#merge sort algorithm

[ceyhanmedya]

Algorithm

New Post has been published on https://hazirbilgi.com/what-is-algorithm-how-is-it-created/

Algorithm

What is algorithm? How is it created?

Algorithm ; It is the name given to the combination of methods and steps planned to perform a job or solve a problem. It is generally defined as a set of operations with a clear beginning and end, used in the field of programming or in solving mathematical problems. It is the regular determination of the movements, processes or works required in order to carry out the work planned to be done, in steps.

It is one of the two approaches used in problem solving and is more preferred than the heuristic solution approach. It is among the subjects that must be learned before a programming language for a computer programmer and can be defined as the most important topic of programming.

History

This concept first appeared in the 9th century and was first introduced by Khwarezmi . The scholar, whose full name is Ebu Abdullah Muhammed Ibn Musa al-Khorezmi, made great contributions to the field of mathematics by putting his work in algebra into writing. Harezmi’s most widely known book with Latin translations; Hisab is al-algebra and al-mukabala (حساب الجبر و المقابلة). This book is also described as the first known collection of algorithms .

The word algorithm originally comes from the word ‘ Algorism ‘. The reason for this is that Khwarezmi’s book was difficult to pronounce in Europe after it was translated into Latin, and Europeans who could not say the name of Khwarezmi called it ‘Algorism’. 

As a result, although the concept of Algorism began to be used in the sense of problem solving with Arabic numerals, it turned into its current form over time and started to be used in a general context. Finally, after the 1950s, especially with the developments in computer technologies, a concept came to represent the way almost every work to be done in the field of programming and the steps to be applied for its construction.

Algorithm creation

The algorithm can be in the form of prose and narrative, or in the form of a flowchart . Generally preferred is the one in the form of a flowchart.��In order to create a process, some symbols are used to describe the work to be done. These symbols are of great importance, especially in terms of developing a program and understanding the process.

In order to create an algorithm, the work or problem to be done must be clearly defined and solution methods must be determined. In order to do the work or to implement the solution, all the steps that will lead to the result from the initial movement should be specified in the order of application. One of the most important concepts in this subject is the flow chart; The schematic representation of the solution of an algorithm is called a flowchart. 

Some flowchart commands are as follows;

Start-Finish (terminator)  

Input  

Process  

viewing 

Decision  

iterative process  

manually entered value

Examples

Example 1 (Explanation with everyday concepts)

Targeted Job:  Going from home to school

Start: Home

End: School

Algorithm:

Step 1: Open the door Step 2: Put on the shoes Step 3: Close the door Step 4: Exit the building Step 5: Walk the road Step 6: Walk to the 2nd fork Step 7: Turn left Step 8: Finish the road Step 9: Enter the school.

Example 2 (Explanation with programmatic concepts)

Intended Business:  Finding the factorial value of a number entered by the user

Getting Started:  Starting the program

Finish:  Show the result

Algorithm:

Step 1: Run the program Step 2: Define the variables factorial,i and n Step 3: Define the initial values of the variables factor = 1 i = Step 4: Read the n value entered from the screen Step 5: Repeat until (i=n) equality is achieved factorial = factorial*i i = i+1 Step 6: Show the value of the factorial variable

Some Important Algorithm Types

Search algorithms

Memory management algorithms

computer graphics algorithms

Combinatorial algorithms

Graph algorithms

evolutionary algorithms

genetic algorithms

Crypto algorithms or cryptographic algorithms

Rooting algorithms

Optimization algorithms

Sorting algorithms

Data compression algorithms

Conclusion

This concept can be encountered by people in all areas of life in general. Because the concept of algorithm represents the way to the solution rather than the solution. A plan prepared for a journey to be made and the steps determined for the completion of a job basically represent the algorithm. 

An algorithm that has not been implemented and whose results have not been observed is not deemed appropriate for patenting by law. But algorithms in software have been the subject of much discussion at this point. 

algorithm,algorithm definition,acls algorithm,dijkstra algorithm,rsa algorithm,rubik’s cube algorithm, quick sort algorithm,merge sort algorithm,binary search algorithm,greedy algorithm,instagram algorithm,algorithm analysis,algorithm synonym,algorithm aversion,algorithm ap psychology definition,algorithm app,algorithm art,algorithm antonyms,algorithm addition,algorithms and data structures,algorithm abbreviation,apriori algorithm,

[data-science-blogs-1]

All about Merge Sort Algorithm - Sorting Algorithm Explained

Introduction to Merge Sort Algorithm Are you looking for an efficient sorting algorithm? Then, look no further than merge sort! Merge sort is a divide and conquer approach to sorting data that has many advantages and benefits, making it an ideal choice for many applications. In this blog, we’ll explore the ins and outs of merge sort algorithms by covering its algorithmic steps/process,…

[m-v-d]

woah this programming tutorial is easy!

