A general combination approach is proposed to address the predictive accuracy problem for software reliability modeling. Instead of relying on any single model, the authors apply several linear combinations of existing software reliability models, called component models, to form a series of linear-combination models. In an experimental investigation with industrial project data, this set of linear combination models was judged to perform better than the component models. For the purpose of automating the procedures in applying existing software reliability models and the linear-combination models, the authors further suggest a computer-aided software engineering tool, called CASRE, to measure software reliability systematically. A discussion is presented of the ideas, approaches, and experimental results of the combination models, as well as the high-level design, structure, and functionality of the CASRE tool. >
['Michael R. Lyu', 'Allen P. Nikora']
Software reliability measurements through combination models: approaches, results, and a CASE tool