#binary tree program

[nerdymemes]

[1o1percentmilk]

and then u have me who understands theory but doesnt know how to program shit!!!

[sufiblackmamba]

[tellltaleacademy-if]

PLAY THE DEMO HERE (30k)

You are an independent trainee trying to survive through a big company's new survival show, Telltale Academy, but things take a dark turn when a mysterious site called GUMIHOCOM, starts leaking the contestants dark secrets, getting them kicked out one by one. They couldn't possibly know what you've done, right?

There is no way they could publish something like that.

You can't know for sure, can you ? The threat claws over your nape. To save yourself and your debut, you have to find out who is behind GUMIHOCOM, or at least get them to leak your fellow contestants secrets before yours !

ᡣ𐭩 Play as female or AFAB non-binary.

ᡣ𐭩 Romance and investigate your fellow contestants.

ᡣ𐭩 Manipulate situations for screen time and popularity.

ᡣ𐭩 Pick songs and concepts for your stage performances.

ᡣ𐭩 Engage in ships and fanservice.

ᡣ𐭩 Sabotage your rivals and bribe staff.

ᡣ𐭩 Choose your skills, strengths and weaknesses as an idol.

ᡣ𐭩 Bite down the memory of that night…..

NYLA SARATHKUMAR (F,21) [ RO ] Daughter of the cyber-security CEO, Nyla is the only contestant that seems chill with potentially being exposed online. Wether she's a wolf in sheep's or a lucky go-lucky goofball, being close to her means safety. And it doesn't hurt that she's just so sweet. Will your affection for her get in the way of your need for survival?

NOH DAMBI (F,21) [ RO ] A lost it-girl, Dambi is an ex-member of a famous girl group who got kicked out for bullying accusations that have since then been " disproven ". Now she turns back to the spotlight for her major comeback, but nobody seems to believe she's truly innocent. She seems so lonely and misunderstood, someone who needs a kind hand. But can you trust your heart to her ?

MACY LEE WALSH (F,20) Being the sister of a well-known Kpop gossip youtuber to the likes of Sojang, Macy knew she was walking into a piranã bowl when she joined Telltale Academy. The most likely culprit, when then leaks start turning up her head is immediately on the market for a high prize. And everyone must be right, right? The apple never falls too far from the tree.

SOAPY (F/M,2X) [ RO ] Your fansite, your knight in shining armor, your stalker? Nobody has ever had your back like your biggest fan. They would do anything for you, even leak other contestants scandalous secrets. Or at the least you hope so.

MA YIFEI [ F, 25 ] - A rich girl and former member of Chinese group SNH48 Yifei would be the epitome of an ideal female idol, if she wasn’t a huge lesbian. For mean girl who’s obsessed with the aesthetics of perfection and femininity, that’s a pretty rough secret to keep, specially when you start to develop feelings for the girls you're supposed to be kicking into the ground .

SABIRA OMAROVA, [ F, 23 ] - A Russian Tatar model who landed herself in this program through a series of unfortunate events, and the object of Yifei’s unrequited obsession. Engage in Love Triangle route where you can be Yifei’s Rebound and romance Sabira at the same time.

TADA EMIKO, [ F, 2X ] - One of the company’s oldest trainee’s and an unbreakable soul that seems to maintain her spark no matter what. A true idol.

KIM AGATHA, [ F, 20 ] - Weird girl central. A former child model and fellow long time trainee at LOVEKRAFT ENTERTAINMENT, she seems to be the CEO’s favorite.

LI MAYUKA, [ F, 22 ] - The life of the party. No filter and no discipline, Mayuka really doesn’t seem like a Kpop trainee, but maybe her rebellious nature is exactly what you need to shield you from the horror of this industry.

[paperometria]

Ieri ho avuto una telefonata con una dei docenti del corso universitario dove insegnerò a Settembre, ed è stata la goccia finale su un vaso colmo di sfiducia verso il sistema, al punto tale che non so se continuerò questa esperienza. E francamente parlando, anche se quella che sto per raccontare non ne è la causa, capisco anche perché non si trovano più insegnanti, a queste condizioni non accetto nemmeno io di esserlo, porterò alla fine questa avventura e amen.

E' da settimane che mi confronto con altre persone che insegnano, come il mio amico che insegna alla Facoltà di Ingegneria alla Federico II, e altri docenti in Italia e qui, anche perché io ho sempre voglia di imparare da persone che si fanno il mazzo da secoli su queste cose e ne hanno da dirtene, ma stavolta sto imparando che non è cosa

Ieri la frase che mi ha gelato di più è stata

non esagerare che i ragazzi poi si annoiano

Chi mi conosce sa che io adoro insegnare, e chi mi ha seguito su @papero-learning sa che faccio sempre di tutto per rendere digeribili concetti che non sono alla portata quotidiana di tutti (se poi ci riesco è un altro paio di maniche, ma lo sforzo c'è), ma qua sta avvenendo un cambio di paradigma che, a mio parere, è molto pericoloso, e se questo cambio è dovuto ad un salto generazionale inevitabile, allora vuol dire che ci siamo scollati, e io non intendo contribuire a 'sta pagliacciata.