[echotunes]

programming mergesort to do my battleship exchange signups like this, too, is studying,

[crescentmp3]

i am done watching the week 3 lecture! ^^

[varunrajkalse]

6 Algorithms Every Developer Should Know

6 Algorithms Every Developer Should Know As a developer, it is essential to understand algorithms to create efficient and scalable software applications. Algorithms are sets of instructions that perform a specific task, such as sorting data or searching for information. By learning about these six essential algorithms, you can improve your coding skills and create better applications. By…

[robot344]

Sorting algorithms in Python:

Sorting algorithms in Python is an essential part of computer science and are used to organize data in a specific order. Python, being a high-level programming language, provides several built-in functions and libraries to perform sorting operations on data structures like lists, tuples, and arrays. In this blog post, we will discuss various sorting algorithms available in Python, their time…

[neurotypical-sonic]

tails' favourite sorting algorithm is merge sort, and sonic's is shell sort

[yokowan]

tethys, do you have a favourite sorting algorithm? if so, what is it?

I LIKE MERGE SORT!!!! RUNNING IT KINDA TICKLES ꞉D

[zahri-melitor]

My comments on the Extended Generational Sorting Algorithm:

Gosh there are some murky in-betweens here.

G-1 – JSA and teams like the All-Star Squadron and the Blackhawks. The WWII edition. This is occasionally merged with G0 as timelines shift, but includes Hippolyta, Ted Knight, Sandra Knight (as Phantom Lady), Alan Scott, Jay Garrick, etc. A lot of this cohort have aging issues and several have grandkids in G1 or G1.5. Zinda simultaneously belongs to this group and G1.5.

G0 – JSA, the gap between WWII and the first JLA. This is the younger JSA cohort who aren’t so tied to WWII and the gap after. Dinah Drake. Ted Grant. Johnny Quick. Giovanni Zatara. Walter Chase (the Acro-Bat). Bruce’s parents. The Kents. Jim Gordon. Etc.

G1 – JLA land! Bruce, Clark, Diana, Ollie, Barry, Hal, Arthur, etc. You know them. Your idea of a headlining JLA includes these folk.

G1.5 – Birds of Prey and JLI zone. Characters too old to be Titans cohort but younger/clearly different than the G1 headliners. Barbara Gordon and Dinah Lance are the stalwarts of this group, plus I’ll add Helena Bertinelli, Cameron Chase, Kate Spencer, Kendra, etc. I guess I’d probably put Harley Quinn, agewise, here too. Also would add Beatriz, Tora, Booster, Ted Kord, etc. Guy and Zatanna sort of bounce between here and G1 depending on storyline.

G2 – it’s the Titans! Dick, Donna, Wally, Roy, Garth, Victor, Gar, Kory, Raven etc. Their agebounds are probably Roy as the oldest and Gar as the youngest, though Gar’s given to them as a courtesy – he’s realistically a member of G2.5, he just hangs with G2. We also add Kyle and Connor and Jesse Quick etc to this cohort despite them not being core Titans given their strong connections to particularly Donna and Wally.

G2.5 – The JL Taskforce kids and Jason’s non-existent team. Ray Palmer’s Teen Titans. This is a group of individuals that has never properly coalesced. Overlaps in age with both the bottom of G2 and the top of G3 but distinctly don’t belong to either. Jason, Ray, Grant, Argent, Cynthia, Eddie, Snapper Carr, plus Danny Chase and arguably Gar all fall into this group. Rose Wilson overlaps with G3 but vibeswise probably also belongs to this group. I am tossing up whether Anissa and Jennifer Pierce belong here or in G2.

G3 – Young Justice. Tim, Kon, Cassie, Bart, Cissie, Greta, Anita. Cass Cain belongs here despite being the same age as several G2.5s. Steph, Charlie, Black Alice, Jaime, Zachary Zatara, even a handful of the newer folk like Jinny Hex slot in here. Several Supergirls including current Kara, Courtney Whitmore IS a member of this group and the three oldest Marvel kids (Billy, Mary and Freddy) are currently aged into this.

