The Capability Maturity Model (CMM) is a development model created in 1986 after a study of data collected from organizations that contracted with the U.S. Department of Defense, who funded the research. The term "maturity" relates to the degree of formality and optimization of processes, from ad hoc practices, to formally defined steps, to managed result metrics, to active optimization of the processes.
In computing, a legacy system is an old method, technology, computer system, or application program, "of, relating to, or being a previous or outdated computer system", yet still in use. Often referencing a system as "legacy" means that it paved the way for the standards that would follow it. This can also imply that the system is out of date or in need of replacement.
Safety engineering is an engineering discipline which assures that engineered systems provide acceptable levels of safety. It is strongly related to industrial engineering/systems engineering, and the subset system safety engineering. Safety engineering assures that a life-critical system behaves as needed, even when components fail.
Failure mode and effects analysis is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet. There are numerous variations of such worksheets. An FMEA can be a qualitative analysis, but may be put on a quantitative basis when mathematical failure rate models are combined with a statistical failure mode ratio database. It was one of the first highly structured, systematic techniques for failure analysis. It was developed by reliability engineers in the late 1950s to study problems that might arise from malfunctions of military systems. An FMEA is often the first step of a system reliability study.
In software development, code reuse, also called software reuse, is the use of existing software, or software knowledge, to build new software, following the reusability principles.
In the context of software engineering, software quality refers to two related but distinct notions:
ISO/IEC 9126Software engineering — Product quality was an international standard for the evaluation of software quality. It has been replaced by ISO/IEC 25010:2011.
Prognostics is an engineering discipline focused on predicting the time at which a system or a component will no longer perform its intended function. This lack of performance is most often a failure beyond which the system can no longer be used to meet desired performance. The predicted time then becomes the remaining useful life (RUL), which is an important concept in decision making for contingency mitigation. Prognostics predicts the future performance of a component by assessing the extent of deviation or degradation of a system from its expected normal operating conditions. The science of prognostics is based on the analysis of failure modes, detection of early signs of wear and aging, and fault conditions. An effective prognostics solution is implemented when there is sound knowledge of the failure mechanisms that are likely to cause the degradations leading to eventual failures in the system. It is therefore necessary to have initial information on the possible failures in a product. Such knowledge is important to identify the system parameters that are to be monitored. Potential uses for prognostics is in condition-based maintenance. The discipline that links studies of failure mechanisms to system lifecycle management is often referred to as prognostics and health management (PHM), sometimes also system health management (SHM) or—in transportation applications—vehicle health management (VHM) or engine health management (EHM). Technical approaches to building models in prognostics can be categorized broadly into data-driven approaches, model-based approaches, and hybrid approaches.
Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability describes the ability of a system or component to function under stated conditions for a specified period of time. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time.
Probabilistic risk assessment (PRA) is a systematic and comprehensive methodology to evaluate risks associated with a complex engineered technological entity or the effects of stressors on the environment.
A software factory is a structured collection of related software assets that aids in producing computer software applications or software components according to specific, externally defined end-user requirements through an assembly process. A software factory applies manufacturing techniques and principles to software development to mimic the benefits of traditional manufacturing. Software factories are generally involved with outsourced software creation.
SEER for Software (SEER-SEM) is a project management application used to estimate resources required for software development.
The function point is a "unit of measurement" to express the amount of business functionality an information system provides to a user. Function points are used to compute a functional size measurement (FSM) of software. The cost of a single unit is calculated from past projects.
Software sizing or software size estimation is an activity in software engineering that is used to determine or estimate the size of a software application or component in order to be able to implement other software project management activities. Size is an inherent characteristic of a piece of software just like weight is an inherent characteristic of a tangible material.
IT Application Portfolio Management (APM) is a practice that has emerged in mid to large-size information technology (IT) organizations since the mid-1990s. Application Portfolio Management attempts to use the lessons of financial portfolio management to justify and measure the financial benefits of each application in comparison to the costs of the application's maintenance and operations.
Whole-life cost is the total cost of ownership over the life of an asset. The concept is also known as life-cycle cost (LCC) or lifetime cost, and is commonly referred to as "cradle to grave" or "womb to tomb" costs. Costs considered include the financial cost which is relatively simple to calculate and also the environmental and social costs which are more difficult to quantify and assign numerical values. Typical areas of expenditure which are included in calculating the whole-life cost include planning, design, construction and acquisition, operations, maintenance, renewal and rehabilitation, depreciation and cost of finance and replacement or disposal.
A glossary of terms relating to project management and consulting.
The Continuous Quality Assessment Toolkit (ConQAT) is a configurable software quality analysis engine. ConQAT is based on a pipes and filters architecture that enables flexible complex analysis configurations using a graphical configuration language. This architecture differs from other analysis tools that usually have a fixed data model and hard-wired analysis logics.
Financial software or financial system software is special application software that records all the financial activity within a business organization. Basic features of this system not only includes all the modules of accounting software like accounts payable, accounts receivable, ledger, reporting modules and payroll but also to explore alternative investment choices and calculate statistical relationships. Features of the system may vary depending on what type of business it is being used for. Primarily, the goal of the financial software is to record, categorize, analyze, compile, interpret and then present an accurate and updated financial dates for every transaction of the business.
Failure modes, effects, and diagnostic analysis (FMEDA) is a systematic analysis technique to obtain subsystem / product level failure rates, failure modes and diagnostic capability. The FMEDA technique considers:
