Verification vs. Validation

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.

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.

BFT (acronym of Byzantine Fault Tolerance) is a property of a system that allows it to continue operating correctly and reach consensus even if some of its components fail in arbitrary, unpredictable ways, including malicious behavior (Byzantine failures). This is a much stronger guarantee than tolerating simple crash failures. It requires a minimum of \(3f+1\) total components to tolerate \(f\) faulty, malicious components.

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.

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.

A statistical measure of a process's ability to produce output within customer-defined specification limits. Unlike control charts, which track stability, Cpk quantifies capability. It measures how centered the process is between the specification limits and accounts for process variation. A higher Cpk value indicates a more capable process. The formula is \(C_{pk} = \min\left[\frac{USL - \mu}{3\sigma}, \frac{\mu - LSL}{3\sigma}\right]\).

The Spiral Model is a risk-driven software development process model that combines elements of both prototyping and the waterfall model. It is a type of iterative development where the project passes through four phases in each iteration (spiral): determine objectives, identify and resolve risks, develop and test, and plan the next iteration. It emphasizes continuous risk analysis.