For any company, from healthcare to e-commerce, rogue web elements can lead to massive fines & reputational damage.

The Danger of Forgotten Pixels on Websites: A New Case Study

Idan conducted cyberattacks to assess corporate security, he started Cynet during his tenure at BugSec, specializing in EDR solutions. Today Idan is the Co-founder & CEO of Reflectiz, an award-winning cybersecurity startup for web threat management.

Idan Cohen

In the dynamic realm of cybersecurity threats, Magecart remains a persistent danger to e-commerce enterprises and their customers. Magecart web-skimming attacks are a popular type of cyberattacks involving injecting malicious code into the checkout pages ...

The Cost of Magecart: More Than Just a Single Fine

Reflectiz, a cybersecurity company specializing in continuweb threat management offers an exclusive, fully remote solution to battle Magecart web-skimming attacks, a popular type of cyberattacks ...

Holiday Season Cyber Alert: Reflectiz Declares War On Magecart

The Hacker News is the most trusted and popular cybersecurity publication for information security professionals seeking breaking news, actionable insights and analysis.

The Hacker News | #1 Trusted Cybersecurity News Site — Index Page

Get the most recent info and news about Reflectiz on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

Reflectiz is a cyber security company that detects website vulnerabilities, threats and privacy issues generated by their third-party applications.

Reflectiz

TEL AVIV, Israel, Sep 05, 2023 — Reflectiz, a cybersecurity company specializing in continuous web threat management, offers an exclusive, fully remote solution to battle Magecart web-skimming attacks, a popular type of cyberattacks involving injecting malicious code into the checkout pages. As the Holiday Season approaches, online retailers face the challenge of protecting their websites against the growing threat of malicious attacks, such as Magecart. However, they struggle to add new security layers due to restrictions on modifying their website code to avoid impacting website performance during the peak shopping season. Reflectiz, a unique web security tool, ensures 100% readiness for Magecart attacks before and during the Holiday Season. This is made possible by Reflectiz's external, non-intrusive solution, requiring no code implementation or IT resources. Your website(s) will be fully protected within days, and there will be no impact on your website performance. Reflectiz automatically detects third-party code changes, keylogging, and communication with malicious domains to prevent Magecart web-skimming attacks. It overcomes the most sophisticated malware obfuscation techniques, lets you track changes, prioritize issues, and implement alerts according to their severity level, empowering you to act before the damage is done. Despite being so powerful, Reflectiz does not affect website performance. It has zero impact on your IT resources and does not require any installation on the client. It begins protecting your web assets within days, ensuring continuous monitoring of all crucial and sensitive web pages, not just checkout pages. “Reflectiz understands online retailers' challenges during this busy time of the year. In 2023, Reflectiz detected Magecart attacks on more than 150 websites, and the count is still rising. Our advanced technology enables the automatic detection of sophisticated threats throughout your entire online environment, all with quick and easy external implementation. You will be up and running within days" - Ysrael Gurt, Co-founder & CTO, Reflectiz Sign up for our exclusive offer today and get the ideal head start in the war on Magecart. Contact Marketing Director Daniel Sharabi Reflectiz daniel.s@reflectiz.com This story was distributed as a release by Cyberwire under . HackerNoon’s Business Blogging Program

