Risk Priority Number (RPN)

Automated theorem proving (ATP) is a subfield of computer science and mathematical logic dedicated to proving mathematical theorems using computer programs. ATP systems, or provers, use logical reasoning to deduce new theorems from a set of axioms and hypotheses. They are distinct from proof assistants, which require more human guidance, though the fields overlap significantly.

Verification techniques are broadly classified as static or dynamic. Static verification (or static analysis) examines the system's code or design without executing it. Examples include code reviews, inspections, and automated static analysis tools. Dynamic verification (or testing) involves executing the system with a set of inputs and observing its behavior to find defects. Both are complementary for comprehensive quality assurance.

Real-time systems are classified as "hard" or "soft" based on the consequence of missing a deadline. In a hard real-time system, missing a deadline is a total system failure, such as in an anti-lock braking system. In a soft real-time system, missing a deadline leads to degraded performance but not catastrophic failure, such as in live audio-video streaming.

Rate-Monotonic Scheduling (RMS) is a static-priority scheduling algorithm for periodic tasks in a real-time system. It assigns priorities based on task frequency: the shorter a task's period (the higher its rate), the higher its priority. RMS is an optimal static-priority algorithm, meaning if any static-priority algorithm can schedule a task set, RMS can too. Schedulability can be checked using a utilization-based test.

A regression model for a categorical, typically binary, dependent variable. Instead of modeling the outcome directly, it models the probability of the outcome using the logistic (sigmoid) function. The model predicts the log-odds of the event as a linear combination of the independent variables: \(\ln(\frac{p}{1-p}) = \beta_0 + \beta_1 x_1 + \dots + \beta_p x_p\), where p is the probability of the event.

The Metropolis-Hastings algorithm is a prominent MCMC method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. At each iteration, it generates a candidate for the next sample based on the current sample. This candidate is then accepted or rejected with a certain probability, ensuring the resulting chain converges to the desired distribution.

Abstraction in OOP is the concept of hiding complex implementation details and showing only the essential features of the object. It focuses on what an object does instead of how it does it. This is achieved through abstract classes and interfaces, which define a blueprint for other classes without providing a complete implementation, simplifying complex systems.

The Seven Basic Tools of Quality are a set of graphical techniques identified by Kaoru Ishikawa for troubleshooting quality-related issues. These tools are: Cause-and-effect diagram (fishbone), Check sheet, Control chart, Histogram, Pareto chart, Scatter diagram, and Stratification (often presented as a flowchart). They are considered 'basic' because they are simple to use and require little formal statistical training.

The Waterfall Model is a sequential, non-iterative software development process, where progress flows steadily downwards (like a waterfall) through distinct phases: conception, initiation, analysis, design, construction, testing, deployment and maintenance. Each phase must be fully completed before moving to the next. It is often contrasted with iterative models to highlight their flexibility.

The recovery block scheme is a software fault-tolerance technique based on design diversity and backward error recovery. It structures a program as a series of blocks, each with a primary module, an acceptance test, and one or more alternate modules. If the primary module's output fails the acceptance test, the system state is restored, and an alternate module is executed.