Io trovo inaccettabile che chi ha deciso volontariamente di iscriversi ad un corso universitario specializzante trovi "noiosa" la teoria. Sì, vero, ci sono dei prof di merda, come ci sono dei colleghi di merda, dei capi di merda, amen. Si può rendere qualsiasi contenuto interessante, ma non a scapito della conoscenza approfondita di un argomento che un corso deve fornire. Un concetto come il massimo comune denominatore può essere raccontato a mo' di Superquark, anzi, deve essere così per tutti coloro che non hanno scelto di fare dell'algebra la loro ragione di vita, ma chi ha deciso altrimenti si deve studiare tutte le cazzo di proprietà, e se un ragazzo di 20 anni ancora non ha compreso che quelle cose apparentemente fini a se stesse fanno parte di quei tanti piccoli mattoni che compongono l'impalcatura di una professione futura, beh, allora tanto vale che vada a rubare o che si faccia spiegare le cose da ChatGPT. E' un discorso da vecchio di merda? Sì, boh, non lo so, e anche se fosse me ne fotto.

Tutti questi ragionamenti me li sarei tenuti per me, o ci avrei scritto sopra molto più in là, ma (sarà che a volte si allineano i pianeti) il reblog di @kon-igi al post di @nusta stamattina ha dato fuoco a quella mia lunga coda di paglia formatasi in queste settimane di confronto con le persone di cui parlavo prima. Sì, i post parlavano d'altro, però boh, io ci ho visto alla radice una matrice che, sebbene io condivida in linee generali quello che ha scritto Kon, non accetto più quando quel tipo di discorso inizia ad infiltrarsi subdolamente in aree dove la velocità non è ammissibile e l'intensità per me è solo sinonimo di approfondimento. Ripeto ancora, il reblog era molto probabilmente inteso per altri contesti, ma io temo che ormai ci si stia arrendendo al fatto che o è tutta una tiktokata (=> romanticizzazione e spettacolarizzazione), anche la scienza, o non se ne fa più nulla.

La tizia della frase sopra in corsivo, prima di organizzare il nostro incontro, mi aveva scritto nell'email

due to the lack of programming skills we started learning programming Java and did only data structures like array list, linked lists and binary trees

Il suo corso è un corso del secondo anno di teoria dell'informazione, e scrivere due to the lack of programming skills è un fallimento su tutta la linea, e non ce l'ho con lei, perché con chi parli parli sembra che sia tutto così, e io mi trovo a dovermi fare carico di concetti avanzati (il mio corso è di programmazione avanzata) col problema che non capiranno un cazzo, perché, per non essere troppo noiosi, i miei colleghi hanno dovuto derogare la qualità dell'insegnamento a favore di, come vogliamo chiamarla, una gita al parco a scrivere un paio di if-then-else?

Tutto questo sfogo non è inteso per mettermi dalla parte della ragione, è solo uno sfogo per aiutarmi ad accettare il fatto che non appartengo più ad un mondo che è andato troppo avanti per me, e di adeguarmi sinceramente non ne ho voglia, soprattutto perché lo trovo deontologicamente parlando una bestemmia, lascio il posto a persone più capaci.

[princess-of-the-corner]

…you realize this means you need a one-shot where the magic translator breaks down, & everyone is speaking their home language, so they all sound like gibberish to each other? Cause, as I think you've said, none of these people are "human", why should their languages sound REMOTELY "human"? Musa sounds like she speaks in bird calls. Aisha sounds like dolphin chatter. Flora's language creaks like ancient trees. Tecna sounds like if binary code auto-tuned & went to Harvard.

Lmao I had to yeet this out and added a little angst I imagined this taking place in Season 1 so rip Aisha you're not here yet

-

"Good morning," Bloom yawned.

There was a returning cacophony from the common room that had her instantly awake.

"What the fuck?" Bloom asked, looking at the girls.

Musa said...... something. But instead of words there was just a sound of ringing bells where her voice should be.

Bloom only looked at her. Tilting her head.

Flora said something too. By her expression Bloom would guess it was a question. But there were no words. Just this unnerving creaking and snapping that reminded her of being nine and climbing a tree only to find the branch no longer held her weight.

Tecna had gotten up. Hands on Bloom's face and inspecting her mouth and throat. Wait. Was there something wrong with her? The other girl said something that may have been 'fascinating!', but was garbled under sounds of dial-up internet.

She then held up a hand, grabbing her phone. Swiftly typing at the keys

Helplessly, Bloom looked to Stella. Hoping for some miracle of communication. Thankfully the words out of her mouth were actual words and not strange vocalizations! Unfortunately they were not words she knew.

"Wait-" Stella said, finally in a recognizable word. "I do not- explain? Translate! Should have school attention."