Holiday Season Cyber Alert: Reflectiz Declares War on Magecart

In 2021, hosted the first-ever awards!! HackerNoon Startup of the Year The goal of this campaign was to give recognition to the hardworking startups who pulled through the pandemic -- growing and thriving (despite all of the challenges). More than 44,000 startups were nominated all across the globe! They were selected from over 4,553 cities, with a total number of * cough * “4 billion” votes. Insane, right? To see who is a winner in each respective city, visit and pick a city. The name at the top of the list is the winner. (Compromised awards are under review. Cities with tie votes will be updated to have two winners!) startups.hackernoon.com The will announce the winners per region in their respective cities. Startups Winners Announcement series Here are the winners in the : Asia region Top Startup Cities in East Asia Seoul The Startup of the Year in is with 377 votes! Seoul dable Central is the Startup of the Year! It came out ahead with 121 votes. UpNow Central Sheung Wan came out as the Startup of the Year in with 154 votes. Votee Sheung Wan Tokyo The Startup of the Year in is with 41 votes! Tokyo ACES Wan Chai The Startup of the Year in is with 54 votes! Wan Chai Zetl Osaka, Japan In , is the winner! Osaka Nanophoton Taiwan came out as the Startup of the Year in ! Tico Taiwan Dongcheng, China In , is declared the Startup of the Year! Dongcheng Waiju Taipei came out as the Startup of the Year in ! Tico Taipei Akasaka In , is the winner! Akasaka WAKUWAKU Chuo In , is declared the Startup of the Year! Chuo GO-NET Ginza came out as the Startup of the Year in ! Netyear Ginza Kanazawa In , is the winner! Kanazawa Granzella Minami-aoyama In , is declared the Startup of the Year! Minami-aoyama Tokyo6 Entertainment Shibuya came out as the Startup of the Year in ! Hupro Japan Shibuya Toranomon In , is the winner! Toranomon Small Worlds Toshima In , is declared the Startup of the Year! 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It came out ahead with 186 votes. SmartWindows Lahore Bangalore, India When it comes to , is the Startup of the Year with 210 votes! Bangalore vBridge Hub Pune, India couldn’t be beaten for Startup of the Year in , it won with 129 votes! InfraCloud Pune Jaipur, India The Startup of the Year in is with 166 votes Jaipur Emizen Tech Lucknow, India is the Startup of the Year! It came out ahead with 279 votes. Keeros Superfoods Lucknow Noida, India came out as the Startup of the Year in with 156 votes! Bagisto Noida Mumbai, India When it comes to , is the Startup of the Year with 96 votes! Mumbai Sequretek Sylhet couldn’t be beaten for Startup of the Year in , it won with 122 votes! DataXpie Sylhet Mylapore, India In , is the winner! Mylapore Yalimart Goa, India In , the Startup of the Year is Goa Filter Coffee Delhi, India In , is declared the Startup of the Year! Delhi EkAnek Networks Karachi, Pakistan The winner in is Karachi Bykea Ahmedabad, India In , is the winner Ahmedabad MageComp Dhaka, Bangladesh The winner in is Dhaka SOLshare Islamabad, Pakistan In Islamabad, is declared the Startup of the Year! TAG Gurgaon, India In , the Startup of the Year is Gurgaon ixigo Bengaluru, India In , is the winner! Bengaluru Prakshep Private Limited Haryana, India couldn’t be beaten for Startup of the Year in ! Footprints Childcare Haryana Kolkata, India In , is the winner! Kolkata Wow! Momo New Delhi, India In , is declared the Startup of the Year! New Delhi Rusk Media Indore, India The winner in is Indore Chattar Patar Kormangala In , is the winner Kormangala Sanctum Technologies Ghaziabad came out as the Startup of the Year in Craftfurnish.com Ghaziabad! Mohali In , the Startup of the Year is Mohali DataKund Mysore The Startup of the Year in is Mysore Excelsoft Karnal came out as the Startup of the Year in ! Dunar Karnal Kolhapur In , is the winner! Kolhapur Zanvar Group Patiya In , the Startup of the Year is Patiya Kloud Project Kathmandu In , is declared the Startup of the Year! Kathmandu Vairav Technology Bangalore City, India In is the winner! Bangalore City, PagarBook Ernakulam The winner in is Ernakulam Epixel Solutions Colombo, Sri Lanka couldn’t be beaten for Startup in the Year in MAs Foods Colombo Andheri, India When it comes to , is the Startup of the Year! Andheri DoorMint Kanpur, India came out as the Startup of the Year in ! ServiceWalaa Kanpur Faisalabad In , is the winner! Faisalabad DigiKhata Nasik The Startup of the Year in is Nasik Sahyadri Farms Patna came out as the Startup of the Year in ! Asvin Tech Patna Chennai, India In , is the winner! Chennai Agnikul Cosmos Faridabad, India In , is declared the Startup of the Year! Faridabad UClean Panjim, India The winner in is Panjim TempoGO Ranchi, India In , is the winner Ranchi Osam Dairy Surat, India In , is declared the Startup of the Year! Surat Wishbook Thane, India In , is the winner! Thane Delight Foods Trivandrum, India came out as the Startup of the Year in ! GenRobotic Trivandrum Vijayawada, India In , the Startup of the Year is Vijayawada Eruvaka Technologies Visakhapatnam, India In , Ltd is declared the Startup of the Year! Visakhapatnam Greenline Labs Pvt Ahmadabad In , is the winner! Ahmadabad KiwiQA Services Bandra came out as the Startup of the Year in ! Car Club Bandra Bombay In , is the winner! Bombay Locobuddy Mobile Technology (Sportobuddy) Cochin In , the Startup of the Year is Cochin Tuttifrutti Interactive Gandhinagar In , is declared the Startup of the Year! Gandhinagar Kroop AI Guwahati In , the Startup of the Year is Guwahati GNRC Hospitals Jamshedpur In , is declared the Startup of the Year! Jamshedpur Intelliber Kabul The winner in is Kabul Miracle Shop (Vocinno Technology) Karur In , is the winner Karur Karur Vysya Bank Kochi The winner in is Kochi BestDoc Kozhikode In , is declared the Startup of the Year! Kozhikode OfficeKit HR Ludhiana In , the Startup of the Year is Ludhiana Trendy Beat Network Madhapur In , is the winner! Madhapur Head Digital Works Mangalore When it comes to , is the Startup of the Year Mangalore Hangyo Nagpur came out as the Startup of the Year in ! UPrudence Agro Nagpur Rawalpindi The Startup of the Year in is Rawalpindi Pro Options Marketing Rishikesh came out as the Startup of the Year in ! Descatuk Rishikesh Secunderabad couldn’t be beaten for Startup of the Year in Prakriti Biosystems Engineering Secunderabad Tirupur In , is the winner! Tirupur Tubeknit Fashions Udupi The winner in is Udupi Krishitantra Top Startup Cities in Southeast Asia Singapore, Singapore The Startup of the Year in is with 6556 votes! Singapore Cake DeFi Hanoi, Vietnam is the Startup of the Year! It came out ahead with 683 votes. DeFi For You Hanoi Kuala Lumpur, Malaysia came out as the Startup of the Year in with 109 votes! Trambellir Kuala Lumpur Pasig, Philippines When it comes to , . is the Startup of the Year with 110 votes! Pasig Quickreach Inc Bangkok, Thailand couldn’t be beaten for Startup in the Year in , it won with 60 votes! Perception Codes Bangkok Johor Bahru In , the Startup of the Year is . Johor Bahru AGR1 Bandung, Indonesia In , is declared the Startup of the Year! Bandung Prosa Portugal The winner in is . Portugal SCEMAI Tangerang, Indonesia In , is the winner Tangerang Yummy Corp Jakarta, Indonesia In , is the winner! Jakarta Tokocrypto Dki Jakarta, Indonesia In , is declared the Startup of the Year! Dki Jakarta Limakilo Bangkok Metropolis In , is the winner! Bangkok Meticuly Medan The winner in is ! Medan DIKA Manila, Philippines In , is declared the Startup of the Year! Manila PawnHero Phnom Penh, Cambodia In , the Startup of the Year is Phnom Penh vKirirom Bali In , is the winner! Bali Radius App Penang When it comes to , is the Startup of the Year Penang EasyParcel Surabaya came out as the Startup of the Year in ! Super Surabaya Setiabudi, Indonesia The Startup of the Year in is Setiabudi Chilibeli Cebu City came out as the Startup of the Year in MiCab Cebu City! Jawa couldn’t be beaten for Startup in the Year in DAUR Jawa Ho Chi Minh City, Vietnam In , is the winner! Ho Chi Minh City Pharmacity Selangor, Malaysia is the Startup of the Year! BabyDash Selangor Jakarta Pusat, Indonesia In , is the winner! Jakarta Pusat StickEarn Semarang When it comes to , is the Startup of the Year! Semarang Food Bear Petaling Jaya, Malaysia The winner in is . Petaling Jaya Deemples Kebayoran Baru, Indonesia couldn’t be beaten for Startup in the Year in ! Yogrt Kebayoran Baru Kuningan The winner in is . Kuningan Prinzio Bukit Merah came out as the Startup of the Year in ! DC Alliance Bukit Merah Huai Khwang In , the Startup of the Year is . Huai Khwang AppMan Co.,Ltd Kuta In , is declared the Startup of the Year! Kuta Gringgo Mandaluyong came out ahead as the Startup of the Year! Work Inspire Mandaluyong Midview City In , is the winner! Midview City BioMers Phuket The Startup of the Year in is ! Phuket Sapahn Yangon, Myanmar The winner in is . Yangon Wave Money Denpasar When it comes to , is the Startup of the Year! Denpasar Revasi Nakhon Ratchasima, Thailand The winner in is . Nakhon Ratchasima Siam Lottery co., Ltd Taguig, Philippines In , is the winner! Taguig PayMongo Bogor came out as the Startup of the Year in ! TIRANYX Bogor Senai, Malaysia won as the Startup of the Year. Nutrition Technologies Senai Bekasi Kota couldn’t be beaten for Startup in the Year in ! 8villages Bekasi Kota Top Startup Cities in Middle East Tel Aviv, Israel The Startup of the Year in is with 1,065 votes! Tel Aviv hyro Beirut, Lebanon is the Startup of the Year! It came out ahead with 1,276 votes. Hovi Digital Lab Beirut Riyadh, Saudi Arabia With 350 votes, came out as the Startup of the Year in ! Flicron Riyadh Tel Aviv-yafo, Israel When it comes to , is the Startup of the Year with 167 votes! Tel Aviv-yafo Cymbio Haifa, Israel couldn’t be beaten for Startup in the Year in , it won with 183 votes! Pico Haifa Amman, Jordan In , with 141 votes, is the winner! Amman Edexy Dubai, United Arab Emirates In , the Startup of the Year is with 74 votes. Dubai Ziina Doha, Qatar In , is declared the Startup of the Year! Doha SkipCash Tehran, Iran The winner in is . BeyondBoard AR Tehran Jerusalem, Israel In , is the winner! Jerusalem SolidBlock Rishon Le Zion The Startup of the Year in is ! Rishon Le Zion Passparto Ness Ziona, Israel is the Startup of the Year! Soapy Ness Ziona Kuwait, Kuwait came out as the Startup of the Year in ! Brapper Shop Kuwait Manama, Bahrain couldn’t be beaten for Startup in the Year in ! Doctori Manama Lod, Israel is the winner in ! Phinergy Lod Agudat Israel, Israel When it comes to is the Startup of the Year with [vote ] votes! Agudat Israel, Aqaurius Engines Beersheba, Israel In , the Startup of the Year is . Beersheba Visual Estate Ltd Giv'atayim, Israel In , is declared the Startup of the Year! Giv'atayim WSC Sports Modi'in, Israel The winner in is . Modi'in Loginno Nazareth, Israel In , is the winner! Nazareth AR Guide In Medical Ramat Gan, Israel The Startup of the Year in is . Ramat Gan Datos Health Baghdad When it comes to , is the Startup of the Year! Baghdad Mishwar Khobar In , the Startup of the Year is . Khobar Garage Misgav couldn’t be beaten for Startup in the Year in ! Eden Shield Misgav Sharjah came out as the Startup of the Year in ! Bookends Sharjah Affula In , the Startup of the Year is . Affula eMotion Technologies Bene Beraq, Israel In , is the winner Bene Beraq Reflectiz Caesarea, Israel In , the Startup of the Year is . Caesarea CardiacSense Dubayy In , is declared the Startup of the Year! Dubayy North Ladder Muscat couldn’t be beaten for Startup in the Year in ! iLab Marine Muscat Tirat Carmel In , the Startup of the Year is . Tirat Carmel PassCall Advanced Technologies Hod Hasharon, Israel The winner in is . Hod Hasharon Idomoo Holon, Israel came out ahead as the Startup of the Year! OptimalPlus Holon Jeddah, Saudi Arabia When it comes to , is the Startup of the Year! Jeddah Arabian Combustion Technologies Ramat Hasharon, Israel is the Startup of the Year! Lumen Ramat Hasharon Al Khobar came out as the Startup of the Year in ! Swyft Al Khobar Bet Shemesh In , is the winner! Bet Shemesh Degania Medical Binyamina When it comes to , is the Startup of the Year! Binyamina OncoHost Makkah In , the Startup of the Year is Makkah Scimagine Or Akiva Last but not least, couldn’t be beaten for Startup in the Year in the city of ! WMT Or Akiva More Information: If you’re a winner, please answer ! If you’re a reader, participant, just a curious individual, consider answering one of our interviews . this interview here Read the FAQs about or . Startups here here To see all of the winners you may visit , pick any city and view the name that appears at the top. this site If you’re interested in partnering with us, we invite you to look through some of these or reach out to our business department. unique sponsorship options Perhaps creating your very own tickles your fancy or maybe you have a whole new idea for how we can partner! writing contest Thank you to all of our sponsors! We truly appreciate your contribution to the tech world and thus the future! The Startups Awards are sponsored by: , , , , , , , , , , Blockster Brex FreeCodeCamp LaunchDarkly Coil Udacity Udemy Vercel Asia Pacific Transgender Network Bybit Everscale Network The post was written by Kushal Tamrakar and Valerie Ejegi, edited by Hang Ngo. If you have any questions or concerns or would like to report a discrepancy please email ellen@hackernoon.com.

