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2. On automata and language based grammar metricsMatej Črepinšek, Tomaž Kosar, Marjan Mernik, Julien Cervelle, Rémi Forax, Gilles Roussel, 2010, original scientific article Abstract: Grammar metrics have been introduced to measure the quality and the complexity of the formal grammars. The aim of this paper is to explore the meaning of these notions and to experiment, on several grammars of domain specific languages and of general-purpose languages, existing grammar metrics together with the new metrics that are based on grammar LR automaton and on the language recognized. We discuss the results of this experiment and focus on the comparison between grammars of domain specific languages as well as of general-purpose languages and on the evolution of the metrics between several versions of the same language.
Keywords: grammar metrics, software language engineering, grammar engineering, grammarware
Published in DKUM: 06.07.2017; Views: 1543; Downloads: 429
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3. A programming language independent framework for metrics-based software evolution and analysisČrt Gerlec, Gordana Rakić, Zoran Budimac, Marjan Heričko, 2012, original scientific article Abstract: 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.]
Keywords: software evolution, software development, quality, structure, metrics
Published in DKUM: 06.07.2017; Views: 2128; Downloads: 381
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4. METRICS-BASED RECOMMENDATION SYSTEM FOR SOFTWARE ENGINEERINGMarko Gašparič, 2013, master's thesis Abstract: This thesis presents the state-of-the-art of recommendation systems for software engineering. The systematic literature review and the survey of authors of analyzed publications showed that the most successful characteristics of the systems are a modular architecture, that is not distributed, and a reactive behavior. Existing RSSEs are mostly standalone solutions or Eclipse plugins.
When developers study their own activities they improve their estimating and planning skills and reduce the number of defects in their work. We developed a prototype that is an Eclipse plugin and visualizes an overall team effort spent per source code artifact, source code metrics, and recommendations for source code improvements.
To evaluate the prototype we conducted nine interviews. Interviews showed that users find the functionalities of our system useful and would also like to get more information, particularly about an effort per developer. Additionally, interviews revealed that developers are willing to execute a non-repetitive task to use the system, while they are not willing to leave the development environment to obtain the same information and recommendations.
Keywords: recommendation system, software engineering, metrics
Published in DKUM: 05.09.2013; Views: 2102; Downloads: 183
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