Comprehensive Vocabulary & Self-Test Quizzes
Definition: An observation — not a law of physics — made by Gordon Moore, co-founder of Intel, that the number of transistors on a chip doubles approximately every 18 months while the cost of that performance stays roughly the same. This means computing power per dollar grows exponentially over time.
Why it matters: Moore's Law became the semiconductor industry's de-facto business plan, setting the expected pace of innovation. Even though transistor shrinkage is slowing, capability continues to grow rapidly — AI capabilities, for example, are currently doubling roughly every 6 months.
Source: Intel NewsroomDefinition: An economic concept describing how much consumer demand changes when the price of a good changes. Demand is highly elastic when a price drop causes a proportionally large increase in the quantity demanded.
Why it matters for tech: Demand for computing power is highly elastic. As chips get cheaper, people find entirely new uses for them — cloud storage, GenAI, tiny wearable devices — and they buy much more. Managers who ignore this are routinely blindsided by the disruptive speed of technology change.
Source: InvestopediaDefinition: A microscopic electronic switch built into a semiconductor chip that can be either "on" (1) or "off" (0), representing binary data. A single modern computer chip contains billions of transistors packed together to perform complex calculations.
Why it matters: Transistors are the fundamental building blocks of all digital computing. Moore's Law is specifically about how many transistors fit on a chip — more transistors = more processing power.
Source: Gallup / course slidesDefinition: A semiconductor is a material (typically silicon) that conducts electricity under some conditions but not others, making it ideal for building transistors. A computer chip (integrated circuit) is a small piece of semiconductor material containing billions of transistors used in CPUs, GPUs, and memory.
Why it matters: Chips are manufactured in specialized facilities called fabs that cost $10–20 billion to build. Most of the world's advanced chips are made by Taiwan Semiconductor (TSMC), creating both an oligopoly and a geopolitical risk — which led the U.S. to pass the CHIPS and Science Act in 2022.
Source: Course slides, Ch 6Volatile memory (RAM): Temporary, fast workspace memory that loses all data when power is cut. The CPU uses RAM as its "kitchen counter" — data being actively worked on lives here. More RAM = more tasks can run simultaneously without slowdowns.
Non-volatile memory (Storage — SSD/HDD): Persistent storage that retains data even without power. This is the "refrigerator" where programs and files are kept long-term until the CPU needs them.
Key distinction: RAM is fast but temporary; storage is slower but permanent. The bottleneck between the two is a key performance consideration.
Source: IntelDefinition: A mental model from the slides for understanding how a computer works:
The Golden Rule: 8 bits = 1 byte.
Storage is measured in Bytes (capital B): KB, MB, GB, TB.
Data transfer / network speed is measured in bits (lowercase b): Mbps = megabits per second.
The Gotcha: Your ISP advertises speed in Mbps, but your download speed shows in MB/s. A 100 Mbps connection only downloads at 12.5 MB/s because you must divide by 8. Students often confuse these and think their internet is slower than advertised.
Source: Course slides, Ch 6Bandwidth: How much data can move at once — think lanes on a highway. Measured in Mbps/Gbps. Critical for streaming 4K video (~25 Mbps needed).
Latency: How fast a single packet travels from A to B — think the speed limit. Measured in milliseconds (ms). Critical for online gaming (<50ms needed) and real-time interactions.
Cloud computing tradeoff: Offloading processing to the cloud introduces latency because data must make an "internet round trip" to remote servers and back.
Source: Course slides, Ch 6Definition: Using multiple processors (or processor cores) simultaneously to solve a problem faster, rather than doing tasks one at a time. Modern CPUs have multiple cores; supercomputers use thousands of processors in concert.
Multicore CPUs: Contain 2 or more calculating cores on a single chip. A group of multicore chips typically outperforms a single fast chip while running cooler and drawing less power.
GPUs & ASICs: Nvidia's GPUs were originally designed for graphics (which require massive parallelism) but turned out to be ideal for AI. The general term for purpose-built chips is Application-Specific Integrated Circuits (ASICs).
Source: Course slides, Ch 6Definition: A layered model (from Prof. Prabhudev Konana, 2007) showing how software layers sit on top of hardware, each depending on the layer beneath it:
Strategic implication: Because each layer depends on those below it, the ecosystem creates lock-in and switching costs. Strategic decisions must account for ecosystem entrenchment — changing one layer can force costly changes in every layer above it.