G4 – Damian’s Teen Titans. Damian, Jon Kent (yes even still with the age up), Emiko Queen, Ace West etc. If they are still a teen right now in DC storytelling or SHOULD be a teen, they belong here (if they’re a teen and SHOULDN’T be they’re probably a G3/G5). The Gotham Academy kids. Arguably the Titan Academy kids too? Agewise the DEO Titans kids but spiritually probably not (also the chances of us ever seeing them again is…low) The younger Marvel kids (Eugene, Pedro and Darla especially) are with this group.

G5 – so this group are either alternate G3 or G3.5s. Too new and too un-networked with G3 to be absorbed. Jace Fox, Yara Flor, Jackson Hyde, Duke Thomas and the We Are Robin cohort all belong here. Kong Kenan, Avery Ho, etc also are members.

G6 – Titans Offspring Gen. Almost everyone in this group has been artificially aged, which is a thing, hey. Lian, Irey, Jai, Cerdian, Robbie. Maxine, obviously. Otho and Osul-Ra.

G7 – Help I’m From Earth-One: Power Girl and Helena Wayne.

G8 – The Lost Children – also Help I’m From Earth-One in a lot of respects but they’re in their teens, not adults. May get folded into other groups if they get more use.

[snapscube]

do you have a favorite sorting algorithm

man i don’t fuckin know i’m just out here watching cartoons and eating a little bit more fried food than i should be you think i got time to think about an algorithm that puts elements of a list into an order. The most frequently used orders are numerical order and lexicographical order, and either ascending or descending. Efficient sorting is important for optimizing the efficiency of other algorithms (such as search and merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for canonicalizing data and for producing human-readable output. Formally, the output of any sorting algorithm must satisfy two conditions:

The output is in monotonic order (each element is no smaller/larger than the previous element, according to the required order).

The output is a permutation (a reordering, yet retaining all of the original elements) of the input.

For optimum efficiency, the input data should be stored in a data structure which allows random access rather than one that allows only sequential access.

[gayarograce]

🌻

(Oh man, the mortifying ordeal of actually having to pick something to talk about when I have so many ideas...)

Uh, OK, I'm talking about galactic algorithms, I've decided! Also, there are some links peppered throughout this post with some extra reading, if any of my simplifications are confusing or you want to learn more. Finally, all logarithms in this post are base-2.

So, just to start from the basics, an algorithm is simply a set of instructions to follow in order to perform a larger task. For example, if you wanted to sort an array of numbers, one potential way of doing this would be to run through the entire list in order to find the largest element, swap it with the last element, and then run though again searching for the second-largest element, and swapping that with the second-to-last element, and so on until you eventually search for and find the smallest element. This is a pretty simplified explanation of the selection sort algorithm, as an example.

A common metric for measuring how well an algorithm performs is to measure how the time it takes to run changes with respect to the size of the input. This is called runtime. Runtime is reported using asymptotic notation; basically, a program's runtime is reported as the "simplest" function which is asymptotically equivalent. This usually involves taking the highest-ordered term and dropping its coefficient, and then reporting that. Again, as a basic example, suppose we have an algorithm which, for an input of size n, performs 7n³ + 9n² operations. Its runtime would be reported as Θ(n³). (Don't worry too much about the theta, anyone who's never seen this before. It has a specific meaning, but it's not important here.)

One notable flaw with asymptotic notation is that two different functions which have the same asymptotic runtime can (and do) have two different actual runtimes. For an example of this, let's look at merge sort and quick sort. Merge sort sorts an array of numbers by splitting the array into two, recursively sorting each half, and then merging the two sub-halves together. Merge sort has a runtime of Θ(nlogn). Quick sort picks a random pivot and then partitions the array such that items to the left of the pivot are smaller than it, and items to the right are greater than or equal to it. It then recursively does this same set of operations on each of the two "halves" (the sub-arrays are seldom of equal size). Quick sort has an average runtime of O(nlogn). (It also has a quadratic worst-case runtime, but don't worry about that.) On average, the two are asymptotically equivalent, but in practice, quick sort tends to sort faster than merge sort because merge sort has a higher hidden coefficient.

Lastly (before finally talking about galactic algorithms), it's also possible to have an algorithm with an asymptotically larger runtime than a second algorithm which still has a quicker actual runtime that the asymptotically faster one. Again, this comes down to the hidden coefficients. In practice, this usually means that the asymptotically greater algorithms perform better on smaller input sizes, and vice versa.

Now, ready to see this at its most extreme?

