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A requirements traceability matrix may be used to check if the current project requirements are being met, and to help in the creation of a request for proposal, [2] software requirements specification, [3] various deliverable documents, and project plan tasks. [4]
Reverse Semantic Traceability as a validation method can be applied to any project artifact, to any part of project artifact or even to a small piece of document or code. However, it is obvious that performing RST for all artifacts can create overhead and should be well justified (for example, for medical software where possible information ...
Requirements traceability is a sub-discipline of requirements management within software development and systems engineering.Traceability as a general term is defined by the IEEE Systems and Software Engineering Vocabulary [1] as (1) the degree to which a relationship can be established between two or more products of the development process, especially products having a predecessor-successor ...
In fact, the key characteristic of round-trip engineering that distinguishes it from forward and reverse engineering is the ability to synchronize existing artifacts that evolved concurrently by incrementally updating each artifact to reflect changes made to the other artifacts. Furthermore, forward engineering can be seen as a special instance ...
Reverse Semantic Traceability is a quality control method that allows testing outputs of every translation step. Before proceeding to the next phase, the current artifacts are “reverse engineered”, and the restored text is compared to the original. If there is a difference between these two texts – the tested artifacts are corrected to ...
Forward compatibility for the older system usually means backward compatibility for the new system, i.e. the ability to process data from the old system; the new system usually has full compatibility with the older one, by being able to both process and generate data in the format of the older system.
Explicit methods calculate the state of a system at a later time from the state of the system at the current time, while implicit methods find a solution by solving an equation involving both the current state of the system and the later one.
The backward algorithm complements the forward algorithm by taking into account the future history if one wanted to improve the estimate for past times. This is referred to as smoothing and the forward/backward algorithm computes (|:) for < <. Thus, the full forward/backward algorithm takes into account all evidence.