Source: Course slides, Ch 6Definition: Discarded, often obsolete technology — also called electronic waste. Global e-waste reached 62 million tons in 2022 and is projected to hit 74 million tons by 2030.
Why it matters: E-waste contains toxic substances (lead, cadmium, mercury) that contaminate soil and water if not recycled correctly. Informal recycling (e.g., burning) harms workers, often children, in developing countries. There is no comprehensive federal e-waste recycling law in the U.S. Moore's Law drives e-waste because rapidly improving and cheapening hardware encourages frequent device replacement.
Source: Course slides, Ch 6Question 1. A student startup is building an AI-powered study app. Right now the AI model requires a chip that costs $500 to run effectively, which makes their hardware budget impossible for a student team. Their faculty advisor tells them not to worry — based on a well-known industry observation, the same level of processing performance should cost roughly half as much in about 18 months without any change in the team's code. The advisor also notes this same trend is why pocket calculators went from $400 in 1970 to practically free today.
Which concept is the faculty advisor describing?
Question 2. A small streaming music startup notices something interesting: every time the price of cloud storage drops, their number of paying subscribers jumps far more than expected. When storage cost fell 30% last quarter, subscriber growth shot up over 80%. The CEO argues this happens because cheaper storage lets them offer larger music libraries and higher audio quality, attracting customers who previously found the service not worth it. The CFO wants a single concept to explain this relationship for their investor deck.
Which concept best explains why a 30% price drop in storage produces an 80% jump in demand?
Question 3. During a group project presentation, your teammate explains Apple's strategy for rolling out its M-series chips. She says Apple redesigned the chip from scratch to run frequently used instructions via shorter pathways, boosting speed and cutting power use dramatically. The downside was that existing Mac apps written for Intel chips suddenly couldn't communicate with the new processor. Apple's solution was to bundle a special program with every new Mac that "translates" old Intel instructions into M-series instructions in real time, so users could keep using their existing software immediately after switching.
What is the specific name of the software tool Apple used to maintain backward compatibility?
Question 4. A logistics company equips its warehouse workers with rugged handheld scanners. Each scanner must record every package scan — even if the device loses power mid-shift — because missing a record could mean lost packages worth thousands of dollars. The IT manager explains that the scanners use one type of memory as a fast workspace while the CPU processes each scan, and a separate type of memory to save every completed record permanently so it survives a dead battery. She warns the team that if the fast workspace memory fills up, scans will slow to a crawl.
Which pairing correctly identifies the two memory types the IT manager is describing?
Question 5. A UT Austin student working a part-time IT internship is asked to explain why the company's voice-activated customer service bot stops functioning whenever the office internet goes down, even though the server running the bot is physically located in the office. The intern's supervisor explains it's because the bot's language processing is not handled by local hardware — instead, every spoken request is sent to a remote data center, processed there, and the answer is sent back. The supervisor adds that this design choice saves enormous hardware costs but introduces a performance tradeoff the team must manage.
What is the specific performance tradeoff the supervisor is referring to?
Definition: A set of instructions that tells hardware what to do. Software comes in many categories — from operating systems that manage hardware resources, to enterprise applications like SAP that coordinate entire organizations, to consumer apps like Chrome or Canvas that individual users interact with daily.
Why managers care: Software choices affect every business function — cost structure, competitive advantage, ability to partner, and how easily a firm can be acquired. Understanding software is not just an IT job; it is a strategic management responsibility.
Source: Course slides, Ch 7The slides give managers a four-question framework to evaluate any piece of software:
Example table from slides: Excel = User App, Closed source, Local, Open standard. Linux = OS, Open source, Local, Open standard. Apple Numbers = User App, Closed source, Local, Closed standard.
Source: Course slides, Ch 7Definition: A visual, icon-based interface that lets users interact with software using a mouse, touchscreen, or keyboard shortcuts — drop-down menus, radio buttons, check boxes — instead of typing commands in raw text at a command line.
Why it matters: Before GUIs, every computer user had to know programming language and work at the command line. The GUI democratized computing, enabling non-programmers to use computers and vastly expanding the market for software. Managers interact with virtually all software through a GUI.
Source: Course slides, Ch 7Definition: The software layer that sits between hardware and all user/enterprise applications. It acts as the interface between the hardware and users & applications — processing keystrokes and mouse movements, sending signals to the monitor, reading and writing disk files, controlling processing of user applications, and managing and coordinating tasks and sharing the computer's resources. It also sets the "look and feel" of the computing environment.
Every computing device has one — desktops, laptops, enterprise servers, mobile phones, video game consoles, car dashboards, and even microwave ovens.
OS Business Models: Some firms sell OS as their major product (Microsoft Windows). Some give it out for free (Linux, Android). Some bundle a proprietary OS with their hardware (Apple macOS/iOS). Some specialty firms build OS for specific devices like fighter jets.
Source: Course slides, Ch 7Definition: Software used for creating, maintaining, and manipulating data. It sits in Konana's Ecosystem above the OS and below middleware and enterprise applications. Most enterprise software works in conjunction with a DBMS. Examples: Microsoft SQL Server, Oracle, MySQL, IBM DB2.
Key concept — DB Application System: A database application is a collection of forms, reports, queries, and programs that process a database. The full system flows: User → DB Application (forms/reports/queries) → DBMS → Database (tables/relationships/metadata). Multiple applications can share one DBMS — for example, Amazon's Order Entry, Warehouse Management, and Purchasing applications all read from the same Inventory Database.
Why a DBMS beats flat files: Multiple applications with different purposes can share the same data without duplication, ensuring consistency — "one version of the truth."
Source: Course slides, Ch 7Definition: Software that sits between the DBMS and enterprise applications in Konana's Ecosystem, acting as "plumbing for data." It translates data formats and enables different enterprise applications to communicate with each other in real time, even if they were built by different vendors or use different data structures.
Analogy from slides: Middleware is like the pipes in a building — you don't see it, but without it data can't flow from one room (application) to another.
Source: Course slides, Ch 7Definition: An enterprise application that integrates many functions needed across an organization — Human Resources, Manufacturing, Inventory, Sales, Purchasing, Order Tracking, and Decision Support — into a single system backed by one common database. SAP is the most prominent example.
Strategic impact (Nestlé case): Nestlé sells 100,000 products in 200 countries. Of 9 million vendor/customer/material records, roughly half were obsolete or duplicated. After a SAP ERP overhaul consolidating everything into ONE database, American operations saved $30 million per year on vanilla alone — by eliminating double-counting and inconsistent records.
Rewards: Streamlines processes, makes data more usable, eases linking with business partners, and can make a firm more attractive as an acquisition target.
Source: Course slides, Ch 7Three major categories of enterprise software that often work alongside or within an ERP:
Integration point: A single shared database connecting SCM, ERP, CRM, and proprietary systems = increased value chain efficiency = more revenue (the "Enterprise IS + DB = $$$" slide).
Source: Course slides, Ch 7Definition: The full lifetime cost of a software investment — not just the purchase price (roughly 20% of the iceberg), but all the hidden costs beneath the surface (~80%), including:
Analogy from slides: Like a car — the sticker price ($) is just the start. Add gas ($), insurance ($$), and maintenance ($$$) and the total cost ($$$$$$$$$$$) is far higher than what you paid the dealer.
Source: Course slides, Ch 7Question 1. A UT Austin student is analyzing two spreadsheet programs for a finance internship. She notes that Microsoft Excel is installed directly on the company's laptops and runs without internet, while Google Sheets runs entirely through a web browser and needs a network connection to function. Both programs have closed source code that only their respective companies can modify. The firm also uses Apple Numbers on one executive's Mac — its files cannot be opened by any third-party spreadsheet app unless Apple specifically allows it.
Using the four-question software classification framework, which characteristic makes Apple Numbers MOST strategically risky for the firm?
Question 2. A part-time IT support student at McCombs is helping a small nonprofit set up a new laptop. The nonprofit director asks why she needs to install Windows before installing QuickBooks accounting software. The student explains that without Windows already on the machine, QuickBooks has no way to communicate with the computer's processor, memory, or hard drive — and that Windows also handles tasks like reading keystrokes, writing files to disk, and managing memory shared between multiple programs running at the same time. The director still looks confused, so the student tries a simpler analogy.
