problem solving & program design in c

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Problem solving and program design in C

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Design Thinking and Innovation

Key concepts, who will benefit, aspiring or current innovation managers, entrepreneurs, product managers, developers, and marketers.

What You Earn

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Content Week - Clarify: Empathy and Understanding

• An Introduction to Innovation
• Clarify Through Observation
• Insights and Problem Framing
• The Right Enviroment for Creativity

Featured Exercises

Project week – clarify.

• Project Instructions

Content Week - Ideate, Part 1: Tools for Generating Ideas

• Establishing Focus with Design Principles
• The Ideation Process: Getting Started with SIT
• More SIT Tools for Ideation
• Open-Ended Approaches to Generating Ideas
• Review of Project Work

Content Week - Ideate, Part 2: User Values and Behaviors

• Design Heuristics for Generating and Refining Ideas
• Designing for Behavior Change

Project Week - Ideate

Content Week - Develop: An Experimentation Mindset

• Idea Selection and Evaluation
• Defining and Refining Your Prototype Plan
• Prototyping: From Exploration to Validation
• Leading Concept Development

Content Week - Implement: Communication and Structure

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Srikant Datar Design Thinking and Innovation

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You can think of the beta version of the Design Thinking and Innovation AI Course Assistant chat bot in two ways: like a virtual Teaching Assistant who can help you consolidate and confirm your understanding of course concepts, and as a virtual Learner Success Assistant who can help you stay on track with completing the coursework in a timely fashion. When you are finding a particular concept difficult to master, or would like additional examples of a theory, try asking the bot your question in the same way you would phrase it to a human TA. If you have a question pertaining to where or how to submit certain assignments, or one relating to deadlines or time estimates, you can also express those in a similar fashion. Please note that no preexisting familiarity or experience with generative AI is necessary or assumed to use the bot and, while we encourage you to engage with the bot and share your candid feedback on your experience, a lack of engagement with the bot will not adversely impact your eligibility for a certificate of completion.

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Participants in Design Thinking and Innovation are eligible for a Certificate of Completion from Harvard Business School Online.

Participants are expected to fully complete all coursework in a thoughtful and timely manner. This will mean meeting each week’s course module deadlines and fully answering questions posed therein. This helps ensure participants proceed through the course at a similar pace and can take full advantage of social learning opportunities. In addition to module and assignment completion, we expect you to offer feedback on others’ reflections and contribute to conversations on the platform. Participants who fail to complete the course requirements will not receive a certificate and will not be eligible to retake the course.

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Description: Design Thinking and Innovation is a 7-week, 40-hour online certificate program from Harvard Business School. Design Thinking and Innovation will teach you how to leverage fundamental design thinking principles and innovative problem-solving tools to address business challenges and build products, strategies, teams, and environments for optimal use and performance.

The program was developed by leading Harvard Business School faculty and is delivered in an active learning environment based on the HBS signature case-based learning model.

What is the project?

Beginning in Module 2 of Design Thinking and Innovation, you will apply the tools you learn in the course to an innovation problem that is important or interesting to you, or you can use a provided scenario. In subsequent modules, you will use your earlier responses to build on your innovation project and make each phase of design thinking relevant to your own work.

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• Data Structures
• Linked List
• Binary Tree
• Binary Search Tree
• Segment Tree
• Disjoint Set Union
• Fenwick Tree
• Red-Black Tree
• Advanced Data Structures
• Tree Data Structure
• Data Structures | Binary Trees | Question 3
• Data Structures | Binary Trees | Question 4
• Data Structures | Binary Trees | Question 1
• Data Structures | Binary Trees | Question 9
• Data Structures | Binary Trees | Question 12
• Data Structures | Binary Trees | Question 14
• Data Structures | Binary Trees | Question 11
• Data Structures | Binary Trees | Question 13
• Data Structures | Binary Trees | Question 15
• Tango Tree Data Structure
• Applications of tree data structure
• Data Structures | Binary Search Trees | Question 7
• Data Structures | Binary Search Trees | Question 8
• Data Structures | Binary Search Trees | Question 5
• Data Structures | Binary Search Trees | Question 6
• Data Structures | Binary Search Trees | Question 2

Binary Tree Data Structure

A Binary Tree Data Structure is a hierarchical data structure in which each node has at most two children, referred to as the left child and the right child. It is commonly used in computer science for efficient storage and retrieval of data, with various operations such as insertion, deletion, and traversal.

Introduction:

• Introduction to Binary Tree – Data Structure and Algorithm Tutorials
• Properties of Binary Tree
• Types of Binary Tree
• Applications, Advantages and Disadvantages of Binary Tree
• Binary Tree (Array implementation)
• Complete Binary Tree
• Perfect Binary Tree

Basic Operations on Binary Tree:

• Tree Traversals (Inorder, Preorder and Postorder)
• Level Order Tree Traversal
• Find the Maximum Depth or Height of given Binary Tree
• Insertion in a Binary Tree
• Deletion in a Binary Tree
• Enumeration of Binary Trees

Some other important Binary Tree Traversals :

• Level order traversal in spiral form
• Reverse Level Order Traversal
• BFS vs DFS for Binary Tree
• Inorder Tree Traversal without Recursion
• Morris traversal for Preorder
• Iterative Preorder Traversal
• Iterative Postorder Traversal Using Two Stacks
• Diagonal Traversal of Binary Tree
• Boundary Traversal of binary tree

Easy Problems on Binary Tree Data Structure:

• Calculate depth of a full Binary tree from Preorder
• Construct a tree from Inorder and Level order traversals
• Check if a given Binary Tree is SumTree
• Check if two nodes are cousins in a Binary Tree
• Check if removing an edge can divide a Binary Tree in two halves
• Check whether a given binary tree is perfect or not
• Check if a Binary Tree contains duplicate subtrees of size 2 or more
• Check if two trees are Mirror
• Foldable Binary Trees
• Symmetric Tree (Mirror Image of itself)
• Write Code to Determine if Two Trees are Identical
• Subtree with given sum in a Binary Tree
• Succinct Encoding of Binary Tree
• Write a program to Calculate Size of a tree
• Diameter of a Binary Tree
• Get Level of a node in a Binary Tree

Medium Problems on Binary Tree Data Structure:

• Find all possible binary trees with given Inorder Traversal
• Populate Inorder Successor for all nodes
• Construct Complete Binary Tree from its Linked List Representation
• Minimum swap required to convert binary tree to binary search tree
• Convert a given Binary Tree to Doubly Linked List | Set 1
• Convert a tree to forest of even nodes
• Flip Binary Tree
• Print root to leaf paths without using recursion
• Check if given Preorder, Inorder and Postorder traversals are of same tree
• Check whether a given Binary Tree is Complete or not | Set 1 (Iterative Solution)
• Check if a binary tree is subtree of another binary tree | Set 2
• Find largest subtree sum in a tree
• Maximum sum of nodes in Binary tree such that no two are adjacent
• Lowest Common Ancestor in a Binary Tree | Set 1
• Height of a generic tree from parent array
• Find distance between two given keys of a Binary Tree

Hard Problems on Binary Tree Data Structure:

• Modify a binary tree to get Preorder traversal using right pointers only
• Construct Full Binary Tree using its Preorder traversal and Preorder traversal of its mirror tree
• Construct a special tree from given preorder traversal
• Construct tree from ancestor matrix
• Construct the full k-ary tree from its preorder traversal
• Construct Binary Tree from String with bracket representation
• Convert a Binary Tree into Doubly Linked List in spiral fashion
• Convert a Binary Tree to a Circular Doubly Link List
• Convert Ternary Expression to a Binary Tree
• Check if there is a root to leaf path with given sequence
• Remove all nodes which don’t lie in any path with sum>= k
• Maximum spiral sum in Binary Tree
• Sum of nodes at k-th level in a tree represented as string
• Sum of all the numbers that are formed from root to leaf paths
• Merge Two Binary Trees by doing Node Sum (Recursive and Iterative)
• Find root of the tree where children id sum for every node is given

Quick Links :

• ‘Practice Problems’ on Trees
• ‘Quizzes’ on Binary Trees
• ‘Videos’ on Trees

Recommended:

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"It's showed us how engineers go through the process of solving problems."

In the second, third, and fourth years of UPEI's Bachelor of Sustainable Design Engineering program, students form small groups to participate in a year-long design and implementation project with a corporate or community partner. Described as "an opportunity for students to act as engineering consultants for a company or organization, where teams of students team solve an actual technical challenge from the partner's operation", the design clinic program is a truly hands-on, real-world learning experience.

Student team members Remi Antoun, James Campbell, Chukwuma "Prince" Ezeilo, and Huy "Alvin" Nguyen worked with the Abegweit First Nation to solve the ongoing challenge of transforming wind-damaged forests into productive blueberry crops while safeguarding the suitability of the land for wild blueberry cultivation. Current methods and machinery for commercial tree removal are prohibitively expensive and pose a risk to the land’s suitability for blueberry propagation. 

To address this challenge, the team designed and developed a manual braking and cable car-like pulley mechanism to safely and effectively move fallen trees as an affordable and sustainable solution that preserves the cultural and environmental values of the community.   

Before showcasing their project at the 2024 Engineering Student Design Expo in April, the team reflected on their experience.

How did you choose Sustainable Design Engineering at UPEI?

"I'm originally from Vietnam, and after I graduated from high school I went to UPEI's Open House for prospective students and saw a lot of cool stuff in the Engineering program," says Alvin. "When I learned that first-year students actually work with community and industry partners as clients right from the start, that's the main reason I chose this program at UPEI."

"My older sister and cousin are Engineering students here at UPEI and I thought it would be interesting and great for me, too," says Remi.

"I'm from Nigeria, and I chose UPEI because I loved their Engineering program, and the sustainable design aspect was something I was looking for," says Prince.

"I live on Prince Edward Island, and nine generations of my family have lived here," says James. "I live on a rural family farm which I want to try to automate and improve. I joined the Engineering program here as an adult to try and learn how to do that."

What kinds of challenges did you face during the project, and what did you particularly enjoy about the work?

"Halfway through the first semester we received the project and the problem to solve," says James. "So for that semester we wrote reports of our planning. We spent the second semester building and testing. Being able to use the Sustainable Design Engineering facility and the resources and tools here is awesome, and the access to the shop materials and working spaces is key to the success of our project. The design spiral is very important to us, the trying and failing and trying again and failing again is key."

"For me, the main challenge was designing and building the device," says Remi. "Figuring out lengths of materials, and the distances and forces required to accurately design the braking mechanism took a lot of testing, a lot of trial and error. My favourite part is at the end, when we're done, and we can start painting, and assembling everything. That's when we find out our devices work and that we've got it right."

"My favourite part of the project was the second week of the second semester when we get to go and test the prototype we constructed out of wood," says Alvin. "It really helped us see how components would fit together and how our design might work when completed."

"It was a challenge but getting the brakes to work manually," says Prince. "That's the part that makes this design and concept different from a normal cable car system. We could have designed it on a computer but until we had something real in front of us that experience helped us learn a lot."   

What impacts has your involvement in this project had for you?

"I've learned CAD, and other technical skills since my first year but more about being confident, presenting to people and giving presentations," says Alvin. "These skills will be very useful for me in the future when I go to work."

"It's showed me how engineers go through the process of solving problems," says Remi. "I'm looking forward to finding work this summer as an intern, or with a company to build on what I've learned."

"Working with a community partner has helped me learn a lot," says Prince. "It's made me want to continue to build on my skills, think outside the box more to solve problems, and things like that."

"I'm hoping to copy this design, improve on it, and utilize it on my farm for loading my sawmill," says James. "Using the design spiral was really important—try something, fail, try something else, fail."

