AN Improvement of software faults’ residual density continuous predicting with bayesian net and value tree

O.O. Slabospickaya

Abstract


An actual problem of Software quality increasing through its faults reducing is considered. Software process is improved with a new process of software residual faults’ density (FD) unified predicting/assessing over the software life cycle (SLC) accordingly to the requirements being stated to him. The model and the methods for the above process are elaborated that overlap limitations of an individual FD predicting (early in SLC) with group FD assessing (later in SLC). The formalized rationale for choosing among FD estimates and their acceptance analyzing is attached to them. These estimates’ consistency continuous increase is accomplished. The premises of prediction/assessment efficiency increase over SLC are created.

Problems in programming 2009; 3: 50-58


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