Meet the Winners of Startups in Asia

Recently I wrote an article where I wanted to compare a popular way of creating object instances with DotNet reflection to another. In that article, I put to see which had better performance. The result saw Activator.CreateInstance emerge as winner in one specific case — but another champion emerges: ConstructorInfo. Activator.CreateInstance head-to-head with Type.InvokeMember In this article, I’ll explain how you can get a ConstructorInfo reference using reflection in DotNet. I’ll also expand upon the benchmarks from the previous article, showing you the code and how the results turned out. Understanding ConstructorInfo From DotNet Reflection In DotNet reflection, we get a powerful set of tools for inspecting assemblies, types, and members at runtime. One of the key components of this reflective capability is the class, which belongs to the namespace. This is where all of the goodies are — ConstructorInfo System.Reflection Even the ones shown in this video that can be misused in the wrong hands: https://youtu.be/3Qstc-ND8Oo?embedable=true allows developers to obtain information about the constructors of a class, including their accessibility (public, private, etc.), parameters, and metadata. But one of the best parts, which we’ll be looking at in more detail, is that it enables the instantiation of objects dynamically at runtime without knowing their types at compile time. ConstructorInfo And the best part? We’re going to see that when we compare it to , it’s way faster. these other DotNet reflection mechanisms for making new instances Finding Constructors with Reflection in DotNet – Getting ConstructorInfo In this section, we’ll look at how we can first get instances so that we can leverage them later for object instantiation: ConstructorInfo Get the instances from types ConstructorInfo Find the right constructor … Profit! Something like that, right? Let’s check these code examples out! Get ConstructorInfo for All Public Constructors To retrieve all public constructors of a class, you can use the method without any parameters by using a instance of a particular type. This method returns an array of objects representing each public constructor defined for the class. GetConstructors Type ConstructorInfo Let’s see it in action in this code example: using System;
using System.Reflection;

public class SampleClass
{
    public SampleClass() { }
    public SampleClass(int i) { }
    protected SampleClass(string s) { }
    private SampleClass(int i, string s) { }
}

Type typeInfo = typeof(SampleClass);
ConstructorInfo[] publicConstructors = typeInfo.GetConstructors();

foreach (var constructor in publicConstructors)
{
    Console.WriteLine(constructor.ToString());
} When we’re thinking about dynamically invoking these things, it’s likely going to be the case that we don’t have the reference to the type though. But if we have the name of the type we’re interested in, we can use the following: Type typeOfInterest = Type.GetType("The.Namespace.Of.Your.Type.TheTypeName"); Get ConstructorInfo Including Private and Protected Constructors To get information about all constructors, regardless of their accessibility level, you can use the method with the parameter. This approach allows you to include non-public constructors in the results: GetConstructors BindingFlags ConstructorInfo[] allConstructors = typeInfo.GetConstructors(BindingFlags.Public | BindingFlags.NonPublic | BindingFlags.Instance);

foreach (var constructor in allConstructors)
{
    Console.WriteLine(constructor.ToString());
} Keep in mind that if you watched the video I linked above, this starts to get into the territory of “Should I be doing this?”. Please strongly consider if you need to be accessing non-public things — Someone likely chose that access modifier for a reason. Get ConstructorInfo Matching a Specific Signature If you’re looking for constructors that match a specific parameter signature, you can use (notice that it’s singular). This takes in binding flags like we saw before as well as an array of types that you want to match. GetConstructorInfo Here’s how you could find constructors that take a single parameter: int // Specify the parameter types of the 
// constructor you are looking for
Type[] paramTypes = new Type[] { typeof(int) };

// Use GetConstructor with the appropriate
// BindingFlags and parameter types
var constructor = typeInfo.GetConstructor(
    BindingFlags.Public | BindingFlags.Instance,
    paramTypes);

if (constructor != null)
{
    Console.WriteLine(constructor);
}
else
{
    Console.WriteLine("No matching constructor found!");
} Note that this method will return null when there’s no match, so ensure you got what you were looking for! Creating Object Instances Using ConstructorInfo Once we have a instance, we can start making object instances. This is what we’ll be benchmarking in the upcoming sections! ConstructorInfo In these examples, assume that we already have a instance called constructorInfo. We’d be getting this instance in any of the ways documented earlier in the article: ConstructorInfo object instance = constructorInfo.Invoke(null); The code above shows instantiating an object with a parameterless constructor. We pass in null for the list of arguments that would need to be provided — because there are none. Take note that the type we get back is an . If we have access to the type at compile, we could cast this instance to that type… But if we have access to the instance at compile time there are probably very few good reasons why you would be doing this in the first place. If you don’t believe me, wait until you see the benchmark results. object If we want to instantiate using a constructor that takes parameters it would look like the following: object instance = constructorInfo.Invoke(new object[] { 42 }); This code example shows a constructor with a single integer parameter defined being invoked with 42 as the single integer argument. ConstructorInfo Performance Benchmarks The moment you’ve all been waiting for! You might enjoy watching the video demonstrating these DotNet reflection benchmarks here: https://youtu.be/Djq7eMI_L-4?embedable=true BenchmarkDotNet Setup for Reflection Performance Much like the previous article, I’ve just added a couple of additional scenarios for the scenarios. I wanted to mention that I added TWO scenarios for each class, and that’s because I wanted to demonstrate the performance if you had to go instantiate AND find the back-to-back. I felt like this variation compared to already having the would be interesting to take note of. ConstructorInfo ConstructorInfo ConstructorInfo Here is the full code: //
// This code was written for the following Dev Leader content:
// https://www.devleader.ca/2024/03/14/activator-createinstance-vs-type-invokemember-a-clear-winner/
// https://www.devleader.ca/2024/03/17/constructorinfo-how-to-make-reflection-in-dotnet-faster-for-instantiation/
// https://youtu.be/Djq7eMI_L-4 
//
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Running;

using System.Reflection;

BenchmarkRunner.Run(Assembly.GetExecutingAssembly());
//BenchmarkSwitcher.FromAssembly(Assembly.GetExecutingAssembly()).RunAllJoined();

public class ParameterlessClass
{
}

public class ClassicStringParameterClass
{
    private readonly string _value;

    public ClassicStringParameterClass(string value)
    {
        _value = value;
    }
}

public class PrimaryConstructorStringParameterClass(
    string _value)
{
}

[ShortRunJob]
public class ParameterlessClassBenchmarks
{
    private Type? _type;
    private ConstructorInfo? _constructorInfo;

    [GlobalSetup]
    public void GlobalSetup()
    {
        _type = typeof(ParameterlessClass);
        _constructorInfo = _type.GetConstructor(Type.EmptyTypes);
    }

    [Benchmark]
    public void Constructor()
    {
        var instance = new ParameterlessClass();
    }

    [Benchmark(Baseline = true)]
    public void Activator_Create_Instance()
    {
        var instance = Activator.CreateInstance(_type!);
    }

    [Benchmark]
    public void Type_Invoke_Member()
    {
        var instance = _type!.InvokeMember(
            null,
            BindingFlags.CreateInstance,
            null,
            null,
            null);
    }

    [Benchmark]
    public void Constructor_Info_Invoke()
    {
        var instance = _constructorInfo!.Invoke(null);
    }

    [Benchmark]
    public void Find_Constructor_Info_Then_Invoke()
    {
        var constructorInfo = _type.GetConstructor(Type.EmptyTypes);
        var instance = constructorInfo!.Invoke(null);
    }
}