"You.... should've paid more attention in school?" Bloom offered.

"Yes!" she nodded.

Almost immediately, her mood deflated. Holding her head in her hands and muttering things Bloom didn't know. Which was not at all helpful in explaining-

"Is this the right language setting?"

She jumped at the voice. Something incredibly robotic and matter-of-fact and not any of her friends' voices. After a moment of panicked looking around, she saw Tecna trying to get her attention.

"Is this the right language setting?" the sound asked again.

Hesitantly, Bloom nodded. This had Tecna grin, and begin typing on her phone again. Only then did she realize the robotic voice was some text-to-speech program.

"The universal translator spells are being updated," the robotic voice spoke for her. "It will be fixed in about an hour, but until then we have to rely on more manual translators."

Translator spells? What in the-

Oh. Right.

She hadn't thought about it. Just like she hadn't thought too much about the idea of other 'worlds'. They had their own languages too.

But the sounds.... entirely inhuman vocalizations. A reminder that they may look Human, but they weren't not really.

A hand wandered up to touch her ear. Now pointed and covered in blue scales. A reminder that she wasn't Human either.

[yanderecrazysie]

J.S Anon here again, you can probably tell what kind of Reader I want for this one. Anyways would I be able to request an NSFW one? Maybe Despair and Hope hating reader silently giving Chihiro a blowjob underneath the table and being walked in on if that's alright!

HI AGAIN! I had a lot of trouble working the Junko’s sister and hope/despair hate into this, but I think I got it! Also, he’s a little OOC so take that as you will.

As always, all characters are 18+.

Title: Take This Longing

Pairings: Chihiro Fujisaki x Reader

WARNINGS: yandere themes, NSFW, NON-CON ORAL (m. receiving)

“Oh take this longing from my tongue

Whatever useless things these hands have done

Let me see your beauty broken down

Like you would do

For one you love”

From “Take This Longing” by Leonard Cohen

You blankly watched the number on the elevator’s display screen change as each floor passed you by. The numbers blinked with the same red as the light on your ankle monitor. 

Not everyone could forgive an Enoshima, after all.

The elevator stopped near the top floor of the highrise and the doors opened, revealing an office bathed in the soft glow of a hundred monitors, lining the walls and desks. There were bookshelves haphazardly placed against the windows that made up the back wall, all half-way filled with technical manuals.

At the center of a ring of monitors was Chihiro Fujisaki, whose eyes flitted between displays with an intensity that didn’t match his sweet-looking exterior. As a member of the Future Foundation, Chihiro had grown taller over the years and had begun wearing pants instead of skirts (embracing his masculine side).

As he looked up at you, his heart skipped a beat. You, the sister of Junko Enoshima and Mukuro Ikusaba, yet a person that loathed both despair and hope, always brought a smile to his face.

He stood, smoothing out the front of his lab coat. You were punctual, as always, on the dot of the hour you were summoned. He admired that about you. He took a deep breath to steady himself.

“You wanted to see me?” your voice was deadpan as always.

“Yes, thank you for coming,” Chihiro gestured to a chair opposite his desk, “Please, take a seat.”

“I’d rather not,” you said simply, crossing your arms.

Chihiro nodded, swallowing thickly, “Alright, well… I’ve been working on something. A project for hope. Of course, you already knew that…”

You didn’t respond, just stood there blankly staring at him, waiting for him to continue.

“It’s an AI, one that can learn and evolve beyond the programming constraints of binary thinking. It’s designed to understand and feel, without falling into the traps that…” he swallowed again, not wanting to bring up the past that had led to you becoming an unwilling member of the Future Foundation, “...well, you know.”

“And you’re telling me this because…?” you sounded wary.

Chihiro’s fingers twitched nervously, “Because, you can help me test it. With your rejection of both hope and despair, we can make sure the AI can run without biases if needed.”

You shrugged, “I’m not allowed to turn down anything you guys ask, but what do you even get out of this?”

Chihiro’s heart hammered in his chest, “I… I admire you,” he confessed, his voice barely above a whisper, “Everything about you.”

You gave him a disgusted look, “I’m not interested in any of you hope-filled tree-huggers. Fuck off with that mushy-gushy shit.”

Chihiro’s heart shattered into a million pieces and tears filled his eyes. He felt a surge of anger, “Why can’t you just like hope? It’s such a good thing, how can you hate it?”

You shrugged again and turned away, “If that’s all, then I’ll take my leave.”

Chihiro suddenly had a thought. One that was awful, terrible, and so tempting.

“Suck me off,” he said, voice trembling. He couldn’t believe something so inappropriate had left his mouth. It had only ever done so in daydreams of the two of you together.

Where you were a willing participant.

You clearly couldn’t believe it either, “The hell’d you say?”

“Suck me off,” Chihiro demanded, voice stronger and clearer this time, “You can’t refuse a direct order from one of us, can you?”