A galactic algorithm is an algorithm with a better asymptotic runtime than the commonly used algorithm, but is in practice never used because it doesn't achieve a faster actual runtime until the input size is so galactic in scale that humans have no such use for them. Here are a few examples:

Matrix multiplication. A matrix multiplication algorithm simply multiplies two matrices together and returns the result. The naive algorithm, which just follows the standard matrix multiplication formula you'd encounter in a linear algebra class, has a runtime of O(n³). In the 1960s, German mathematician Volker Strassen did some algebra (that I don't entirely understand) and found an algorithm with a runtime of O(n^(log7)), or roughly O(n^2.7). Strassen's algorithm is now the standard matrix multiplication algorithm which is used nowadays. Since then, the best discovered runtime (access to paper requires university subscription) of matrix multiplication is now down to about O(n^2.3) (which is a larger improvement than it looks! -- note that the absolute lowest possible bound is O(n²), which is theorized in the current literature to be possible), but such algorithms have such large coefficients that they're not practical.

Integer multiplication. For processors without a built-in multiplication algorithm, integer multiplication has a quadratic runtime. The best runtime which has been achieved by an algorithm for integer multiplication is O(nlogn) (I think access to this article is free for anyone, regardless of academic affiliation or lack thereof?). However, as noted in the linked paper, this algorithm is slower than the classical multiplication algorithm for input sizes less than n^(1729^12). Yeah.

Despite their impracticality, galactic algorithms are still useful within theoretical computer science, and could potentially one day have some pretty massive implications. P=NP is perhaps the largest unsolved problem in computer science, and it's one of the seven millennium problems. For reasons I won't get into right now (because it's getting late and I'm getting tired), a polynomial-time algorithm to solve the satisfiability problem, even if its power is absurdly large, would still solve P=NP by proving that the sets P and NP are equivalent.

Alright, I think that's enough for now. It has probably taken me over an hour to write this post lol.

[the-ark-awaits]

Hello all you may remember me from such bangers as 'show me the proxies in marble hornets' and 'and another thing'

oday um here to talk about how we've fucking regressed as a fandom since creepypasta and marble hornets on ao3 got. presumably merged as a fandom tags bc sorting for exclude crossovers still shows creepypasta fic. in fact doing that just now to confirm this, the very first fic on the list was creepypasta.

so obviously this is a huge pain in the ass for anyone who wants marble hornets fanfic and only marble hornets fanfic. you cant even remove creepypasta fics with exclude crossover, youd have to do it manually with filtering options not everyone knows how to use. and we shouldnt have to yknow? you should be able to go in your fandom tag on ao3 and find only that fandom and crossovers (which should be easily filtered out by exclude crossovers) same as here on tumblr crosstagging is a huge issue but the worst part of it is that the continuous crosstagging in recent years has caused the fandom tags to be merged (not fully as shown by the fact that the numbers for amount of fic in each tag is different) but enough that they're considered the same universe by ao3 which is. blatantly untrue.

creepypasta is a catchall term for internet short stories made by a community, marble hornets is one single webseries online. fuck the creepypasta fandom wouldnt be what it is without huge swaths of shit stolen from marble hornets (like yknow, the pages, the operator symbol, masky and hoodie) but that doesnt mean they are marble hornets fans that doesnt mean theyre making marble hornets content. that would be like saying that since fnaf and batim are kinda similar and the fans have an overlap that means theyre the same and should be tagged the same. they arent, and shouldnt be yknow?

also apologies this isnt the best post im kinda fried rn and im stuck on mobile

that not withstanding its fucking depressing. this did not used to be an issue. thr only fics tagged with both were generally easy to ignore or a real honest to god crossover, but now i swear you look at the mh tag on ao3 and the majority of the recent fics are crosstagged crp fics with giant tag lists that tack up the whole page and tag anyone who is so much as mentioned

and maybe this is a step too far here. but i really think this is bc of tiktok. the people crosstagging posts and fics seem to be the same type to complain avout the 'ao3/tumblr algorithm' not favoring them. but there is no algorithm, just annoyed fans who have to dig for their actual content because people dont have common decency anymore. theres an etiquette you need to follow for shit like this. like how would you feel if like. i dunno. fucking... genshin (just an example of a large fandom or whatever made a character cameo out of like jeff the killer and suddenly all the crp tags were filled with genshin posts not even related to or barely mentioning the character, just ti try and get more clicks?

youd be pretty fucking annoyed having to scroll past all that to find actual creepypasta content huh?