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What is decision making?

Decisions, decisions. When was the last time you struggled with a choice? Maybe it was this morning, when you decided to hit the snooze button—again. Perhaps it was at a restaurant, with a miles-long menu and the server standing over you. Or maybe it was when you left your closet in a shambles after trying on seven different outfits before a big presentation. Often, making a decision—even a seemingly simple one—can be difficult. And people will go to great lengths—and pay serious sums of money—to avoid having to make a choice. The expensive tasting menu at the restaurant, for example. Or limiting your closet choices to black turtlenecks, à la Steve Jobs.

Get to know and directly engage with senior McKinsey experts on decision making

Aaron De Smet is a senior partner in McKinsey’s New Jersey office, Eileen Kelly Rinaudo  is McKinsey’s global director of advancing women executives and is based in the New York office, Frithjof Lund is a senior partner in the Oslo office, and Leigh Weiss is a senior adviser in the Boston office.

If you’ve ever wrestled with a decision at work, you’re definitely not alone. According to McKinsey research, executives spend a significant portion of their time— nearly 40 percent , on average—making decisions. Worse, they believe most of that time is poorly used. People struggle with decisions so much so that we actually get exhausted from having to decide too much, a phenomenon called decision fatigue.

But decision fatigue isn’t the only cost of ineffective decision making. According to a McKinsey survey of more than 1,200 global business leaders, inefficient decision making costs a typical Fortune 500 company 530,000 days  of managers’ time each year, equivalent to about $250 million in annual wages. That’s a lot of turtlenecks.

How can business leaders ease the burden of decision making and put this time and money to better use? Read on to learn the ins and outs of smart decision making—and how to put it to work.

Learn more about our People & Organizational Performance Practice .

How can organizations untangle ineffective decision-making processes?

McKinsey research has shown that agile is the ultimate solution for many organizations looking to streamline their decision making . Agile organizations are more likely to put decision making in the right hands, are faster at reacting to (or anticipating) shifts in the business environment, and often attract top talent who prefer working at companies with greater empowerment and fewer layers of management.

For organizations looking to become more agile, it’s possible to quickly boost decision-making efficiency by categorizing the type of decision to be made and adjusting the approach accordingly. In the next section, we review three types of decision making and how to optimize the process for each.

What are three keys to faster, better decisions?

Business leaders today have access to more sophisticated data than ever before. But it hasn’t necessarily made decision making any easier. For one thing, organizational dynamics—such as unclear roles, overreliance on consensus, and death by committee—can get in the way of straightforward decision making. And more data often means more decisions to be taken, which can become too much for one person, team, or department. This can make it more difficult for leaders to cleanly delegate, which in turn can lead to a decline in productivity.

Leaders are growing increasingly frustrated with broken decision-making processes, slow deliberations, and uneven decision-making outcomes. Fewer than half  of the 1,200 respondents of a McKinsey survey report that decisions are timely, and 61 percent say that at least half the time they spend making decisions is ineffective.

What’s the solution? According to McKinsey research, effective solutions center around categorizing decision types and organizing different processes to support each type. Further, each decision category should be assigned its own practice—stimulating debate, for example, or empowering employees—to yield improvements in effectiveness.

Here are the three decision categories  that matter most to senior leaders, and the standout practice that makes the biggest difference for each type of decision.

• Big-bet decisions are infrequent but high risk, such as acquisitions. These decisions carry the potential to shape the future of the company, and as a result are generally made by top leaders and the board. Spurring productive debate by assigning someone to argue the case for and against a potential decision can improve big-bet decision making.
• Cross-cutting decisions, such as pricing, can be frequent and high risk. These are usually made by business unit heads, in cross-functional forums as part of a collaborative process. These types of decisions can be improved by doubling down on process refinement. The ideal process should be one that helps clarify objectives, measures, and targets.
• Delegated decisions are frequent but low risk and are handled by an individual or working team with some input from others. Delegated decision making can be improved by ensuring that the responsibility for the decision is firmly in the hands of those closest to the work. This approach also enhances engagement and accountability.