[ShortRunJob]
public class ClassicStringParameterClassBenchmarks
{
    private Type? _type;
    private ConstructorInfo? _constructorInfo;

    [GlobalSetup]
    public void GlobalSetup()
    {
        _type = typeof(ClassicStringParameterClass);
        _constructorInfo = _type.GetConstructor([typeof(string)]);
    }

    [Benchmark]
    public void Constructor()
    {
        var instance = new ClassicStringParameterClass("Hello World!");
    }

    [Benchmark(Baseline = true)]
    public void Activator_Create_Instance()
    {
        var instance = Activator.CreateInstance(
            _type!,
            new[]
            {
                "Hello World!",
            });
    }

    [Benchmark]
    public void Type_Invoke_Member()
    {
        var instance = _type!
            .InvokeMember(
                null,
                BindingFlags.CreateInstance,
                null,
                null,
                new[]
                {
                    "Hello World!",
                });
    }

    [Benchmark]
    public void Constructor_Info_Invoke()
    {
        var instance = _constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }

    [Benchmark]
    public void Find_Constructor_Info_Then_Invoke()
    {
        var constructorInfo = _type.GetConstructor([typeof(string)]);
        var instance = constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }
}

[ShortRunJob]
public class PrimaryConstructorStringParameterClassBenchmarks
{
    private Type? _type;
    private ConstructorInfo? _constructorInfo;

    [GlobalSetup]
    public void GlobalSetup()
    {
        _type = typeof(PrimaryConstructorStringParameterClass);
        _constructorInfo = _type.GetConstructor([typeof(string)]);
    }

    [Benchmark]
    public void Constructor()
    {
        var instance = new PrimaryConstructorStringParameterClass("Hello World!");
    }

    [Benchmark(Baseline = true)]
    public void Activator_Create_Instance()
    {
        var instance = Activator.CreateInstance(
            _type!,
            new[]
            {
                "Hello World!",
            });
    }

    [Benchmark]
    public void Type_Invoke_Member()
    {
        var instance = _type!
            .InvokeMember(
                null,
                BindingFlags.CreateInstance,
                null,
                null,
                new[]
                {
                    "Hello World!",
                });
    }

    [Benchmark]
    public void Constructor_Info_Invoke()
    {
        var instance = _constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }

    [Benchmark]
    public void Find_Constructor_Info_Then_Invoke()
    {
        var constructorInfo = _type.GetConstructor([typeof(string)]);
        var instance = constructorInfo!.Invoke(new[]
        {
            "Hello World!",
        });
    }
} ConstructorInfo Benchmark Results from BenchmarkDotNet The first set of results will be for the parameterless constructor: In the results above, we already knew that without using reflection, we get the best speed. No brainer here. BenchmarkDotNet says it’s so fast it can’t even measure it properly. But we’ll notice that is technically a smidge faster here than using , even if we already had the instance ahead of time. The results are very close, and I have seen this swing the other way. So overall, these two are very comparable in this situation. Activator.CreateInstance ConstructorInfo What happens if we need to use parameters though? The BenchmarkDotNet results above show that a classic style constructor taking in a single string parameter, is an order of magnitude faster than the other DotNet reflection options. Even if we need to look up the instance first, it’s still almost twice as fast as the other options! ConstructorInfo And of course, I wanted to see if primary constructors were any different in behavior: Based on the results above though, they’re right on par! Wrapping Up ConstructorInfo and Reflection in DotNet As we can see from the BenchmarkDotNet results, leveraging can be very performant! Only in the case where we’re dealing with a public parameterless constructor did it seem to be right on par with . Technically in this run it showed that it was a touch slower, but I’ve run these before and seen the opposite case too. Overall, you’ll want to consider if it makes sense for you to leverage this approach for creating object instances — but certainly don’t opt for reflection if you can easily just call ! ConstructorInfo Activator.CreateInstance new() If you found this useful and you’re looking for more learning opportunities, consider and check out my ! subscribing to my free weekly software engineering newsletter free videos on YouTube

Faster Instantiation With DotNet Reflection Using ConstructorInfo

Reflection in is a powerful feature that allows you to inspect and manipulate code at runtime. If that sounds like some fancy programming magic, it’s because it basically is. And you know what they say — with great power, comes great responsibility. C# Reflection in C# provides us with the ability to examine types, and their members, and invoke methods dynamically, opening up a world of possibilities for creative programs. In this article, I’ll provide you with 4 simple code examples illustrating how reflection works in C#. Example 1: Retrieving Type Information Using Reflection in C# Reflection in C# allows us to examine and manipulate types at runtime. It gives us the ability to retrieve information about classes, interfaces, methods, properties, and more. Understanding how to retrieve types using reflection is important for more complex and creative applications in C#. To retrieve types using reflection, we can use the class from the namespace. The class provides various methods and properties to work with types dynamically. Here’s an example code snippet that demonstrates how to retrieve types using reflection: Type System Type using System;

public class Program
{
    public static void Main()
    {
        // Get the type of a class
        Type carType = typeof(Car);
        Console.WriteLine($"Type Name: {carType.Name}");

        // Get all public methods of a class
        MethodInfo[] methods = carType.GetMethods();
        Console.WriteLine("Methods:");
        foreach (MethodInfo method in methods)
        {
            Console.WriteLine($"- {method.Name}");
        }

        // Get all properties of a class
        PropertyInfo[] properties = carType.GetProperties();
        Console.WriteLine("Properties:");
        foreach (PropertyInfo property in properties)
        {
            Console.WriteLine($"- {property.Name}");
        }
    }
}

public class Car
{
    public string Make { get; set; }
    public string Model { get; set; }

    public void StartEngine()
    {
        Console.WriteLine("Engine started");
    }

    public void StopEngine()
    {
        Console.WriteLine("Engine stopped");
    }
} In the above code, we first use the of the class. Then, we can . In this example, we retrieve the type’s name, all public methods, and all properties. Running this code will output the following: typeof operator to get the type Car access various information about the type Type Name: Car
Methods:
- StartEngine
- StopEngine
Properties:
- Make
- Model Retrieving types using reflection can be useful in a variety of scenarios. For example, you might want to dynamically load and instantiate classes based on user input or configuration data. Reflection also enables you to inspect the structure and behavior of code at runtime, and this opens up some doors when you need to make decisions based on information that you don’t have at compile time. See how this works in this video tutorial: https://youtu.be/7xWaSuPn2I8?embedable=true Example 2: Accessing Non-Public Members Using Reflection in C# We previously saw how we could access things like public methods and properties that are available on types. As mentioned, this can have many helpful use cases but it doesn’t *quite* feel like the scary stories we might have heard about reflection. Let’s change that up a bit. While reflection in C# allows us to look up this information, we can also look up non-public information about types. That’s right. All of that effort that someone put in place to use private/protected and hide details from us on the outside? Gone. We can see everything we want! Muahaha! Oh, right — with great power comes great responsibility. No more evil laughter. Here’s an example code snippet that demonstrates how to access non-public members using reflection: using System;
using System.Reflection;

public class Person
{
    private string _name;

    privateint Age { get; set; }

    private void SayHello()
    {
        Console.WriteLine("Hello!");
    }
}

public class Program
{
    public static void Main()
    {
        Type personType = typeof(Person);

        // Accessing a field using reflection
        FieldInfo nameField = personType.GetField(
            "_name",
            BindingFlags.NonPublic | BindingFlags.Instance);
        Console.WriteLine($"Field Name: {nameField.Name}");

        // Accessing a private property using reflection
        PropertyInfo ageProperty = personType.GetProperty(
            "Age"
            BindingFlags.NonPublic | BindingFlags.Instance);
        Console.WriteLine($"Property Name: {ageProperty.Name}");

        // Accessing a private method using reflection
        MethodInfo sayHelloMethod = personType.GetMethod(
            "SayHello",
            BindingFlags.NonPublic | BindingFlags.Instance);
        Console.WriteLine($"Method Name: {sayHelloMethod.Name}");
    }
} In the above code, we define a class with a , a private property , and a private method . In the method, we obtain the object for the class using . Using reflection, we can access the field, property, and method by specifying their names and using the , , and methods of the type, respectively, to retrieve the corresponding members. Person private field name Age SayHello Main Type Person typeof(Person) GetField GetProperty GetMethod Type But the super important part here? The enum. We can ask, for instance, non-public members. We combine these two categories of members together , which you can : BindingFlags using flag enums learn more about here in this video https://www.youtube.com/watch?v=_yUOrzTCpGU&embedable=true Example 3: Modifying Objects Using Reflection Reflection in C# not only allows us to inspect and retrieve information about objects, but it also gives us the power to modify their data and behavior dynamically at runtime. This means that we can, at runtime, get a member by name (and other conditions) and then make modifications — effectively bypassing a lot of the compile-time checks we normally get. And… we can combine that with the non-public access we just saw! Keep that maniacal evil laughter under control… To illustrate how modifying objects using reflection works, let’s consider a scenario where we have a simple class with properties representing their name and age: Person public class Person
{
    public string Name { get; set; }
    