“I’m- I’m not a sex toy!” you snapped, blood running to your cheeks. Despite your protest, you reluctantly got on your knees and crawled under his desk. He could hardly believe it when shaking hands unbuttoned and unzipped his pants, pulling his painfully hard cock out of his trousers.

It was bigger than you expected for such a delicate-looking man, and it was threatening-looking, with a pulsating vein down the side and pre beading at the tip. You hesitated for a moment, looking up at Chihiro’s face. He was staring down at you with a mix of desire and embarrassment, biting his lip as he watched you.

You took a deep breath and leaned forward, tentatively wrapping your lips around the head of his cock. It was warm and spongy, and very, very salty. You moved your head forward, taking as much of his impressively-sized member into your mouth as possible.

Chihiro let out a high-pitched moan as you started to move your head up and down, swirling your tongue around the tip of his cock. He grew harder and heavier in your mouth, his hips starting to thrust forward slightly as he lost himself in the sensation.

He thrust a little too hard and you gagged, pulling off the cock with a whine of pain. “Sorry, sweetheart,” he gasped, carding his hand through your hair, “I’ll be more careful- please keep going!”

You took him back into your mouth, sucking harder and beginning to bob your head up and down. Your hands reached up to cup his balls, gently massaging them as you continued to work his cock.

Chihiro let out a strangled moan as he felt the familiar tightness building in his groin. He couldn’t believe how good it felt. He felt like he’d died and gone to heaven, because having you on your knees for him, sucking his throbbing cock, was better than any fantasy he could have conjured up in that moment..

With one final thrust forward, he exploded into your mouth, cock pulsating as he filled it with his release. You swallowed it down, but the sheer volume of it spilled over onto your lips, leaving you looking more debauched than ever.

At that moment, the elevator doors opened, and Byakuya stepped into the room. “Fujisaki, I need those-” he stopped, absolutely horrified by the sight he was seeing.

Chihiro was sure he looked red-faced, with his spent cock hanging out of his pants and you, under his desk, white cum dripping down your chin.

“Disgusting,” Byakuya shuddered, shaking his head as he walked straight back into the elevator.

You looked borderline tearful until Chihiro placed his hand back in your hair, letting out a contented sigh, “You’re perfect, you know that?”

You stared at him blankly, as though you couldn’t believe what you had done, all emotion driven out of you.

Chihiro couldn’t wait until you did it again for him. 

Maybe next time, he’d make you go all the way.

[selfishdissatisfaction]

i installed a program

to put me together

heap dumps and milligrams

tattered and weathered

reflections of black and green

wishing not to be seen

rusted veins and a binary tree

green hills and make believe

there's blood on the tile again

[lady-of-imladris]

Omg hiiii I have an unhinged ask: what’s the funniest thing that you’ve ever done while drunk?

I have done A LOT of funny things while drunk!! My mother and I usually have bad ideas when we drink together but I can't think of anything specific rn

When I failed my programming class and had to retake it I got super drunk once before doing an assignment bc I was angry at myself for failing the first time and... Who would've thought that the secret to recursion is being drunk? I solved that fucker in 7 minutes. Binary tree implementation. Not using anything pre-built from Java.

[bitfreak]

Most Asked Coding Questions in Placements

Getting ready for placements? Whether you're aiming for a service-based firm or a top-tier product company, you must brush up on your coding fundamentals and problem-solving skills. 🚀

Here are the go-to topics recruiters always test:

Arrays & Strings – Duplicates, palindromes, reversing arrays, maximum subarray sum.

Linked Lists – Reversing a list, detecting cycles, merging two sorted lists.

Sorting & Searching – Implementing sorting algorithms, using binary search creatively.

Recursion & Backtracking – Generating permutations/combinations, solving Sudoku.

Dynamic Programming – Longest Common Subsequence, Knapsack, and similar problems.

Trees & Graphs – Tree/graph traversals, finding shortest paths, DFS/BFS.

Stacks & Queues – Valid parentheses, implementing queues using stacks, and vice versa.

✨ Want a full list of the top coding questions companies love to ask? Check out this solid guide: Most Asked Coding Questions in Placements - https://prepinsta.com/interview-preparation/technical-interview-questions/most-asked-coding-questions-in-placements/

Level up your prep and go ace that interview. 💪💻

[stentorai]

Predicting Employee Attrition: Leveraging AI for Workforce Stability

Employee turnover has become a pressing concern for organizations worldwide. The cost of losing valuable talent extends beyond recruitment expenses—it affects team morale, disrupts workflows, and can tarnish a company's reputation. In this dynamic landscape, Artificial Intelligence (AI) emerges as a transformative tool, offering predictive insights that enable proactive retention strategies. By harnessing AI, businesses can anticipate attrition risks and implement measures to foster a stable and engaged workforce.