In addition, business leaders can take the following four actions to help sustain rapid decision making :

• Focus on the game-changing decisions, ones that will help an organization create value and serve its purpose.
• Convene only necessary meetings, and eliminate lengthy reports. Turn unnecessary meetings into emails, and watch productivity bloom. For necessary meetings, provide short, well-prepared prereads to aid in decision making.
• Clarify the roles of decision makers and other voices. Who has a vote, and who has a voice?
• Push decision-making authority to the front line—and tolerate mistakes.

Introducing McKinsey Explainers : Direct answers to complex questions

How can business leaders effectively delegate decision making.

Business is more complex and dynamic than ever, meaning business leaders are faced with needing to make more decisions in less time. Decision making takes up an inordinate amount of management’s time—up to 70 percent for some executives—which leads to inefficiencies and opportunity costs.

As discussed above, organizations should treat different types of decisions differently . Decisions should be classified  according to their frequency, risk, and importance. Delegated decisions are the most mysterious for many organizations: they are the most frequent, and yet the least understood. Only about a quarter of survey respondents  report that their organizations make high-quality and speedy delegated decisions. And yet delegated decisions, because they happen so often, can have a big impact on organizational culture.

The key to better delegated decisions is to empower employees by giving them the authority and confidence to act. That means not simply telling employees which decisions they can or can’t make; it means giving employees the tools they need to make high-quality decisions and the right level of guidance as they do so.

Here’s how to support delegation and employee empowerment:

• Ensure that your organization has a well-defined, universally understood strategy. When the strategic intent of an organization is clear, empowerment is much easier because it allows teams to pull in the same direction.
• Clearly define roles and responsibilities. At the foundation of all empowerment efforts is a clear understanding of who is responsible for what, including who has input and who doesn’t.
• Invest in capability building (and coaching) up front. To help managers spend meaningful coaching time, organizations should also invest in managers’ leadership skills.
• Build an empowerment-oriented culture. Leaders should role model mindsets that promote empowerment, and managers should build the coaching skills they want to see. Managers and employees, in particular, will need to get comfortable with failure as a necessary step to success.
• Decide when to get involved. Managers should spend effort up front to decide what is worth their focused attention. They should know when it’s appropriate to provide close guidance and when not to.

How can you guard against bias in decision making?

Cognitive bias is real. We all fall prey, no matter how we try to guard ourselves against it. And cognitive and organizational bias undermines good decision making, whether you’re choosing what to have for lunch or whether to put in a bid to acquire another company.

Here are some of the most common cognitive biases and strategies for how to avoid them:

• Confirmation bias. Often, when we already believe something, our minds seek out information to support that belief—whether or not it is actually true. Confirmation bias  involves overweighting evidence that supports our belief, underweighting evidence against our belief, or even failing to search impartially for evidence in the first place. Confirmation bias is one of the most common traps organizational decision makers fall into. One famous—and painful—example of confirmation bias is when Blockbuster passed up the opportunity  to buy a fledgling Netflix for $50 million in 2000. (Actually, that’s putting it politely. Netflix executives remember being “laughed out” of Blockbuster’s offices.) Fresh off the dot-com bubble burst of 2000, Blockbuster executives likely concluded that Netflix had approached them out of desperation—not that Netflix actually had a baby unicorn on its hands.
• Herd mentality. First observed by Charles Mackay in his 1841 study of crowd psychology, herd mentality happens when information that’s available to the group is determined to be more useful than privately held knowledge. Individuals buy into this bias because there’s safety in the herd. But ignoring competing viewpoints might ultimately be costly. To counter this, try a teardown exercise , wherein two teams use scenarios, advanced analytics, and role-playing to identify how a herd might react to a decision, and to ensure they can refute public perceptions.
• Sunk-cost fallacy. Executives frequently hold onto underperforming business units or projects because of emotional or legacy attachment . Equally, business leaders hate shutting projects down . This, researchers say, is due to the ingrained belief that if everyone works hard enough, anything can be turned into gold. McKinsey research indicates two techniques for understanding when to hold on and when to let go. First, change the burden of proof from why an asset should be cut to why it should be retained. Next, categorize business investments according to whether they should be grown, maintained, or disposed of—and follow clearly differentiated investment rules  for each group.
• Ignoring unpleasant information. Researchers call this the “ostrich effect”—when people figuratively bury their heads in the sand , ignoring information that will make their lives more difficult. One study, for example, found that investors were more likely to check the value of their portfolios when the markets overall were rising, and less likely to do so when the markets were flat or falling. One way to help get around this is to engage in a readout process, where individuals or teams summarize discussions as they happen. This increases the likelihood that everyone leaves a meeting with the same understanding of what was said.
• Halo effect. Important personal and professional choices are frequently affected by people’s tendency to make specific judgments based on general impressions . Humans are tempted to use simple mental frames to understand complicated ideas, which means we frequently draw conclusions faster than we should. The halo effect is particularly common in hiring decisions. To avoid this bias, structured interviews can help mitigate the essentializing tendency. When candidates are measured against indicators, intuition is less likely to play a role.