thats the same issue happening here, and honestly i think its a huge issue. for obvious reasons but also bc its so much harder to find mh content now that im sure its incredibly disheartening to be a creator in the fandom rn and foe the past few years. you work and make content for your rather small fandom and its buried under barely related shit, its gonna feel bad yknow? especially when that content gets more clicks bc. frankly theres more creepypasta fans than mh fans just bc of what creepypasta is format wise. its collectively made shortstories. you can like one or two and bc a crp fan, its not like that for mh

this is going kinda off my starting topic but anyways if theres any ao3 tag wrangles following me or who see this.

please for the love of god i beg of you to do anything you can to unmerge those tags i will do anything ill get receipts proving they're separate things please unmerge the tags im dying here

[lhazaar]

literally tumblr could capture so much of the social media market right now today by emphasizing their flexibility for content creators. this site is not Easy to grow on, no, but i don't think it needs to be in order to actually attract creatives—the things that make twitter and tiktok so easy to go viral on are also the things that enshittify social media. i don't want a super-discoverable algorithm, i want a more robust tagging system so that artists can upload their work and then sort it into genre tags, like #painting or #animal art or #concept art, and not be limited to the first five tags on their actual post. i want those tags searchable. give us a discovery page where we get, say, recent uploads to those genre tags, and maybe some of the "popular" ones that are picking up notes. like every art website for the past 15 years has been doing

like the best things about this site for artists, in my experience, are 1) flexibility and 2) long-term archival. the queue helps so much. your pieces will keep circulating for a long time organically just from people queuing posts. you aren't required to upload in specific resolutions or formats and i genuinely like a lot of the modifications staff has made to the photo upload process over the past couple years (uploading more than 10 pieces? being able to merge photo and text in the body of the post? hell yeah!), but tumblr has a compression problem and the full-screen viewer is glitchy and user-hostile. deviantart managed to figure that out and i think tumblr could too and that would attract, say, a ton of painters who moved to twitter for their portfolios. this site is really good in terms of allowing you to fully customize your blog's web interface and users have been figuring out how to make it work for us for a long time (see, for example, themes that are set up to host webcomics on your tumblr and allow you to click through posts like you're turning a page, in chronological order)

i don't even hate the concept of tumblr live! i think it's weird in its current iteration because they partnered with some shady fucking third party app, but can you imagine a native streaming functionality on this site that actually worked? i would be thrilled to be able to just jump into artists' livestreams. also i would absolutely use that to show people crowbar's harness walks. you don't have to enshittify it and try to shove monetization down people's throats, just give people the platform to so much as host their work and exist first. that's what artists don't have right now. deviantart has sucked ass since at least the eclipse redesign and twitter is actively dying; weasyl never really took off and the only people on furaffinity are either trapped there by their customer base or varying levels of covert about their neonazi shit. online Art Communities right now don't have anywhere, and tumblr could be that, and i don't think they're going to take the opportunity

[jurysoft-raas]

Top 10 Skills to Look for in a Python Developer in 2025: How Jurysoft Helps You Hire the Best Talent

As we approach 2025, Python continues to dominate the programming landscape, offering unparalleled versatility in fields like web development, data science, machine learning, and automation. The demand for skilled Python developers is only growing, and finding the right talent can significantly impact the success of your projects. At Jurysoft, we understand the challenges of hiring the best Python developers, which is why we focus on delivering top-tier professionals with the skills that matter most.

In this article, we'll explore the top 10 skills you should look for in a Python developer in 2025 and show you how Jurysoft can help you hire the right developer to meet your unique needs.

1. Mastery of Python Fundamentals and Advanced Concepts

A strong foundation in Python basics is non-negotiable. Developers should be proficient in variables, data types, loops, functions, and control flow. But the best developers take it a step further, demonstrating expertise in advanced features like decorators, context managers, and lambda functions.

At Jurysoft, we ensure that our developers not only excel in Python fundamentals but are also capable of handling more sophisticated programming challenges, ensuring they can write clean, scalable, and efficient code for any project.

2. Expertise in Web Development Frameworks (Django, Flask, FastAPI)

Web development is one of the most common areas for Python developers, and proficiency in popular frameworks like Django, Flask, and FastAPI is crucial. Django is perfect for large, enterprise-level applications, while Flask offers a lighter, more flexible framework, and FastAPI is optimized for high-performance APIs.

With Jurysoft, you get access to developers who are experts in these frameworks, ensuring that your web applications are developed efficiently, securely, and are built to scale according to your business needs.

