Rate-Monotonic Scheduling (RMS)

The Risk Priority Number (RPN) is a quantitative measure used in FMEA to prioritize risks. It is calculated as the product of three ranked factors: Severity (S), Occurrence (O), and Detection (D). The formula is \(RPN = S times O times D\). Each factor is typically rated on a scale from 1 to 10, allowing teams to focus on the highest-scoring risks first.

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.

The Finite Volume Method (FVM) is a dominant numerical technique in CFD for solving partial differential equations. It discretizes the domain into a mesh of control volumes and applies the governing equations in their integral form to each volume. By converting volume integrals to surface integrals using the divergence theorem, it focuses on calculating the flux of conserved properties across cell faces.

Formal verification is the use of mathematical methods to prove or disprove the correctness of a system's design with respect to a formal specification. Unlike testing, which can only show the presence of bugs for specific inputs, formal verification can prove their absence for all possible inputs. It involves creating a formal model of the system and using techniques like model checking or theorem proving.

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.

Verification and validation (V&V) are distinct processes. Verification ensures a product meets its specified requirements ("Are you building it right?"). Validation ensures the product meets the user's actual needs and intended use ("Are you building the right thing?"). They are complementary activities within quality management, often performed sequentially or in parallel to ensure both correctness and usefulness.

The repeatability limit, \(r\), is a critical value derived from the repeatability standard deviation (\(s_r\)). It represents the maximum expected absolute difference between two single test results, obtained under repeatability conditions, with a 95% probability. It is commonly calculated as \(r = 2.8 \times s_r\). If the difference exceeds \(r\), the results are considered suspect.