

Test-Driven Design

Writing tests first often leads to better design decisions. When I write tests before implementing features, I'm forced to consider how components will be used, leading to more intuitive interfaces.

This approach has helped me create more modular, loosely coupled designs that are easier to test and maintain.

Conclusion

Good software design isn't about following rules rigidly—it's about understanding the principles behind them and applying them judiciously to your specific context. The principles and patterns I've outlined here have served me well in my own projects, helping me create code that's not only functional but also adaptable to change.

As your applications evolve, you'll find that time invested in thoughtful design pays dividends in reduced maintenance costs and increased development velocity.

Remember that the best code is not just correct—it's clear, maintainable, and a joy to work with. Happy coding!

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What design principles have you found most valuable in your projects? I'd love to hear your thoughts in the comments below.

Hello World!

After months of contemplating, planning, and yes—battling procrastination—I'm thrilled to finally launch this blog. Welcome to my little corner of the internet!

"Arise, awake and stop not till your goal is reached." - Swami Vivekananda

That quote has been my North Star throughout this journey. Along with the Tamil proverb "Ellam nanmaike" (All is well), these words of wisdom guide my approach to both life and coding.

And yes, I'm well aware of the irony in the joke: "Procrastinators unite... Tomorrow." Try not to procrastinate as much as you can—a lesson I'm still learning myself!

I've come to realize that passion alone is not sufficient. It should be backed by suitable knowledge. That's partly why I've created this blog: to deepen my understanding through sharing.

What This Blog is About

This space will serve as my digital journal where I'll share:

• Technical insights and challenges from my software engineering projects
• Deep dives into interesting programming concepts and technologies
• Lessons learned throughout my career journey
• Thoughts on software architecture, design patterns, and best practices
• Occasional reflections on the tech industry and developer culture

I hope that by documenting my experiences, I might help fellow developers avoid pitfalls I've encountered or discover solutions I've found useful.

About Me

I'm Ganapathy Subramanian Ramachandran, though most people know me as Ganu. I'm a software engineer passionate about building robust, scalable systems. My journey in tech has taught me that continuous learning and adaptation are essential in our ever-evolving field.

When I'm not coding, you might find me discovering new restaurants around town, driving to scenic places on weekends, or simply spending quality time with my kid. I particularly enjoy exploring the culinary diversity this region offers, finding those quiet, picturesque spots that make for perfect getaways, and watching my child learn and grow through our everyday adventures together.

What's Next

In the coming weeks/months/years, I'll be sharing posts about my thoughts on the technology space . If there's anything specific you'd like me to explore, feel free to reach out!

For more updates and to connect professionally, you can find me on LinkedIn.

Thanks for joining me on this journey. Here's to breaking the procrastination cycle and building something meaningful together!