    // NOTE: this probably makes no sense to ever
    // just have a private property like this here
    // but it's just for demonstration
    private int Age { get; set; }

    public void PrintInfo()
    {
        Console.WriteLine($"{Name} - {Age} years old");
    }
} Now, let’s say we want to change the age of a object dynamically based on some condition. With reflection, we can achieve this by accessing and modifying the property at runtime. Person Age // Create a new instance of the Person class
Person person = new Person()
{
    Name = "Dev Leader",
};

// Get the Type object for the Person class
Type personType = typeof(Person);

// Get the PropertyInfo object for the Age property
PropertyInfo ageProperty = personType.GetProperty(
    "Age",
    BindingFlags.NonPublic | BindingFlags.Instance);

// Set the value of the Age property to 35
ageProperty.SetValue(person, 35);

// Prints "Dev Leader - 35 years old")
person.PrintInfo(); In this code example, we first create an instance of the class. Then, using reflection, we obtain the object for the class. From the object, we retrieve the object for the property, which is private and not accessible to us traditionally from the outside. Finally, we use the method of the object to modify the property of the object to 35. When we ask the instance to print its info, we see the updated value! Person Type Person Type PropertyInfo Age SetValue PropertyInfo Age person While being able to modify objects dynamically can be incredibly powerful, it also comes with some risks and considerations. Modifying objects using reflection can introduce complexity and potential pitfalls (read that as: “will likely break things”), such as breaking encapsulation and violating the intended behavior of the object. It’s important to exercise caution and ensure that the modifications made using reflection align with the design and requirements of the system — this *probably* shouldn’t be your first course of action for many things. Learn more about private access and modification in this video tutorial: https://youtu.be/3Qstc-ND8Oo?embedable=true Example 4: Creating Objects Using Reflection Reflection in C# allows us to dynamically. This means that we can create objects of a certain class without knowing the class name at compile-time. This flexibility can be particularly useful in scenarios where we need to dynamically instantiate objects based on runtime data or configuration. create instances of types To create an object dynamically using reflection, we need to follow a few steps: We need to obtain a Type object that represents the class we want to create an instance of. We can do this by using the method and passing the fully qualified name of the class as a string. Type.GetType() We can use the method to create an instance of the class. This method takes the Type object as a parameter and returns a new instance of the class. We can then cast this instance to the desired type and use it as needed. Activator.CreateInstance() Let’s take a look at an example: string className = "MyNamespace.MyClass";
Type classType = Type.GetType(className);
object instance = Activator.CreateInstance(classType);
MyClass myObject = (MyClass)instance; In the code above, we start by defining the fully qualified name of the class we want to create an instance of ( ). We then obtain the Type object by calling and passing the class name as a string. Next, we use to create a new instance of the class and cast it to the desired type ( in this case). MyNamespace.MyClass Type.GetType() Activator.CreateInstance() MyClass Creating objects dynamically using reflection can be useful in various scenarios, including: . By using reflection, we can dynamically create instances of the plugin classes based on configuration or user input. A plugin system where we want to load different plugins at runtime Dynamic object creation when working with deserialization. For example, if we receive JSON or XML data and need to map it to different classes based on the data content, reflection in C# can help us create the appropriate objects dynamically. Remember to handle exceptions and ensure proper error-checking when working with reflection and dynamically creating objects! It’s easy to forget that reflection opens some funky doors that we really need to be careful with. Showcase of Reflection in C# Reflection in C# is a powerful tool that every C# developer should get familiar with because even if you don’t need to use it regularly, it’s helpful to understand. Reflection allows us to examine and manipulate objects at runtime, providing us with great flexibility and control over code in some creative situations — like plugin loading! By leveraging reflection, we can dynamically load types, query and invoke methods, access properties, and even create new objects. Throughout this article, we explored four code examples that showcased how you can leverage reflection in C#. We discussed how to iterate through members, inspect things that aren’t publicly available, retrieve and set property values dynamically, and dynamically create instances of objects. If you found this useful and you’re looking for more learning opportunities, consider and check out my ! subscribing to my free weekly software engineering newsletter free videos on YouTube Also published . here

4 Simple But Powerful Code Examples of Reflection in C#

Context This article is meant to be a sober reflection on the data lakehouse table format conversation I have had as a participant over the last two years. I've written the following articles over the years on the subject: Table Format Comparison Table Format Comparison: Partitioning Table Format Comparison: Governance Architecture of the Lakehouse Table Formats Apache Iceberg 101 I am writing this article in response to these two pieces: Jacques Nadeau: Overview of state of table formats Kyle Weller: Don’t Worry About Data Lakehouse Features, Trust in Google Search… I work for , who is a contributor to Apache Iceberg and has robust support for Apache Iceberg Data Lakehouses (DDL, DML, Cataloging, Table Optimization) and also can read Delta Lake tables. DISCLOSURE: Dremio, the Data Lakehouse Platform Introduction Choosing the right open-source table format for your data lakehouse is more top of mind than ever as people explore implementing data lakehouses and data lakehouse platforms. With three prominent options in Apache Iceberg, Apache Hudi, and Delta Lake, all vying to be the heart of your lakehouse, it's easy to get lost in the noise of feature sets and performance benchmarks. This blog aims to cut through the fear, uncertainty, and doubt (FUD) surrounding table formats, providing a clear path to understanding what really matters in your selection process. Short Version for Quick Readers All major table formats are mature projects that are constantly improving performance and feature sets. The existence of multiple formats is a boon to the industry, as it fosters a competitive environment that drives improvements across the board. However, when it comes down to choosing a format, it's not just about features and performance. The critical decision should be based on the ecosystem of tools you plan to use and how well they integrate with the format. By focusing on your use cases and testing with your actual workloads, you'll find the table format that best meets your needs. My Journey with Table Formats and Lakehouses Over the last two years, I've immersed myself in the world of table formats and lakehouses, a journey that I plan to continue for the foreseeable future. My entry into this conversation began with an article comparing different table formats. That piece, which became one of my most-viewed writings, initially focused on the various features of these formats. However, as I've updated the article over time, I've noticed the narrowing differences between them, leading to a significant realization. Ecosystem Over Features What truly matters is not the array of features a format possesses but the ecosystem that supports these features and their usability. After all, what's the point of advanced functionality if it's not utilized effectively or is too complex to integrate? The real value lies in how these features are implemented within the ecosystem and how seamlessly they can be adopted into your workflows. Key Takeaways The first major takeaway from my experience is the paramount importance of the ecosystem and usability over the raw feature set. A table format might boast an impressive list of capabilities, but if those features are not accessible or practical for your team's use, their value diminishes. Thus, when evaluating table formats, consider the supporting tools, documentation, community, and ease of integration into your existing systems. Ecosystem and Usability Over Features Performance Considerations: Beyond Benchmarks When delving into the world of table formats, it's easy to get caught up in the numbers game of performance benchmarks. While these metrics offer a snapshot of efficiency under ideal conditions, they seldom provide the full picture needed for informed decision-making. The Limitations of Benchmarks Benchmarks, particularly those in Apache Spark environments, have their place in performance evaluation. However, they often reflect a momentary advantage, influenced by specific configurations and data sets that may not align with everyday usage. The reality is that the performance of a table format is not static; it evolves with each update to its libraries, the processing too, and as users configure the table and tools to suit their unique workloads. True performance evaluation requires a broader lens, one that considers how a table format behaves with the suite of tools you rely on and the nature of your data. Making Informed Choices Choosing a table format based on performance means looking beyond Spark-centric benchmarks. It involves testing how each format manages your specific data types and use cases across the tools and technologies that form the backbone of your data infrastructure. Only by assessing performance in this holistic manner can you ensure that your chosen table format aligns with your operational realities and performance expectations. Understanding the Metric of Open Source Contributors A critical aspect I'd like to clarify from my original blog post is the rationale behind using the number of open-source contributors as a key metric. This choice might have raised some eyebrows, especially considering the complex structure of repository management across many table formats. These projects often distribute their development efforts across multiple repositories, separating the core project—typically written in Java—from implementations in other programming languages like Python, Go, and Rust. Why Focus on Core Contributors? The decision to concentrate on contributors to the core format was deliberate. The core repository is where the most significant decisions regarding the format's evolution are made. It's the heart of the project, determining not just current functionalities but also setting the direction for future developments. The distribution of influence over these decisions is crucial. It reveals whether the evolution of the format is being guided by a diverse group of stakeholders or if it's under the control of a few, potentially leading to a bias in development priorities. The Impact on the Ecosystem While there are undoubtedly many talented contributors working across the various language-specific repositories, their work often focuses on mirroring the functionality established in the core. Although valuable, this does not typically drive the project's overall direction. The core repository's contributor diversity is, therefore, a more accurate indicator of the project's health and its alignment with the broader community's needs. The Importance of Competitive Diversity From a consumer's perspective, the diversity of contributors to the core repository is more than a technicality; it's a safeguard against vendor lock-in, budget inflation, and the potential stagnation of innovation in a controlled market. A table format steered by a community with varied interests ensures that no single entity can dominate the project's direction to the detriment of the community. This competitive diversity fosters an environment where vendors can innovate on equal footing, driving technological advancements and more favorable pricing for end-users. The Value of Contributor Diversity In aiming for a competitive market, the significance of an open format governed by a broad coalition cannot be overstated. The diversity of core repo contributors matters because it ensures that the format remains open, adaptable, and free from monopolistic control. By prioritizing formats with a wide array of contributors, we champion the principles of open innovation and collective progress that are foundational to the open source ethos. Conclusion It's clear that the table format conversation transcends mere technical specifications and performance metrics. The past two years have illuminated the paramount importance of ecosystem compatibility, the tangible benefits of a broad, diverse community of open-source contributors, and the nuanced understanding required to evaluate performance in real-world scenarios. As we navigate the choices between Apache Iceberg, Apache Hudi, and Delta Lake, it becomes evident that the true value lies in fostering an open, competitive market that drives innovation, ensures flexibility, and avoids vendor lock-in. By prioritizing formats that align with our technological ecosystems, supported by a vibrant community, and delivering performance on our workloads with our desired tooling, we can build data infrastructures that are not only robust and efficient but also adaptable and forward-looking. Try the Dremio Lakehouse Platform Today Build a Prototype Data Lakehouse on Your Laptop with This Tutoria Also published . here