Which analogy MOST accurately describes the role of the operating system in this scenario?
Question 3. A regional grocery chain operates three separate software systems: one for online orders entered by customers, one for warehouse staff to manage shelf inventory, and one for the purchasing team to reorder products from suppliers. Each system has its own interface and purpose, but the chain's IT director explains that all three programs read from and write to the exact same inventory database. When a customer places an order online, the warehouse system immediately sees the reduced stock level, and the purchasing system can automatically trigger a reorder without any manual data entry.
Which concept from the DB Application System framework explains how three different applications can share one database without conflicting with each other?
Question 4. A hospital network uses three separate software platforms: one for patient medical records (built by Vendor A), one for billing and insurance claims (built by Vendor B), and one for lab results (built by Vendor C). When a doctor orders a lab test, the result automatically appears in both the medical record and the billing system within seconds — even though all three platforms were built independently and use different data formats. The hospital's CIO explains that a critical software layer translates the data between these systems and routes it in real time, without requiring any of the three vendors to modify their own products.
Which layer of Konana's Ecosystem is the CIO describing?
Question 5. A small Austin e-commerce startup is deciding whether to build a custom inventory system or buy a well-known packaged ERP solution. The sales pitch for the ERP shows a license fee of $50,000 — and the founder thinks that sounds expensive but manageable. Her advisor pulls out a list: the firm will also need to pay $20,000 for a consultant to configure the system, $15,000 to train staff, lose roughly $30,000 in productivity during the learning curve, and budget $10,000 per year for ongoing support and updates. The advisor warns that the $50,000 number is "just the tip of the iceberg."
Which concept is the advisor applying, and approximately what is the true 3-year cost?
Definition — OSS: Software whose source code is openly shared and freely downloadable by anyone. It can be modified and redistributed, though most OSS licenses prohibit selling derivative or customized versions. OSS vendors make money by selling support, consulting, and managed-hosting services — not the code itself.
Definition — Closed Source (Proprietary): Software sold by conventional vendors whose source code is treated as intellectual property and is not available to customers. Vendors profit when customers pay to download the machine-code executable or pay a monthly SaaS fee to access the software online.
Key distinction for the exam: The difference is not "free vs. paid" — it is "who can read and change the underlying code." Open Office is open source; Microsoft Excel is closed source. Both are user applications (same Konana layer), both run locally, and both use open standards — they differ only on source code access.
Source: Course slides, Ch 8Source code is the human-readable set of instructions a programmer writes — in Python, Java, PHP, C++, etc. Each programming language has its own vocabulary (keywords) and grammar (syntax), just like natural languages.
Machine code is the binary (0s and 1s) that the CPU actually executes. Source code must be translated into machine code either by a compiler (translation happens once, ahead of time — faster at runtime, "closer to the metal," e.g., C, C++) or by an interpreter/runtime (translation happens line-by-line as the program runs — slower but usually easier to write, e.g., Python, PHP).
Why it matters for OSS: In closed-source software, only the machine code is distributed — customers cannot read or modify the logic. In open-source software, the source code itself is distributed, allowing anyone with programming experience to understand and change how the program works.
Source: Course slides, Ch 8Understanding the why behind OSS dominance is a recurring exam theme. The story unfolds in four acts:
Core argument: Open source is a $60 billion industry, but has a disproportionately large impact on the $1.4 trillion IT software market because it lowers the cost of infrastructure for every firm in the economy.
The strategic logic (key for managers):
The headline principle: "Keeping the lights on" does not create competitive advantage. Infrastructure is a commodity. Competing on proprietary infrastructure is wasteful; competing on what you build on top of that infrastructure is where firms win.
Source: Course slides, Ch 8Definition: A tech stack is a coordinated set of layered software technologies that work together to make a website or application function. Each layer maps directly to Konana's Ecosystem.
The shift from Web 1.0 (static pages) to Web 2.0 (dynamic, interactive pages — YouTube, blogs, social media, e-commerce) created user demand that only an integrated open-source stack could satisfy cheaply enough to scale.