Understanding Employee Attrition

Employee attrition refers to the gradual loss of employees over time, whether through resignations, retirements, or other forms of departure. While some level of turnover is natural, high attrition rates can signal underlying issues within an organization. Common causes include lack of career advancement opportunities, inadequate compensation, poor management, and cultural misalignment. The repercussions are significant—ranging from increased recruitment costs to diminished employee morale and productivity.

The Role of AI in Predicting Attrition

AI revolutionizes the way organizations approach employee retention. Traditional methods often rely on reactive measures, addressing turnover after it occurs. In contrast, AI enables a proactive stance by analyzing vast datasets to identify patterns and predict potential departures. Machine learning algorithms can assess factors such as job satisfaction, performance metrics, and engagement levels to forecast attrition risks. This predictive capability empowers HR professionals to intervene early, tailoring strategies to retain at-risk employees.

Data Collection and Integration

The efficacy of AI in predicting attrition hinges on the quality and comprehensiveness of data. Key data sources include:

Employee Demographics: Age, tenure, education, and role.

Performance Metrics: Appraisals, productivity levels, and goal attainment.

Engagement Surveys: Feedback on job satisfaction and organizational culture.

Compensation Details: Salary, bonuses, and benefits.

Exit Interviews: Insights into reasons for departure.

Integrating data from disparate systems poses challenges, necessitating robust data management practices. Ensuring data accuracy, consistency, and privacy is paramount to building reliable predictive models.

Machine Learning Models for Attrition Prediction

Several machine learning algorithms have proven effective in forecasting employee turnover:

Random Forest: This ensemble learning method constructs multiple decision trees to improve predictive accuracy and control overfitting.

Neural Networks: Mimicking the human brain's structure, neural networks can model complex relationships between variables, capturing subtle patterns in employee behavior.

Logistic Regression: A statistical model that estimates the probability of a binary outcome, such as staying or leaving.

For instance, IBM's Predictive Attrition Program utilizes AI to analyze employee data, achieving a reported accuracy of 95% in identifying individuals at risk of leaving. This enables targeted interventions, such as personalized career development plans, to enhance retention.

Sentiment Analysis and Employee Feedback

Understanding employee sentiment is crucial for retention. AI-powered sentiment analysis leverages Natural Language Processing (NLP) to interpret unstructured data from sources like emails, surveys, and social media. By detecting emotions and opinions, organizations can gauge employee morale and identify areas of concern. Real-time sentiment monitoring allows for swift responses to emerging issues, fostering a responsive and supportive work environment.

Personalized Retention Strategies

AI facilitates the development of tailored retention strategies by analyzing individual employee data. For example, if an employee exhibits signs of disengagement, AI can recommend specific interventions—such as mentorship programs, skill development opportunities, or workload adjustments. Personalization ensures that retention efforts resonate with employees' unique needs and aspirations, enhancing their effectiveness.

Enhancing Employee Engagement Through AI

Beyond predicting attrition, AI contributes to employee engagement by:

Recognition Systems: Automating the acknowledgment of achievements to boost morale.

Career Pathing: Suggesting personalized growth trajectories aligned with employees' skills and goals.

Feedback Mechanisms: Providing platforms for continuous feedback, fostering a culture of open communication.

These AI-driven initiatives create a more engaging and fulfilling work environment, reducing the likelihood of turnover.

Ethical Considerations in AI Implementation

While AI offers substantial benefits, ethical considerations must guide its implementation:

Data Privacy: Organizations must safeguard employee data, ensuring compliance with privacy regulations.

Bias Mitigation: AI models should be regularly audited to prevent and correct biases that may arise from historical data.

Transparency: Clear communication about how AI is used in HR processes builds trust among employees.

Addressing these ethical aspects is essential to responsibly leveraging AI in workforce management.

Future Trends in AI and Employee Retention

The integration of AI in HR is poised to evolve further, with emerging trends including:

Predictive Career Development: AI will increasingly assist in mapping out employees' career paths, aligning organizational needs with individual aspirations.

Real-Time Engagement Analytics: Continuous monitoring of engagement levels will enable immediate interventions.

AI-Driven Organizational Culture Analysis: Understanding and shaping company culture through AI insights will become more prevalent.

These advancements will further empower organizations to maintain a stable and motivated workforce.

Conclusion

AI stands as a powerful ally in the quest for workforce stability. By predicting attrition risks and informing personalized retention strategies, AI enables organizations to proactively address turnover challenges. Embracing AI-driven approaches not only enhances employee satisfaction but also fortifies the organization's overall performance and resilience.

Frequently Asked Questions (FAQs)

How accurate are AI models in predicting employee attrition?

AI models, when trained on comprehensive and high-quality data, can achieve high accuracy levels. For instance, IBM's Predictive Attrition Program reports a 95% accuracy rate in identifying at-risk employees.

What types of data are most useful for AI-driven attrition prediction?

Valuable data includes employee demographics, performance metrics, engagement survey results, compensation details, and feedback from exit interviews.

Can small businesses benefit from AI in HR?

