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Effort estimation is an important activity in agile software development. The goal of the presented study was to determine the influence of individual competence on software development effort estimation. In particular, we measured both the accuracy of effort estimation and the duration of the estimation process itself, both for three different estimation methods. The subjects of our study were teams of students of a graduate‐level software engineering course at the University of Ljubljana, Faculty of Computer and Information Science. Based on the grades that individual students attained in their undergraduate study, we classified each team as "high‐competence" or "low‐competence" and additionally as "heterogeneous" or "homogeneous" (the criterion here being the variance of the members' average grades). We found out that there was no significant difference in effort estimation accuracy neither between high‐competence and low‐competence teams nor between heterogeneous and homogeneous teams, regardless of which estimation method was used. However, high‐competence teams spent significantly less time on effort estimation than low‐competence ones. Likewise, for two of the employed estimation methods, heterogeneous teams completed effort estimation in a significantly shorter time than homogeneous teams. These results might benefit both academic and professional community. [ABSTRACT FROM AUTHOR]

Published studies on agile effort estimation predominantly focus on comparisons of the accuracy of different estimation methods, while efficiency comparisons, i.e. how much time the estimation methods consume was not in the forefront. However, for practical use in software development, the time required can be a very important cost factor for enterprises, especially when the accuracy of different agile effort estimations is similar. In this study, we thus try to advance the current standard accuracy comparison between methods by introducing efficiency, i.e. time it takes to use a method as an additional dimension of comparison. We conduct this comparison between three agile effort estimation methods that were not yet compared in the literature, namely, Planning Poker, Bucket System and Affinity Estimation. For the comparison, we used eight student teams with 29 students who had to use all the effort estimation methods during the course where they had to finish a programming project in 3 weeks. The results indicate that after the students get used to using the different methods the accuracy between them is not statistically significantly different, however, the efficiency is. On average, Bucket System and Affinity Estimation methods take half as much time as Planning Poker. [ABSTRACT FROM AUTHOR]

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In this paper, we present a method to convert a metamodel in the form of a UML class diagram into a context-sensitive graph grammar whose language comprises precisely the set of model graphs (UML object diagrams) that conform to the input metamodel. Compared to other approaches that deal with the same problem, we use a graph grammar formalism that does not employ any advanced graph grammar features, such as application conditions, precedence rules, and production schemes. Specifically, we use Rekers and Schürr's Layered Graph Grammars, which may be regarded as a pure generalization of standard context-sensitive string grammars. We show that elementary grammatical features, i.e., grammar labels and context-sensitive graph rewrite rules, suffice to represent metamodels with arbitrary multiplicities and inheritance. Inspired by attribute string grammars, we also propose a graph-grammar-based approach to the semantic analysis of model graphs. [ABSTRACT FROM AUTHOR]

Introduction: Rising antibiotic resistance has become an increasing public health problem. There is a well-established correlation between antibiotic consumption and antimicrobial resistance. Consequently, measures to rationalize the prescribing of antibiotics should reduce the resistant strains. Following a 24% increase in antibiotic consumption at the end of the 1990s, multiple activities were designed and introduced by the Health Insurance Institute of Slovenia (ZZZS) and other organizations in Slovenia at the end of 1999. These activities reduced the antibiotic consumption by 18.7% by 2002. These measures have continued. Objective: To study changes in antibiotic utilization from 1995 to 2012 alongside the multiple interventions and their consequences, including changes in resistance patterns. Methods: This was a retrospective observational study involving all patients dispensed at least one ZZZS prescription for an antibiotic in Slovenia. Utilization was expressed in defined daily doses per thousand inhabitants per day. Multifaceted interventions were conducted over time involving all key stakeholder groups, that is, the Ministry of Health, ZZZS, physician groups and patients. These included comprehensive communication programs as well as prescribing restrictions for a number of antibiotics and classes. Results: From 1999 to 2012, antibiotic consumption decreased by 2-9% per year, with an overall decrease of 31%. There were also appreciable structural changes. Overall antibiotic utilization and the utilization of 7 out of 10 antibiotics significantly decreased after multiple interventions. The resistance of Streptococcus pneumoniae to penicillin decreased in line with decreased utilization. However, its resistance to macrolides increased from 5.4 to 21% despite halving of its utilization. The resistance of Escherichia coli to fluoroquinolones doubled from 10 to 21% despite utilization decreasing by a third. Expenditures on antibiotics decreased by 53%. Conclusion: Multiple demand-side measures introduced following increased utilization significantly decreased subsequent antibiotic utilization and associated costs. However, there was variable impact on antibiotic resistance. Additional targeted activities are planned to further reduce antibiotic prescribing and resistance. [ABSTRACT FROM AUTHOR]

Copyright of Electrotechnical Review / Elektrotehniski Vestnik is the property of Electrotechnical Society of Slovenia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We introduce a new equivalence on graphs, defined by its symmetry-breaking capability. We first present a framework for various backtracking search algorithms, in which the equivalence is used to prune the search tree. Subsequently, we define the equivalence and an optimization problem with the goal of finding an equivalence partition with the highest pruning potential. We also position the optimization problem into the computational-complexity hierarchy. In particular, we show that the verifier lies between P and NP -complete problems. Striving for a practical usability of the approach, we devise a heuristic method for general graphs and optimal algorithms for trees and cycles. [ABSTRACT FROM AUTHOR]