LAMP Stack (Classic — powers 40%+ of all websites):
MEAN Stack (Modern — built for real-time, constantly changing data):
Key MEAN advantage: all JavaScript, so a single "full-stack" developer can work at every layer — easier and cheaper to hire than LAMP's multi-language team. Powers: Netflix, Uber.
Source: Course slides, Ch 8Enterprise users are not buying the code — they are buying insurance, scale, and peace of mind. The four main revenue models:
Many large technology firms pay their engineers to contribute to open-source projects — not out of charity, but because OSS contributions support their core revenue strategies:
AI is described in the slides as a "Data Revolution," not just an "Algorithm Revolution." Business leaders risk focusing on the AI model (the "brain") while ignoring the data infrastructure (the "fuel").
The core insight: AI is only as good as the data it is fed. If a firm's data stack is fragmented, siloed, or poorly governed, no model will deliver reliable insights. Understanding the tech stack lets a manager audit the firm's "data readiness".
Source: Course slides, Ch 8OSS dominates infrastructure but struggles with consumer-facing productivity apps. The reasons:
Question 1. A UT Austin MIS student is interning at a mid-size Austin hospital. The hospital's IT director explains that the entire patient records platform runs on Linux servers with a MySQL database and Apache handling web requests — all open-source components. However, when the student asks why doctors still use Microsoft Windows on their workstations rather than switching to Linux (which would be free to license), the director explains that the support costs alone for a non-technical clinical staff on Linux desktops would far exceed the cost of Windows licenses. Additionally, a handful of specialized clinical applications the hospital is legally required to use are only certified to run on Windows.
Which two concepts from Ch 7–8 together BEST explain why the hospital uses OSS for servers but proprietary software for doctor workstations?
Question 2. In the early 2000s, a rapidly growing digital economy that included e-commerce, online banking, and social media was built almost entirely on Linux servers — a project originally created and maintained by a small group of unpaid volunteers. Large corporations like IBM, HP, Oracle, and Intel had come to depend on this infrastructure for their own cloud and server businesses. Executives at these firms began to realize that if key volunteer maintainers quit, burned out, or were no longer able to contribute, the entire ecosystem could stall — despite representing billions of dollars in commercial value. They also feared that without coordination, rival corporations might push incompatible versions of Linux the way competing Unix variants had fragmented that ecosystem decades earlier.
Which two specific risks did these corporations identify, and what institution did they create to address both?
Question 3. A McCombs student is starting a food delivery startup in Austin. She needs to build a web application where customers can create accounts, browse menus, place orders, and track deliveries in real time — with data updating on screen the moment the driver's location changes. Her co-founder suggests the MEAN stack, arguing it is better suited to this scenario than LAMP. The student agrees but admits she is not sure she can explain why in terms the investors will understand.
Which explanation MOST accurately describes why MEAN is the better architectural choice for this specific application?
Question 4. A product manager at a large Austin tech firm is sitting in a meeting where the CTO proposes deploying a new AI-powered customer analytics tool. The vendor's pitch is slick — the model's accuracy benchmarks are impressive, and the demo shows real-time personalization that executives find exciting. The product manager raises her hand and asks a question that visibly annoys the CTO: "Before we buy the model, can we talk about where our customer data actually lives right now, how clean it is, and whether our data infrastructure can feed this system reliably?" A colleague whispers to her after the meeting that she "killed the vibe." She responds that without answering those questions first, the AI purchase would fail regardless of how good the model is.
Which concept from Ch 8 is the product manager applying, and why does it matter specifically in the context of AI adoption?
Question 5. A UT Austin student is debating with her roommate whether Meta (Facebook) was acting altruistically or strategically when it released Llama — its large language model — as open-source software, making it freely available to developers everywhere and directly competing with OpenAI's paid ChatGPT product. The roommate argues that Meta was just "being nice" and contributing to the open-source community. The student pushes back, arguing that Meta had a very clear strategic reason for doing so, which aligns with a pattern seen across multiple companies discussed in the Ch 8 slides.
What is the MOST accurate strategic explanation for why Meta released Llama as open-source, and which other company from the slides follows the same pattern for the same underlying reason?
Definition: A form of cloud computing where a firm accesses software online as a service instead of installing it locally. The SaaS provider manages everything—hardware, operating system, database, middleware, and the enterprise/consumer application itself. Examples include Canvas, Office 365, and Salesforce.