Data Lakehouse Table Formats: Considerations, Reflection, and Perspective

This year has been important in so many ways. I’ve been publishing more content than ever. I had a part-time personal assistant. Got access to many wonderful opportunities. I raised my net worth by 60%. I’ve built a great team and moved the product forward at the cybersec SaaS I work at. I almost finished my master’s in management (thesis postponed to the next year). I designed and furnished my first (and hopefully last) apartment. Hell, I even started using separate products for hair and body. And there was a lot of personal change as well. Join me in this short recap if you want to learn where a path like mine can lead you. I’ll share mostly blog and online presence-related details with some professional (engineering), financial, and private information sprinkled on top. Happy to tell more to those interested. Why am I here? I like sharing knowledge, writing, and helping people. I believe that publishing is a vital part of being a professional. Being here, rushing some content out even though it’s not perfect, being vulnerable - that’s a great way to get to know more people and open one’s mind to new points of view. I think one person - Austin Kleon - put this in words much better than me. Check out his short book, and you’ll know everything. is about why generosity trumps genius. It's about getting , about using the network instead of wasting time "networking." It's not self-promotion, it's self-discovery--let others into your process, then let them steal from you. Show Your Work! findable I had a blast putting effort into this blog and other projects this year. Some people enjoyed it as well, as seen in stats from various platforms. Stats Here’s the most interesting numbers i dug out! My blog was visited a total of 43 thousand times: I also got an additional 23k visits to my articles republished on Hackernoon. My LinkedIn content generated 65k impressions, similar to views on the blog. I’ve been posting quite irregularly, as seen in the graph below. Near the end of the year, I started listening to the numbers, resulting in more engagement than ever. Posts mentioning others and with my photos are noticeably more popular. Other numbers: My newsletter got 50 subscribers (up from 24 in July). On Twitter, my posts generated ~300k impressions. I spoke at eight conferences. I was a guest in 5 podcast episodes. I have published 12 blog articles. Best content If you missed some of my articles, here’s a chance to catch up. It’s clear that my most popular content was not opinions, summaries, or anything related to my publishing online. Most viewed articles were software engineering tutorials. A lot of traffic came from Google search, where I ranked quite high for some keywords. I also think I figured out a good way to create thumbnails. 11k views: Extracting and Generating JSON Data with GPTs, LangChain, and Node.js 9K views: How I Effortlessly Create PowerPoint Presentations with ChatGPT and MARP (as a Software Engineer) 2K views: Fine-tuning OpenAI GPT 3.5: Practical example with Python Tip for me for the next year: write more engineering tutorials. Other projects simple message from me here: don’t build a house or buy a new unfinished apartment if you’re not into it. I had to learn interior design from the ground up. Get to know materials, design solutions, too many new technical terms. It interesting, it can be fun, but it is a lot of work. Even though I’m very happy with the outcome, I think I could have spent my time better. Real estate investing / buying a new apartment: really is kicked off 2, shipped none. Excuses? Master thesis and moving apartments. Picking them up again in 2024. One was MeetingFusion: , the other is still unpublished. MF got several sign-ups on the waiting list. Side projects/startups: https://meetingfusion.com : Struggling, will post an update soon. My old AI Startup, Sentimatic : I’ve been able to provide some small-scale but well-paid software engineering services on the side. Consulting : applied for government funding and spent a lot of time. My assistant spent 175 hours on it! The application was of a master’s thesis size. Funding for new AI project Opportunities Writing here gave me more opportunities than ever before. Apart from everything mentioned above, here are some highlights. I’ve been invited a few times to run a workshop about topics I write about by several engineering companies. All my offers were rejected due to the price. I am okay with this, as I only considered it if I was able to provide the absolute best quality of the workshop. I’ve got more interesting job offers than ever. I did not proceed with any, as I’m committed to my current work at Netacea. I’ve been asked to develop a Vue.JS course for a popular course platform. The contract signing is in progress, so hopefully, next year, some people will be able to learn something new using the course. I’ve been invited to many more conferences than I spoke at. Had to choose where to spend my time. Money My work around this blog and anything professional that is not related to Netacea (the cybersec startup I’ve mentioned) only me money. cost Apart from this money pit, I am quite okay at managing my finances, saving it, and investing. I’m also fluent in tax codes. I don’t let money go to waste. I am following the stock market to a limited extent as well. All of this pays dividends and helps me feel more secure in life. I recommend everyone to have basic financial fluency. I won’t get into much detail and exact numbers, but I’ll share some stats to give you some insight into how I think about money and investing. I can share some guidelines for engineers in a separate article. Let me know. My net worth (assets less liabilities) is allocated between cash, real estate, and stocks. I am definitely real estate heavy but I have access to really good advice. Going forward, I’d prefer to have my net worth allocated in some business I run or contribute to in the form of work or investment. I am tracking my savings and investments as a whole by doing a monthly net worth evaluation (it’s a quick exercise at this point). I’ve been doing it since April 2019 and have been able to maintain a good pace of growth, albeit with some ups and downs. Don’t get all excited; the starting point was fairly low! My short advice for friends: use retirement tax-advantaged accounts buy the simplest stock market investments - index funds, S&P500, whole US stock market get a mortgage; it’s a low-interest rate leveraged capital, and overall properties keep up with inflation rates have a safety net with some small cash (as in a bank) pile to bail you out in emergencies Plans My plans regarding this blog and my online presence are still in the making. I want to aim for something that will keep giving me satisfaction while being relevant and impactful. Here are the goals I am thinking about: Launch and grow a newsletter up to at least 1000 subscribers. Shipping one successful SaaS tool on my own. And then grow or sell it. Grow my global (online) and local (at Netacea) influence as an engineering leader. Write one blog post per week. Publish video content and get a reasonable following. Regardless of the details of these, you’ll likely see much more from me next year! Stay tuned. Summary So yeah, a lot happened, and I want it to continue to happen. This year has been another great period of my life which I’m truly grateful for. As for this blog, I want to keep writing and being a part of the global community. After years of learning and working, I finally think like I have something to say. For me, writing has always been this elusive thing that I never quite got to do. I stopped hiding behind perfectionism and started sharing. And many people found it useful, which just makes me happy. I keep learning but this time, I make some of my private notes public. This year, I’ve learned a lot, made mistakes, and made new friends. The future looks exciting. See you there. Have the most wonderful year of your life. Don't forget to follow me on Twitter and subscribe to my blog’s for more tips and insights! @ horosin_ newsletter If you don't have Twitter, you can also follow me on . LinkedIn Also published . here

