Knowledge about different aspects of software quality during software evolution can be valuable information for developers and project managers. It helps to reduce the number of defects and improves the internal structure of software. However, determining softwarećs quality and structure in heterogeneous systems is a difficult task. In this paper, a programming language independent framework for evaluating software metrics and analyzing software structure during software development and its evolution will be presented. The framework consists of the SMIILE tool for calculation of software metrics, extended with an analysis of software structure. The data are stored in a central repository via enriched Concrete Syntax Tree (eCST) for universal source code representation. The framework is demonstrated in a case study. The development of such a framework is a step forward to consistent support for software evolution by providing a change analysis and quality control. The significance of this consistency is growing today, when software projects are more complex, consisting of components developed in diverse programming languages.[Acknowledgments. Work of the second and third author is partially supported by the Serbian Ministry of Science and Technological Development through project no. OI174023 ĆIntelligent Techniquesand Their Integration into Wide-Spectrum Decision SupportĆ. Bilateral project between Slovenian Research Agency and Serbian Ministry of Science and Technological Development (Grant BI-SR/10-11-027) enabled the exchange of visits and ideas between authors of this paper and their institutions.

Software organizations are always looking for approaches that help improve the quality and productivity of developed software products. Quality software is easy to maintain and reduces the cost of software development. The Software Factories (SF) approach is one of the approaches to provide such benefits. In this paper, the quality and productivity benefits of the SF approach were examined and evaluated with an experiment involving two treatments - the traditional and the SF approach. For the purposes of this experiment, the Goal – Question – Metric (GQM) approach was used. Participants were grouped into thirty two teams. There were sixteen projects available. The results were evaluated and presented through quality and productivity criteria, which were used for the experimental study. The results showed that the Software Factories approach was significantly better than the traditional approach

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