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Software Development Management: Empirical and Analytical Perspectives Having awareness, experience, and understanding of the actions required, students are more likely to apply such principles under real-life constraints in their working life. Furthermore, we give examples that show how empirical studies contribute to high-quality learning outcomes, to student motivation, and to the awareness of the advantages of applying software engineering principles.

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We give examples illustrating how to utilize empirical studies, discuss challenges, and derive an initial guideline that supports teachers to include empirical studies in software engineering courses. In this paper, we show how different types of empirical studies can be used for educational purposes in software engineering. A way to experience such effects and to increase the relevance of software engineering education is to apply empirical studies in teaching.

Real-life software development often deals with large, software-intensive systems and is influenced by the complex effects of teamwork and distributed software development, which are hard to demonstrate in an educational environment.

Industry training has similar requirements of relevance as companies seek to keep their workforce up to date with technological advances. Educators must address issues beyond exercises and theories that can be directly rehearsed in small settings. Guidelines for using empirical studies in software engineering educationĭirectory of Open Access Journals (Sweden)įull Text Available Software engineering education is under constant pressure to provide students with industry-relevant knowledge and skills. Current work presents the results of a study carried out on a Portuguese medium-sized software development organization in order to obtain a formal method for EPMs elicitation in development processes. Particularly, missing data is a widespread phenomenon observed during the elaboration of effort prediction models (EPMs) required for budget, time and functionalities planning. Missing values is a common problem in the data analysis in all areas, being software engineering not an exception. OLGA FEDOTOVA GLADYS CASTILLO LEONOR TEIXEIRA HELENA ALVELOS SOFTWARE EFFORT PREDICTION: AN EMPIRICAL EVALUATION OF METHODS TO TREAT MISSING VALUES WITH RAPIDMINER ® The paper outlines the general course setup, topics addressed, and it provides initial lessons learned. an extra specific expertise that they offer as service to other teams, thus, fostering cross-team collaboration. In this paper, we present a Master-level course on empirical software engineering in which different empirical instruments. Yet, empirical software engineering increases this difficulty by adding the scientific method as extra dimension. is crucial, software engineering is considered hard to teach. Due to the involvement of humans and the multitude of fields for which software. Teaching Empirical Software Engineering Using Expert TeamsĮmpirical software engineering aims at making software engineering claims measurable, i.e., to analyze and understand phenomena in software engineering and to evaluate software engineering approaches and solutions.