Absolutely. While implementation may vary in scale, small businesses can leverage AI tools to gain insights into employee satisfaction and predict potential turnover, enabling timely interventions.

How does AI help in creating personalized retention strategies?

AI analyzes individual employee data to identify specific needs and preferences, allowing HR to tailor interventions such as customized career development plans or targeted engagement initiatives.

What are the ethical considerations when using AI in HR?

Key considerations include ensuring data privacy, mitigating biases in AI models, and maintaining transparency with employees about how their data is used.

For more Info Visit :- Stentor.ai

[simerjeet]

Mastering Data Structures: A Comprehensive Course for Beginners

Data structures are one of the foundational concepts in computer science and software development. Mastering data structures is essential for anyone looking to pursue a career in programming, software engineering, or computer science. This article will explore the importance of a Data Structure Course, what it covers, and how it can help you excel in coding challenges and interviews.

1. What Is a Data Structure Course?

A Data Structure Course teaches students about the various ways data can be organized, stored, and manipulated efficiently. These structures are crucial for solving complex problems and optimizing the performance of applications. The course generally covers theoretical concepts along with practical applications using programming languages like C++, Java, or Python.

By the end of the course, students will gain proficiency in selecting the right data structure for different problem types, improving their problem-solving abilities.

2. Why Take a Data Structure Course?

Learning data structures is vital for both beginners and experienced developers. Here are some key reasons to enroll in a Data Structure Course:

a) Essential for Coding Interviews

Companies like Google, Amazon, and Facebook focus heavily on data structures in their coding interviews. A solid understanding of data structures is essential to pass these interviews successfully. Employers assess your problem-solving skills, and your knowledge of data structures can set you apart from other candidates.

b) Improves Problem-Solving Skills

With the right data structure knowledge, you can solve real-world problems more efficiently. A well-designed data structure leads to faster algorithms, which is critical when handling large datasets or working on performance-sensitive applications.

c) Boosts Programming Competency

A good grasp of data structures makes coding more intuitive. Whether you are developing an app, building a website, or working on software tools, understanding how to work with different data structures will help you write clean and efficient code.

3. Key Topics Covered in a Data Structure Course

A Data Structure Course typically spans a range of topics designed to teach students how to use and implement different structures. Below are some key topics you will encounter:

a) Arrays and Linked Lists

Arrays are one of the most basic data structures. A Data Structure Course will teach you how to use arrays for storing and accessing data in contiguous memory locations. Linked lists, on the other hand, involve nodes that hold data and pointers to the next node. Students will learn the differences, advantages, and disadvantages of both structures.

b) Stacks and Queues

Stacks and queues are fundamental data structures used to store and retrieve data in a specific order. A Data Structure Course will cover the LIFO (Last In, First Out) principle for stacks and FIFO (First In, First Out) for queues, explaining their use in various algorithms and applications like web browsers and task scheduling.

c) Trees and Graphs

Trees and graphs are hierarchical structures used in organizing data. A Data Structure Course teaches how trees, such as binary trees, binary search trees (BST), and AVL trees, are used in organizing hierarchical data. Graphs are important for representing relationships between entities, such as in social networks, and are used in algorithms like Dijkstra's and BFS/DFS.

d) Hashing

Hashing is a technique used to convert a given key into an index in an array. A Data Structure Course will cover hash tables, hash maps, and collision resolution techniques, which are crucial for fast data retrieval and manipulation.

e) Sorting and Searching Algorithms

Sorting and searching are essential operations for working with data. A Data Structure Course provides a detailed study of algorithms like quicksort, merge sort, and binary search. Understanding these algorithms and how they interact with data structures can help you optimize solutions to various problems.

4. Practical Benefits of Enrolling in a Data Structure Course

a) Hands-on Experience

A Data Structure Course typically includes plenty of coding exercises, allowing students to implement data structures and algorithms from scratch. This hands-on experience is invaluable when applying concepts to real-world problems.

b) Critical Thinking and Efficiency

Data structures are all about optimizing efficiency. By learning the most effective ways to store and manipulate data, students improve their critical thinking skills, which are essential in programming. Selecting the right data structure for a problem can drastically reduce time and space complexity.

c) Better Understanding of Memory Management

Understanding how data is stored and accessed in memory is crucial for writing efficient code. A Data Structure Course will help you gain insights into memory management, pointers, and references, which are important concepts, especially in languages like C and C++.

5. Best Programming Languages for Data Structure Courses

While many programming languages can be used to teach data structures, some are particularly well-suited due to their memory management capabilities and ease of implementation. Some popular programming languages used in Data Structure Courses include:

C++: Offers low-level memory management and is perfect for teaching data structures.

Java: Widely used for teaching object-oriented principles and offers a rich set of libraries for implementing data structures.

Python: Known for its simplicity and ease of use, Python is great for beginners, though it may not offer the same level of control over memory as C++.

