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[1] Site Reliability Engineering (SRE) is a discipline that monitors and improves the availability and performance of deployed software systems, often large software services that are expected to deliver reliable response times across events such as new software deployments, hardware failures, and cybersecurity attacks.
For databases reliability, availability, scalability and recoverability (RASR), is an important concept. Atomicity, consistency, isolation (sometimes integrity), durability is a transaction metric. When dealing with safety-critical systems, the acronym reliability, availability, maintainability and safety is frequently used.
Site reliability engineering, a discipline that incorporates aspects of software engineering and applies that to operations; Space Capsule Recovery Experiment, an Indian satellite; Sodium Reactor Experiment, a former US experimental nuclear power plant; Software reverse engineering
The Software Engineering Body of Knowledge (SWEBOK (/ ˈ s w iː ˌ b ɒ k / SWEE-bok)) refers to the collective knowledge, skills, techniques, methodologies, best practices, and experiences accumulated within the field of software engineering over time.
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2.0 Overview of Software Reliability Growth (Estimation) Models Software reliability growth (or estimation) models use failure data from testing to forecast the failure rate or MTBF into the future. The models depend on the assumptions about the fault rate during testing which can either be increasing, peaking, decreasing or some combination of ...
In engineering, reliability, availability, maintainability and safety (RAMS) [1] [2] is used to characterize a product or system: Reliability: Ability to perform a specific function and may be given as design reliability or operational reliability; Availability: Ability to keep a functioning state in the given environment
The cleanroom software engineering process is a software development process intended to produce software with a certifiable level of reliability. The central principles are software development based on formal methods, incremental implementation under statistical quality control, and statistically sound testing.