Why managers care: It shifts the financial burden from a large upfront capital expense (CapEx) to a predictable operational expense (OpEx).
Infrastructure as a Service (IaaS): The vendor provides raw hardware (servers, storage) over the internet, but the client must manage the OS, databases, and apps. Example: Netflix running on AWS.
Platform as a Service (PaaS): The vendor provides the hardware, OS, database, and middleware. The client company only manages their own custom enterprise applications built on top of this platform. Example: Salesforce allows customers to build custom apps connected to Salesforce data.
Software as a Service (SaaS): The vendor manages the entire stack, right up to the user application.
SaaS firms generate revenue in several distinct ways instead of charging one-time license fees.
For Enterprises: Faster deployment times, lower upfront costs (no need to buy servers or hire armies of consultants), access to higher quality hardware, remote availability, and highly scalable systems.
For Providers: They only have to develop and maintain code for one platform (their own cloud environment) rather than thousands of different Windows/Mac variations. Deploying fixes and updates is instantaneous, and software piracy is drastically reduced because the code is never distributed to users.
Cloud computing transforms the TCO curve. Traditional software involves a massive spike in upfront costs (hardware, licenses, consultants) followed by lower maintenance fees, then another spike for major upgrades. SaaS flattens this curve out into a steady, predictable monthly cost, making IT budgeting much easier and less risky.
While the cloud is powerful, it carries distinct risks:
Question 1. An independent video game studio used to distribute its software on physical discs, but struggled with rampant piracy costing them millions. They recently shifted their model entirely: users now pay a $15 monthly fee to stream the games directly to their TVs from the studio's remote servers. The users never actually download or own the game code. In addition to eliminating piracy, the studio’s lead developer notes that when they find a bug, they can fix it on their server once, and the fix is instantly applied to all players globally without forcing users to download patches.
Based on the Chapter 9 slides, the studio has shifted to which business model, and which two provider benefits are they experiencing?
Question 2. A McCombs MIS student lands a job at a retail company. The company’s old IT infrastructure required them to buy millions of dollars in servers and database licenses every three years, followed by hiring expensive consultants from IBM to configure it. A new CIO comes in and shifts the company to a cloud-based inventory platform. Now, instead of huge, unpredictable cash outlays every few years, the firm pays a steady, predictable monthly fee per user, freeing up cash flow for new store openings.
Which financial concept does this scenario illustrate regarding the shift to cloud computing?
Question 3. A student working on an MIS 302f assignment is frustrated. They are trying to upload a large Excel file that is stored on their UT Box cloud account directly into an assignment submission window in Canvas (which is also a cloud service). The upload is taking far longer than expected. The professor explains that the data isn't moving directly from Box to Canvas; instead, the file must be sent from the Box server, down to the student's browser on their laptop, and then back up to the Canvas server.
What specific cloud computing challenge is causing this delay?
Question 4. During a board meeting, the CEO of a mid-sized healthcare company pushes back against the IT Director's proposal to move patient records to Amazon Web Services (AWS). The CEO states, "I refuse to put our highly sensitive data on some remote Amazon server. It is much safer right here in the server closet down the hall where we can physically lock the door." The IT Director replies that while the CEO's instinct is common, it is factually incorrect.
Based on the Chapter 9 slides, how should the IT Director accurately counter the CEO's security concern?
Question 5. A rapidly growing startup needs to update its technology strategy. They decide to rent raw processing power and basic server hardware from Amazon over the internet to run their back-end infrastructure. However, for their HR and payroll team, they simply buy a monthly subscription to Workday, which provides a fully complete, ready-to-use application accessed via a web browser.
According to Konana's ecosystem and cloud computing models, what two types of cloud services is this startup using?
Concept: "There are no IT projects, some business projects have an IT component." (Kaiser-Permanente CIO Cliff Dodd).
Why it matters: Information systems are never just off-the-shelf; they are built to serve a business function. Taking responsibility for requirements analysis is the single most important task a business manager can perform. If business users do not clearly define the features and processes the software must execute, the project will fail regardless of how good the programming is.
Definition: Every project is bounded by three interdependent constraints: Scope (requirements/features), Resources (money, people, equipment), and Schedule (time).
