The two most popular classification tree algorithms in machine learning and statistics - C4.5 and CART - are compared in a benchmark experiment together with two other more recent constant-fit tree learners from the statistics literature (QUEST, conditional inference trees). The study assesses both misclassification error and model complexity on bootstrap replications of 18 different benchmark datasets. It is carried out in the R system for statistical computing, made possible by means of the RWeka package which interfaces R to the open-source machine learning toolbox Weka. Both algorithms are found to be competitive in terms of misclassification error - with the performance difference clearly varying across data sets. However, C4.5 tends to grow larger and thus more complex trees. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Today there is a heavy integration of information technology in almost every aspect of our lives and there is an increase in computer security that goes with it. To ensure this security, and that policies and procedures within an organisations related to this security are enforced; security audits are conducted. At the same time, use of open source software is also becoming increasingly common, becoming more a fact of life rather than an option. With these two trends in mind, this study analyses a selection of scientific literature on the topic and identifies the unique challenges a security audit in an open source environment faces, and aims to contribute on how to help alleviate the challenges. The study was performed in the form of a literature review, where the comparison and analysis revealed interesting information regarding the open source specific challenges, including both technical issues as well as challenges stemming from people’s perception and handling of open source software today. The answer to the question “What are the challenges when conducting security audits for open source systems and how can they be alleviated?” shows the main challenges to be too much trust is put in unverified binaries. The report offers suggestions and ideas on how to implement solutions in order to help diminish this challenge through the use and integration of Reproducible Builds, answering the second part of the question.

Pro potřebu kontroly kvality kódu v Javě lze jednak využít funkce vývojového prostředí, ale také i samostatné programy, které kvalitu kódu hlídají - analyzéry kódu. Ty lze použít v podobě pluginů pro vývojová prostředí. V této práci jsem se primárně zaměřoval na vývojová prostředí NetBeans a Eclipse a jejich podporu pro různé analyzéry kódu (FindBugs, PMD, atd.) z oblasti open source. Práce se zabývá analýzou kontroly kvality ve vývojových prostředích a analyzérech kódu.

Práce se zabývá problematikou objektově-relačních databázových systémů. Cílem je analýza současné situace na poli databázových platforem ze sféry tradičních robustních i open source produktů, která by vedla k posouzení předpokladů uplatnění otevřených databázových platforem v oblastech dosud charakteristických především pro tradiční distributory. Na počátku práce nejprve přibližuji čtenáři otázky související s distribucí softwaru (proprietární vs. open source) a základní pojmy v oboru databázových systémů. Po tomto výchozím uvedení stanovuji kriteria pro následnou komparaci vybraných databázových platforem, která předurčují další postup v rozhodující části věnované komparační analýze. K dovršení celého rozboru práci uzavírám nastíněním přítomných možností využití tradičních robustních a především pak open source databázových systémů. Komparační analýza je vystavena na základě předem definovaných kritérií do pěti oddílů zohledňujících základní charakteristiky, technologické a funkční vlastnosti, bezpečnost, dostupnost i podporu produktů a nevěnuje se rozboru z hlediska výkonu a optimalizace. Za účelem srovnání byly vybrány čtyři přední databázové systémy ? Oracle, DB2, Teradata a PostgreSQL. V návaznosti na důkladnou analýzu, která vedla ke zmapování aktuální situace na databázovém trhu, jsou v závěru práce vytknuty hlavní faktory kolidující širšímu uplatnění open source platforem.

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores - Major de Telecomunicações. Faculdade de Engenharia. Universidade do Porto. 2008

Estágio realizado na PT Inovação / Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 2008

Estágio realizado na Critical Links, S. A. e orientado por Nuno Ferreira / Tese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 2008

Tese de mestrado. Redes e Serviços de comunicação. Faculdade de Engenharia. Universidade do Porto. 2008

Tese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 2008

Programming is a valuable skill in the labor market, making the underrepresentation of women in computing an increasingly important issue. Online question and answer platforms serve a dual purpose in this field: they form a body of knowledge useful as a reference and learning tool, and they provide opportunities for individuals to demonstrate credible, verifi- able expertise. Issues, such as male-oriented site design or overrepresentation of men among the site's elite may therefore compound the issue of women's underrepresentation in IT. In this paper we audit the differences in behavior and outcomes between men and women on Stack Overflow, the most popular of these Q&A sites. We observe significant differences in how men and women participate in the platform and how successful they are. For example, the average woman has roughly half of the reputation points, the primary measure of success on the site, of the average man. Using an Oaxaca-Blinder decomposition, an econometric technique commonly applied to analyze differences in wages between groups, we find that most of the gap in success between men and women can be explained by differences in their activity on the site and differences in how these activities are rewarded. Specifically, 1) men give more answers than women and 2) are rewarded more for their answers on aver age, even when controlling for possible confounders such as tenure or buy-in to the site. Women ask more questions and gain more reward per question. We conclude with a hypo thetical redesign of the site's scoring system based on these behavioral differences, cutting the reputation gap in half.