Reflecting On My 2023: A Year of Growth, Opportunities, and Financial Insights

Introduction This is my consistent coding for the past year 👨🏻‍💻 https://twitter.com/Dhanush_Nehru/status/1741475660978397453?embedable=true Additionally, I discovered that I was one among 0.4% of consistent coders on Leetcode 🧠 https://twitter.com/Dhanush_Nehru/status/1735666289027227690?embedable=true Mastering Consistency How was I so consistent? Here’s how I did it, I just enjoy coding and problem solving, so I thought of doing something better than my 100 Days Of Code Challenge, so I chose to do a 365 Day of Leetcode Challenge. “Choose a job you love, and you will never have to work a day in your life.” — Confucius . I love to solve problems, and my interest and passion for problem-solving made it a habit to face a new problem and solve it without any motivation. “Every man is divine and strong in his real nature. What are weak and evil are his habits, his desires, and thoughts, but not himself.” — Swami Vivekananda. Similar to how we do our daily tasks, problem-solving has become a habit for me without much pressure or inspiration. “First we make our habits, and then our habits make us.” — John Dryden. Similar to how you go to the gym and exercise and maintain your health, it is necessary to train your brain as well as the ability to code. “Programming is a journey, not a destination. The code you write today is not the code you will write tomorrow.” — Unknown. Consistency is an art. It was hard for me to be consistent a few years back, so in order to master consistency as a goal, I did this challenge. It’s not what we do once in a while that shapes our lives. It’s what we do consistently.” — Tony Robbins . Mistakes to Avoid Here are a few mistakes that you can avoid while doing leetcode, We generally force ourselves to get the solution anyway, and once we see the solution, we feel bad about ourselves, and all the negative self-talk comes into play. But, most people do not understand that you must know the basics first before solving that particular problem. How can you expect yourself to play chess well if you don’t know how the coins move? Clear your fundamentals/syntax of whatever programming language, then push yourself to solve the problem. Build your foundation first: You should start valuing your efforts rather than getting the solution. Problem-solving skills are developed in those 30 minutes of fighting with the problem to get the solution. Sometimes, when you are not able to get the solution on the initial days, it is okay to look into the solutions by others, but it should not be a regular practice. Getting to the solution is not everything: Pick up a pen and paper, try to think of all the possible solutions, and focus on building up the solution. Start with the smallest example, try to come up with a solution, and then optimize it with edge case scenarios, etc. Don’t code in your head: There are more than 2000+ problems on Leetcode, and you don’t need to solve all of them. I just coded it as a matter of consistency. However, you need not solve every single problem every day if you want to improve your problem-solving. Concepts are limited. Problems are infinite: Even if I could solve the problem on my own, I always go to the comment section and quickly scan over superior solutions. You may not be aware of how many more effective approaches and viewpoints there are to solving the same issue. Also, I have done many open sources, so it has helped me to view others co’ code in a better way. Read other’s code: Establish a timer for each task; the breakdown is as follows: easy tasks take around 15 minutes, medium tasks take about 30 minutes, and hard tasks take about 45 minutes. Try not to enjoy the moment of finding the answer right away. Always time yourself: No matter how many questions you solve in the contest, show up every time. Once you show up, you have completed the hardest part. Don’t care about ratings: After the contest try to solve the questions without any time limit, if you don’t get it then check other’s solutions understand what they have done, read about that particular topic, and solve it back again using the specific knowledge. Up-solve the contest questions again: I have answered many more questions about my journey in the video below. Do watch, like, to show your support 🙏🏻 subscribe to my channel “The important thing is not to stop questioning. Curiosity has its own reason for existing.” — Albert Einstein. https://www.youtube.com/watch?v=J-hDaEU8smE&embedable=true In the end, it doesn’t matter how smart or dumb or lucky you are, if you are consistent enough you can outwork all the people you think are talented or smarter than you. Also, life is not something that happens on weekends. It is something that happens every single day. A Big Thank You 🙏🏻 If you’ve made it this far, thank you! If you love this post, please give a like as a sort of encouragement and also share this post on social media, which would benefit others. Connect ⬇️ / / / / Twitter Instagram Github Youtube Newsletter Also published . here