6. How to Choose the Right Data Structure Course?

Selecting the right Data Structure Course depends on several factors such as your learning goals, background, and preferred learning style. Consider the following when choosing:

a) Course Content and Curriculum

Make sure the course covers the topics you are interested in and aligns with your learning objectives. A comprehensive Data Structure Course should provide a balance between theory and practical coding exercises.

b) Instructor Expertise

Look for courses taught by experienced instructors who have a solid background in computer science and software development.

c) Course Reviews and Ratings

Reviews and ratings from other students can provide valuable insights into the course’s quality and how well it prepares you for real-world applications.

7. Conclusion: Unlock Your Coding Potential with a Data Structure Course

In conclusion, a Data Structure Course is an essential investment for anyone serious about pursuing a career in software development or computer science. It equips you with the tools and skills to optimize your code, solve problems more efficiently, and excel in technical interviews. Whether you're a beginner or looking to strengthen your existing knowledge, a well-structured course can help you unlock your full coding potential.

By mastering data structures, you are not only preparing for interviews but also becoming a better programmer who can tackle complex challenges with ease.

[lorelei-system]

Hey everyone. We are a traumagenic system of who knows how many, not sure whether DID or OSDD. Medically recognized but currently not in therapy. They/them collectively preferred. Body is female and 30.

We are syscourse neutral (some alters have differing opinions) and will keep those topics off this blog. Will post about our experiences as a system, and reblog relatable system posts mainly. We try to sign off with names.

Side blogs:

lorelei-pics (nature photography by Nat, Riley, and Moss)

dannylovesart (art reblogs by danny)

Currently fronting: Lucy (she/her)

Alters relevant to this blog:

Poppy:

- age: 15

- pronouns: she/ her or it/its

- system host

- favorite color: black

- possible BPD/ depression symptom holder

- host of the grief subsystem

- link to subsystem post

- tags: #poppy speaks #poppy reblogs

Nini:

- age: 3-4

- pronouns: she/her

- loves plushies

- trauma holder

- tags: #nini #nini reblob #nini’s art

Phoebe:

- age: 12 (teen)

- pronouns: she/her

- nickname: Bee

- likes pastel colors

- likes/ wants to go into psychology

- acts older than she is (very mature and responsible for her age)

- tags: #phoebe speaks #phoebe reblogs

Ace:

- age: 18

- pronouns: they/ them (preferred) or he/him

- agender and asexual

- caring and sweet

- likes languages, crochet, video games, and puzzles

- tags: #ace speaks

Nick:

- age: 15

- pronouns: he/him (trans masc)

- likes watching Criminal Minds

- tags: #nick speaks

Ruby:

- age: 20

- pronouns: she/her, but any are fine

- impulsive and fun-loving

- I love cooking, listening to music and getting stuff done

- the “productivity alter”

- mood booster?

- tags: #ruby speaks

Lucy:

- age: 26

- pronouns: she/her

- reckless and careless

- into some messed-up stuff

- probably a persecutor in the self-destructive way

Moss:

- Age: 3-7

- Pronouns: they/bug (non-binary)

- loves nature

- currently obsessed with trees, specifically evergreens, more specifically pine trees

- also loves stim toys; possible autism/ ADHD symptom holder (we’re not formally diagnosed with either, hence the “possible”)

- has green hair, brown eyes, insect wings and antennae (in innerworld obviously)

Max:

- age: 20 something

- pronouns: he/him

- straight trans guy

- likes birds

Lisa:

- pronouns: she/her

- lesbian

- loves writing (mostly original fiction)

- tags: #lisa speaks

Riley:

- pronouns: she/her

- teenager (16-18?)

- self-proclaimed rebel

- I love everything black

- love spooky season and rain

- I enjoy rock music and am currently getting into programming

- tags: #riley speaks

Danny:

- pronouns: he/him

- teen

- into art (+ history) and music (+ history)

- loves looking at art, and making art

- has to relearn so back to being a beginner artist (but that’s okay)

- tags: #danny’s tag #art

[fauxfickle]

"Pizza parlor robots perform musical magic"

Detroit Free Press, Friday, Jan 21, 1983 (By Gary Graft)

Barbra Stringband has the Streisand schtick down pat. She’s got the narrow, mascaraed eyes and a wealth of nose. Okay, you do have to ignore her 280 pound frame.

But she is a real fox — in the fur, pointed ear sense of the word. And most nights she belts out the theme song from “Main Event” while a few seven and eight-year-olds do their version of slam dancing in the aisles.

Her band? A crocodile playing piano, a lion on drums and a walrus on saxophone.

And when Barbra and gang take a rest, the crowd is entertained alternatively by a pair of singing bears and a quartet of instruments equipped with arms, legs and faces so they can play themselves.

That motley crew makes up the house entertainment at Major Magic’s All-Star Pizza Revue. Two of the eateries are open now, with a total of five due to be operating by June. The idea is to offer anything the average family could want on a night out, including lots of diversions for the kids. But even though the pizza isn’t bad and the video arcade is kept up to date, the real attraction at Major Magics is the robots.