The Tradeoff: You cannot change one without affecting the others. If a manager increases the Scope (adds features), they must either increase the Schedule (delay the launch) or increase the Resources (spend more money). Note: Time can only be reduced to a point, and adding more people can actually backfire (see Brook's Law).
Definition: "Adding more people to a late software project makes it later."
Why it happens: Software development suffers from diseconomies of scale. As development teams grow, the average contribution per worker decreases. When new people are added to a project mid-stream, the existing team must stop working to train them, and the overhead required to coordinate the larger group consumes more time than the new workers provide.
Compiled Languages (e.g., C++, C#): Code written by the programmer is translated into machine-readable binary (compiled) entirely up front, before the program is run. Often faster at runtime but specific to the hardware it was compiled for.
Interpreted / Scripting Languages (e.g., Python, Java, JavaScript): Code is translated line-by-line within an application (an interpreter) as the program runs. Slower, but provides platform independence (code written once can run anywhere the interpreter is installed).
Waterfall Method: A rigid, linear, sequential approach to software development. Requirements are gathered completely up front to create a "blueprint," followed by design, coding, testing, and deployment. Highly out-of-favor because it cannot adapt to changing business requirements, leading to massive cost overruns and fiascos.
Agile Method: The dominant methodology today. Work is developed continually and iteratively in small chunks. Prioritizes frequent product rollouts, constant improvement, and rapid adaptation to feedback. Prototypes and wireframes are heavily used to let users test interfaces early.
Definition: Highly visual software tools (like Microsoft Power Apps or Google AppSheet) that allow non-programmers (called "citizen developers") to build information systems without writing raw code.
Risks: While LCNC is a $27 billion booming market, allowing business users to build apps without IT oversight bypasses governance. It risks creating duplicate data, introducing security flaws, and violating legal regulations like HIPAA (healthcare) or FERPA (student records).
The Failure: Launched in 2013, the site crashed immediately. Root causes were classic project management failures: lack of clear authority/leadership, scope complexity, inability to handle demand, and zero performance dashboards.
The Rescue: It was fixed in about two months by bringing in clear leadership with true authority, seasoned technologists who set clear priorities, and the implementation of Agile practices (specifically daily stand-up meetings to coordinate the teams).
Question 1. The University of Texas is upgrading its financial aid portal. Two months before the launch deadline, the project manager realizes they are deeply behind schedule. Panicking, the manager requests an emergency budget increase and hires 15 external software developers to join the existing 5-person team, assuming this will quadruple their coding speed. However, one month later, the project is even further behind because the original team spends all day explaining the system architecture to the new hires instead of coding.
Which project management principle perfectly describes why this intervention failed?
Question 2. A McCombs graduate is managing the development of a custom CRM tool. Halfway through development, the marketing team asks to add a massive new feature: an AI chatbot for customer service. The project manager looks at the "Project Management Triple Constraint" and explains to the marketing team that adding this feature represents a major increase in the project's Scope.
According to the Triple Constraint model, if the Scope increases, what must the project manager do?
Question 3. A startup is developing a mobile application. Rather than waiting 18 months to launch a perfectly polished final product, the team releases a functional but basic "Version 1.0" after just six weeks. They study how users interact with the app, identify flaws, and release an updated "Version 1.1" two weeks later. They repeat this cycle continuously, prioritizing flexibility and constant feedback.
Which software development methodology is this team using?
Question 4. An HR director at a large logistics company gets tired of waiting for the IT department to build a new employee onboarding portal. Using a visual, drag-and-drop tool provided by Microsoft, she builds the application herself over a weekend without writing any code. However, three months later, the company is fined by federal regulators because the portal inadvertently stored employees' sensitive health data in an unencrypted format, violating HIPAA regulations.
Which specific trend in software development does this highlight, and what is its primary risk?
Question 5. In a post-mortem review of a failed $5 million supply chain software project, the lead software engineer testifies: "We built exactly what you asked for! The code is flawless, the servers are fast, and there are zero bugs." The Director of Logistics replies, "Yes, but the system doesn't match how our warehouse workers actually load trucks, so nobody can use it!"
According to the Ch 10 slides, who is primarily to blame for this failure and why?