Reflecting on My Year of Consistent Leetcode Practice and Mistakes to Avoid

Image by Geralt on Pixabay The trading realm is evolving unprecedentedly, with at the helm of this transformation. The ubiquitous integration of AI in trading is hard to ignore, given that the global AI market is projected to reach a staggering . This growth underscores the increasing importance of AI technologies and the new opportunities and challenges they introduce. AI $407 billion by 2027 As we navigate the pros and cons of AI in trading, it's essential to understand that it's a double-edged sword. On the one hand, AI presents groundbreaking efficiencies and potential profits, but on the other hand, it brings significant cybersecurity concerns in finance. This article offers a balanced, insightful examination of these contrasting aspects. Understanding AI in Trading AI trading strategies represent an innovative leap in the financial sector, blending high-tech algorithms with data analysis to maximize profitability. This enticing fusion of tech and finance paves the way for unprecedented market insights and investment opportunities. Let's delve into AI trading strategies, illuminating the past, present, and potential future. Definition and scope of AI in trading Trading using AI refers to the use of complex algorithms to make trading decisions. These systems analyze vast amounts of data and execute trades at lightning speeds. Automated trading systems have revolutionized modern finance, enabling high-frequency trading and reducing the likelihood of human errors. They offer the potential for greater efficiency and profitability, but their use also raises essential ethical and security questions. Historical context and the evolution of AI in finance The genesis of AI in finance began in the 1980s with rudimentary algorithmic trading. With advancements in technology, AI swiftly progressed. From simple predictive models, it evolved into complex neural networks by the 1990s. The advent of machine learning in the 2000s further propelled AI's capabilities. Today, are integral to finance, encapsulating trading, risk management, and financial planning. sophisticated AI trading strategies Pros and Cons of AI in Trading AI presents a fascinating blend of benefits and challenges. Its impact on the trading industry is transformative, reshaping the landscape in unprecedented ways. Let's uncover AI's intricate pros and cons in trading technology, shedding light on its potential to revolutionize trading as we know it. Pros of AI in trading Here are the pros of using AI trading strategies: Enhanced marketing efficiency AI trading strategies streamline and expedite the trading marketing process. They decipher complex market data, identify patterns, and accurately predict trends. This leads to informed decisions and targeted marketing strategies. Further, automated trading systems reduce costs and increase response times, boosting overall marketing efficiency. Superior data processing and analysis AI in trading revolutionizes , making financial decisions faster and more efficient. Automated trading systems can handle vast amounts of market data in real-time. data processing and analysis They identify subtle patterns and trends that humans could miss. These systems excel at predictive analysis, providing traders with insightful forecasts. This superior analysis capability translates to more precise, data-driven trading decisions, enhancing profitability. Automated decision-making and speed AI-powered trading systems ensure speedy and automated decision-making. They analyze and act on market data at an unrivaled pace, offering a competitive edge. This lightning-fast decision-making ability eliminates the lag associated with human intervention. It enables traders to capitalize on fleeting trading opportunities, which are commonplace in volatile markets. By eliminating human error and emotional trading decisions, AI ensures more strategic, efficient, and profitable trading. Cons of AI in trading Here are the cons of AI in trading: Ethical considerations and biases AI trading systems can inadvertently perpetuate biases, skewing trading decisions based on flawed algorithms or biased data. Ethical considerations arise when these systems prioritize profitability over fairness or transparency. Furthermore, such biases could lead to discriminatory trading practices, amplifying market disparities. This highlights the need for rigorous bias and ethics checks in AI trading strategies. Risk of over-reliance and loss of human oversight An over-reliance on AI in trading could result in a lack of human oversight. This absence of human judgment might exacerbate market risks. AI systems, while efficient, lack the intuition and adaptability inherent in human traders. This makes them susceptible to unexpected market changes. Moreover, an over-reliance could lead to complacency, with traders not fully understanding the underlying trading strategies. A balanced approach between AI and human oversight is crucial for sustainable and responsible trading. Cybersecurity threats and data privacy concerns While highly efficient, AI trading platforms expose financial markets to an increased risk of cyber-attacks. Cybercriminals can exploit weak security measures to manipulate trading algorithms and compromise sensitive data. Additionally, data privacy concerns arise as AI systems process large quantities of personal and financial information. Therefore, implementing in finance is paramount in AI trading to protect the integrity of trading strategies and the privacy of trader's data. robust cybersecurity The Impact of AI on Trading Strategies and Performance AI has revolutionized trading strategies with its accuracy and speed, fostering a new era of automated trading systems. These sophisticated systems are transforming traditional trading, offering innovative strategies and improved performance. Innovative trading strategies enabled by AI harness the power of artificial intelligence to analyze vast data sets, identify trading opportunities, and execute trades at lightning-fast speeds. These strategies can learn from market patterns and trends and adapt their tactics accordingly. AI trading strategies AI's ability to process high volumes of data and make real-time data-driven decisions significantly enhances trading operations' efficiency and profitability. Incorporating AI in trading strategies has ushered in a new era of precision, speed, and effectiveness in financial markets. Performance Analytics Automated trading systems provide robust performance analytics, furnishing traders with critical insights. These systems analyze market data, assessing trade performance with pinpoint precision. The analytics highlight effective strategies and potential areas for improvement. This data-driven method leads to more informed decision-making and improved trading outcomes. Risk management in AI trading AI significantly bolsters risk management in trading. It delivers predictive analytics, enabling traders to foresee potential market downturns and adjust strategies proactively. Enhanced cybersecurity measures in AI trading systems also ensure data integrity and privacy. Due to AI's ability to detect anomalies, cybersecurity threats are identified and mitigated promptly, safeguarding financial transactions and confidential data. AI's role in cybersecurity in finance is crucial, ensuring safe and secure trading operations. AI's Impact on Employment in the Trading Sector AI's integration into the trading sector isn't just transforming strategies—it's revolutionizing the job landscape. As we delve into its impact on employment, we'll explore the delicate balance between job displacement and creation. We'll also discuss the changing skill requirements in this rapidly evolving industry. This exploration will shed light on the increasingly vital role of human expertise amidst the rise of machines. Job displacement vs. job creation AI has led to job displacement in the trading sector. Due to automated trading systems, traditional roles, such as floor traders and stock analysts, are becoming redundant. These systems can execute trades faster and more accurately than human traders, enhancing efficiency and performance. Moreover, AI can analyze vast amounts of financial data in real-time, eliminating the need for human analysis. On the flip side, AI has also stimulated job creation. are emerging. For instance, AI trading strategists analyze AI trading outcomes and refine AI algorithms. There's also a surge in demand for AI compliance officers who ensure AI trading systems adhere to regulatory standards. New roles that require expertise in AI and machine learning AI developers and cybersecurity specialists are also in high demand to build and protect these systems. This indicates that while AI may replace specific jobs, it's also creating new roles for those with specialized skills. Changing skill requirements The shift towards AI trading mandates traders to adapt their skill sets. A strong understanding of AI algorithms, data analysis, and financial modeling becomes crucial. Expertise in programming languages like Python that aid in developing AI strategies is beneficial. Lastly, skills in risk management, understanding AI ethical considerations, and regulatory compliance are indispensable in this increasingly AI-driven trading environment. The Human Element in AI Trading While AI has disrupted trading with its speed, efficiency, and data-crunching prowess, human insight remains essential. This intersection of AI and human expertise creates a dynamic, transformative landscape in trading. The nuanced balance between these two elements unfolds as we delve further, revealing their collective impact on AI trading strategies. Let's explore the enduring relevance of the human element in this AI-dominant environment. Importance of human intuition and management Human intuition in trading continues to hold ground amidst advanced automated trading systems. Experienced traders, with their intuitive understanding, can discern patterns in market behavior that AI might overlook. Furthermore, they can make adaptive decisions based on fluctuating market contexts, something that AI systems may struggle with given the limited predefined parametrics. Therefore, while automated trading systems provide significant benefits, human oversight often brings balance, propelling successful trading strategies. Balancing AI and human decision-making Striking a balance between AI and human decision-making in trading has its unique set of challenges. AI tools excel in processing vast data, making quick decisions, and reducing human errors. On the other hand, they lack the intuitive understanding humans have of market subtleties. Humans excel at making flexible judgments based on experience and context. However, they can be slow and prone to errors. The ideal scenario is a symbiosis—AI offering efficiency and speed, humans providing oversight, nuance, and intuition. Training for tomorrow's AI-enhanced workforce Preparing for an AI-enhanced workforce entails comprehensive training and upskilling initiatives. Companies must foster a continuous learning culture, encouraging employees to embrace AI tools. Training should focus on understanding AI's capabilities, application in their respective roles, and ethical considerations. This readiness will help businesses adapt swiftly to AI's influence, particularly in dynamic sectors like marketing, where data-driven strategies are gaining prominence. Exploring Cybersecurity in Finance Evolving technology comes with increased cybersecurity risks, particularly in finance. While financial institutions harness AI's immense power, they must simultaneously address cybersecurity concerns. The following sections dive deeper into this critical interplay, highlighting the importance of robust security measures in our increasingly digital world. Emerging threats in AI systems AI systems in finance are facing emerging cybersecurity threats. Hackers are exploiting AI's intricate algorithms to launch sophisticated attacks. These threats can compromise data integrity, disrupt trading operations, and tarnish a company's reputation. Additionally, deepfakes, powered by AI, pose a significant identity verification challenge. Consequently, the industry must invest heavily in advanced cybersecurity measures to counter these risks. Strategies for securing AI in trading Here are practical yet helpful strategies to secure your trading journey: Employing multi-factor authentication is crucial to secure AI in trading. This strategy enhances access control, reducing unauthorized entry. Regular audits can help detect anomalies early. Encrypted communication protocols bolster data security during transmission. Continuously updating AI algorithms increases resilience against emerging cyber threats. Privacy Concerns in AI-Driven Trading Privacy concerns occupy a pivotal role in the rapidly evolving realm of AI-driven trading. As financial institutions leverage AI's prowess, they grapple with an unseen adversary—privacy breaches. These intrusions are detrimental to their reputation and potentially risk their financial stability. Now, let's explore this further and see how the finance sector can navigate this precarious cyber landscape. Data collection and usage In AI-driven trading, vast amounts of data are collected relentlessly. This data, encompassing personal details and transaction histories, fuels the predictive capabilities of AI models. However, such extensive data collection can infringe upon your privacy, as sensitive information could fall into the wrong hands. Moreover, concerns about how this data is stored, processed, and shared persist, warranting stringent data governance protocols. The delicate balance between leveraging data for AI and maintaining privacy is a pressing issue in today's digitalized trading world. Legal implications of privacy breaches When privacy breaches occur, the legal fallout can be severe. Financial institutions may face hefty penalties if found to be non-compliant with data protection laws. Additionally, they may suffer substantial reputational damage. Clients could lose trust and opt for other service providers, leading to a loss of business. Therefore, financial entities must adhere strictly to laws and regulations, taking a proactive stance in ensuring the safety and confidentiality of user data. User consent and data rights Consent and data rights form the bedrock of ethical AI trading. Users must knowingly give consent, understanding the extent of data use. Explicitly stating data rights upholds transparency and builds trust. Informed consent is fundamental to adhere to cybersecurity norms. It fuels the relationship between the finance sector and clients, anchoring it in trust. Redefining Markets With AI: Balancing Risks and Rewards AI is redefining trading markets and unlocking potential while introducing new risks. Emphasizing data privacy and cybersecurity while exploiting AI's capabilities can strike a balance. The benefits are significant: AI can identify trading patterns, automate transactions, and improve decision-making. However, the risks, including data breaches and privacy infringements, are concerning and demand attention. In conclusion, as AI revolutionizes trading markets, it will be crucial to balance its rewards and risks. The future holds promise if we navigate responsibly, ushering in an efficient and secure trading era.

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