3. Deep Knowledge of Data Structures and Algorithms

Whether you are building data-heavy applications or working on performance optimization, a strong understanding of data structures and algorithms is a must. Developers should know when and how to use lists, stacks, queues, trees, and graphs, and should be familiar with algorithms for sorting, searching, and optimizing performance.

At Jurysoft, we prioritize hiring developers with a sharp focus on problem-solving skills. Our developers are well-versed in writing efficient algorithms that can handle large datasets and complex tasks with ease.

4. Proficiency in Data Science and Machine Learning

Python is the language of choice for data science and machine learning, and a good developer should be comfortable using libraries like NumPy, Pandas, Matplotlib, SciPy, and Scikit-learn. With the rise of AI-driven applications, the ability to build predictive models and analyze big data is more valuable than ever.

If your project involves machine learning or AI, Jurysoft connects you with developers who are not only proficient in these libraries but also experienced in deploying machine learning models to production.

5. Cloud Computing Experience (AWS, Google Cloud, Azure)

In today’s world, cloud computing is essential for building scalable, high-performance applications. Python developers should have hands-on experience with major cloud platforms like AWS, Google Cloud, and Microsoft Azure. They should know how to deploy applications, manage databases, and integrate with cloud-native services like Lambda, S3, and Kubernetes.

Our developers at Jurysoft are cloud-savvy, ensuring your applications are optimized for cloud environments and can handle rapid scaling as your business grows.

6. Version Control (Git) Proficiency

Version control systems, especially Git, are essential for collaboration and managing project versions. Skilled developers should be proficient in using Git for branching, merging, and resolving conflicts. A strong Git workflow ensures that team members can work simultaneously on the same codebase without disrupting progress.

At Jurysoft, we emphasize the importance of a seamless development process. Our developers are experts in using Git to streamline collaboration and maintain code integrity throughout the development cycle.

7. Expert Testing and Debugging Skills

Writing code is only half the job; testing and debugging are what ensure the software works correctly and efficiently. Developers should be skilled in writing unit tests, conducting integration testing, and using frameworks like PyTest or unittest. Additionally, the ability to debug complex issues and optimize performance is essential.

With Jurysoft, you can be assured that the developers we provide are well-versed in testing best practices, ensuring your software is reliable and bug-free from the start.

8. Security Best Practices

Security is a growing concern for businesses, especially as cyber threats continue to evolve. Python developers should understand best practices for writing secure code, such as preventing SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF). They should also be proficient in encryption, authentication, and secure API design.

At Jurysoft, we prioritize security across all our development projects. Our developers are trained in industry-standard security practices, ensuring your application is safe and protected from potential vulnerabilities.

9. Strong Communication and Collaboration Skills

While technical expertise is key, communication and collaboration are equally important. A great Python developer needs to work effectively with team members, product managers, and clients. They should be able to explain technical concepts clearly and provide updates on progress.

At Jurysoft, we not only focus on technical skills but also emphasize the importance of soft skills. Our developers are collaborative team players who can communicate effectively, ensuring smooth project execution and alignment with business goals.

10. Continuous Learning and Adaptability

Technology is always changing, and a great Python developer must be committed to learning new tools, techniques, and technologies. Whether it’s exploring new Python libraries, attending conferences, or taking online courses, the best developers are those who are always evolving with the industry.

At Jurysoft, we believe in fostering a culture of continuous improvement. Our developers are passionate about learning and staying up to date with the latest Python trends, ensuring they can apply the newest technologies to your project.

Why Choose Jurysoft for Your Python Developer Needs?

At Jurysoft, we understand that finding the right Python developer can be challenging. That's why we specialize in providing businesses with top-notch Python developers who are experts in the latest technologies and best practices.

Whether you need a developer for a short-term project, long-term partnership, or specialized task, Jurysoft can help you find the right match. We take pride in our rigorous hiring process, which ensures that our developers are not only highly skilled but also a great fit for your company culture.

From web development to machine learning and cloud computing, Jurysoft is your trusted partner for hiring Python developers who can take your projects to the next level.

Contact us today, and let us help you find the perfect Python developer for your team in 2025!

[codeshive]

Solved COMP 3270 Assignment 1 – Asymptotic Analysis of Sorting Algorithms

1. Overview To empirically evaluate 4 sorting algorithms and verify their theoretical upper bound. The sorting algorithms we will evaluate are: merge sort, quick sort, insertion sort, and selection sort. A starter code with helper functions and implementations of 2 algorithms (selection sort and merge sort) has been provided. Your task is to implement the remaining two sorting algorithms (quick…