For more common biases and how to beat them, check out McKinsey’s Bias Busters Collection .

Learn more about Strategy & Corporate Finance consulting  at McKinsey—and check out job opportunities related to decision making if you’re interested in working at McKinsey.

Articles referenced include:

• “ Bias busters: When the crowd isn’t necessarily wise ,” McKinsey Quarterly , May 23, 2022, Eileen Kelly Rinaudo , Tim Koller , and Derek Schatz
• “ Boards and decision making ,” April 8, 2021, Aaron De Smet , Frithjof Lund , Suzanne Nimocks, and Leigh Weiss
• “ To unlock better decision making, plan better meetings ,” November 9, 2020, Aaron De Smet , Simon London, and Leigh Weiss
• “ Reimagine decision making to improve speed and quality ,” September 14, 2020, Julie Hughes , J. R. Maxwell , and Leigh Weiss
• “ For smarter decisions, empower your employees ,” September 9, 2020, Aaron De Smet , Caitlin Hewes, and Leigh Weiss
• “ Bias busters: Lifting your head from the sand ,” McKinsey Quarterly , August 18, 2020, Eileen Kelly Rinaudo
• “ Decision making in uncertain times ,” March 24, 2020, Andrea Alexander, Aaron De Smet , and Leigh Weiss
• “ Bias busters: Avoiding snap judgments ,” McKinsey Quarterly , November 6, 2019, Tim Koller , Dan Lovallo, and Phil Rosenzweig
• “ Three keys to faster, better decisions ,” McKinsey Quarterly , May 1, 2019, Aaron De Smet , Gregor Jost , and Leigh Weiss
• “ Decision making in the age of urgency ,” April 30, 2019, Iskandar Aminov, Aaron De Smet , Gregor Jost , and David Mendelsohn
• “ Bias busters: Pruning projects proactively ,” McKinsey Quarterly , February 6, 2019, Tim Koller , Dan Lovallo, and Zane Williams
• “ Decision making in your organization: Cutting through the clutter ,” McKinsey Quarterly , January 16, 2018, Aaron De Smet , Simon London, and Leigh Weiss
• “ Untangling your organization’s decision making ,” McKinsey Quarterly , June 21, 2017, Aaron De Smet , Gerald Lackey, and Leigh Weiss
• “ Are you ready to decide? ,” McKinsey Quarterly , April 1, 2015, Philip Meissner, Olivier Sibony, and Torsten Wulf.

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A Conversation With President Zelensky

In a wide-ranging interview, president volodymyr zelensky of ukraine challenged the west’s hesitations..