“I think this is significant,” says Bob Sapp, an independent programmer who helped design the Major Magics project.

“We’ve tried to literally imitate human movement; you can’t appreciate how complex human movement — something as simple as trying to bend an elbow — is until you’ve programmed into a character,” he says. “We want them to sweat, to cry, to move across the stage.”

“I don’t say that this is the best it’s going to be, but it’s the best around”

Major Magic’s president and found is Grosse Pointer Bob Rashid, 31.

The inspiration for it all came from Major Magic’s major competitor: Chuck E. Cheese’s. Rashid visited one in 1979 in San Jose, and though Rashid liked the concept, he wasn’t totally enthralled with the way it was working.

So Rashid hooked up with Ken Acton, president of Los Angeles-based Acton Animation, who had been with robots and animatronics and subsequently with Sapp.

“We’re head to head with Disney,” says Sapp, who now helps program the robots here. “They’re not doing anything new with their characters. We want ours to really progress; we intend to make it as elaborately lifelike as possible. We look forward to the day Disney looks at our characters with fright.” With good reason — Sapp pirated three Disney technicians to develop new technology for him.

The 11 characters included in the Major Magic’s floor show are not something you’d like to have dropped on you. Made of clay, fiberglass, plastic, latex skin and individually implanted strands of hair, a character like Burly, a giant grizzly bear complete with tree stump, weighs about 500 pounds.

The Binary Toning Coding System — the computer which controls the robots — is named Carl after it’s founder, Carl Jacobson. Inside the computer room behind the Major Magic’s stage, more than 8,500 miles of wire snake between the characters and the system.

The basic operation works like this; each motion, from an eye blink to a head nod is programmed on a computer disc, then switched to tapes and then into a microprocessor, which feeds the information through the computer and triggers electronic and hydraulic equipment inside the characters, making motion.

“I freaked out when I came up here the first day,” says Dean Natsuti, a technician.

Sapp and Dennis Tonich [sic], the entertainment directors at Major Magic’s and former drummer for the MC5 rock band, don’t deny that it’s a complicated process. They first spend several weeks of after-business-hours work programming the characters and adding their own personal touches to the show. Tonich programmed the drum-playing lion himself and [poured?] through hundreds of Beatles, Streisand and other pop music albums to come up with appropriate music, while Sapp put his voice on tape as Singin’ Sam, a sidekick to Burly the bear.

And, as far as they’re concerned, there’s no need for too many people to understand exactly what they’re doing; the idea is to entertain and not necessarily provide a complete robotics education.

“The kids just love it,” Tonich says. “It’s a fantasy made real for them.”

“My every robotics fantasy has been fulfilled now,” Sapp adds “They’re here and they’re performing; there’s a personal relationship between the robotics and the audience that hasn’t been done before this.”

“It has allowed us to spend money on the technology,” Sapp says “Come back a year from now and you’ll find that we got rid of all but maybe two tracks of music. They’ll really be playing their instruments, performing for people.”

The innovation has paid off for Rashid, annual sales projections for the locations — which he says cost $850,000 to build — are $1.6 million based on the first eight months of operation.

But despite the success, both Sapp and Tonich add they don’t feel there’s a danger of their robots replacing live human entertainment.

“‘Move over humans’ — that’s a long way off,” Tonich says. “I think the public gets a bias against robots, a fear of temporary job replacement. That’s not what we’re after.”

***

I was reading this FB post on Major Magic and thought I'd might transcribe for you guys since it was a bit blurry and hard to read. As a funny sidenote, the drummer for MC5 isn't named "Tonich", it's Thompson. Not sure how they spelled the harder last name.

All photos sourced from the MM archive on IG

[lonelydipshit]

What if I start a side blog called assembly official, and pretend to be a low level programming language that exists solely for the sake of making CS students cry?

Can you tell I just did my binary bomb lab? I wanna cry, what kind of sadistic fuck decided to put a fucking binary search tree in assembly, and the only indicator was that “hey this function looks kind of like dfs” ????

[hackeocafe]

Data Structure and Algorithms in JAVA | Full Course on Data Structure

In this course, we are going to discuss Data Structures and Algorithms using Java Programming. The data structure is a way to store and organize data so that it can be used efficiently. It is a set of concepts that we can use in any programming language to structure the data in the memory. Data structures are widely used in almost every aspect of computer science i.e. operating systems, computer science, compiler design, Artificial Intelligence, graphic,s and many more. Some examples of Data structures that we are going to cover in this course are arrays, linked lists, stack, queue, Binary Tree, Binary Search Tree, Graphs, etc. Apart from knowing these data structures, it's also important to understand the algorithmic analysis of a given code. Different Sorting and searching techniques will be talked about with their implementation in java programming. Lastly, this course contains information on the Greedy approach, Dynamic approach, and divide and Conquer approach to programming.