Hosted by Sabrina Tavernise

Featuring Andrew E. Kramer

Produced by Nina Feldman ,  Clare Toeniskoetter ,  Rob Szypko and Diana Nguyen

With Michael Simon Johnson

Edited by Lisa Chow

Original music by Marion Lozano ,  Elisheba Ittoop and Sophia Lanman

Engineered by Chris Wood

Listen and follow The Daily Apple Podcasts | Spotify | Amazon Music | YouTube

Five years ago, a TV personality and comedian, Volodymyr Zelensky, won the presidency in Ukraine in a landslide victory. When Russia launched a full-scale invasion of the country three years later, he faced the biggest challenge of his presidency and of his life. Despite initial success beating back one of the world’s largest armies, the tide has turned against him.

Andrew E. Kramer, the Kyiv bureau chief for The Times, sat down with Mr. Zelensky to discuss the war, and how it might end.

On today’s episode

Andrew E. Kramer , the Kyiv bureau chief for The New York Times.

Background reading

Read The New York Times’s interview with President Volodymyr Zelensky of Ukraine .

Explaining the debate over Ukraine’s use of Western weapons .

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We aim to make transcripts available the next workday after an episode’s publication. You can find them at the top of the page.

Special thanks to Oleksandr Chubko .

The Daily is made by Rachel Quester, Lynsea Garrison, Clare Toeniskoetter, Paige Cowett, Michael Simon Johnson, Brad Fisher, Chris Wood, Jessica Cheung, Stella Tan, Alexandra Leigh Young, Lisa Chow, Eric Krupke, Marc Georges, Luke Vander Ploeg, M.J. Davis Lin, Dan Powell, Sydney Harper, Mike Benoist, Liz O. Baylen, Asthaa Chaturvedi, Rachelle Bonja, Diana Nguyen, Marion Lozano, Corey Schreppel, Rob Szypko, Elisheba Ittoop, Mooj Zadie, Patricia Willens, Rowan Niemisto, Jody Becker, Rikki Novetsky, John Ketchum, Nina Feldman, Will Reid, Carlos Prieto, Ben Calhoun, Susan Lee, Lexie Diao, Mary Wilson, Alex Stern, Sophia Lanman, Shannon Lin, Diane Wong, Devon Taylor, Alyssa Moxley, Summer Thomad, Olivia Natt, Daniel Ramirez and Brendan Klinkenberg.

Our theme music is by Jim Brunberg and Ben Landsverk of Wonderly. Special thanks to Sam Dolnick, Paula Szuchman, Lisa Tobin, Larissa Anderson, Julia Simon, Sofia Milan, Mahima Chablani, Elizabeth Davis-Moorer, Jeffrey Miranda, Maddy Masiello, Isabella Anderson, Nina Lassam and Nick Pitman.

Andrew E. Kramer is the Kyiv bureau chief for The Times, who has been covering the war in Ukraine since 2014. More about Andrew E. Kramer

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Problem Solving And Program Design in C 5th Edition

There is a newer edition of this item:.

• ISBN-10 0321409914
• ISBN-13 978-0321409911
• Edition 5th
• Publisher Addison-Wesley
• Publication date January 1, 2006
• Language English
• Dimensions 7.5 x 1.25 x 9 inches
• Print length 919 pages
• See all details

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Product details

• Publisher ‏ : ‎ Addison-Wesley; 5th edition (January 1, 2006)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 919 pages
• ISBN-10 ‏ : ‎ 0321409914
• ISBN-13 ‏ : ‎ 978-0321409911
• Item Weight ‏ : ‎ 2.95 pounds
• Dimensions ‏ : ‎ 7.5 x 1.25 x 9 inches
• #741 in C Programming Language
• #8,857 in Decision-Making & Problem Solving
• #17,595 in Computer Software (Books)

About the authors

Jeri r. hanly.

Jeri Hanly is Emerita Lecturer in Computer Science at the University of Wyoming. She has also recently been on the faculty of the Computer Science Department at Loyola College in Maryland and Howard University.

Elliot B. Koffman

Discover more of the author’s books, see similar authors, read author blogs and more

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