Perceptions of ICT practitioners regarding software privacy

During software development activities, it is important for Information and Communication Technology (ICT) practitioners to know and understand practices and guidelines regarding information privacy, as software requirements must comply with data privacy laws and members of development teams should know current legislation related to the protection of personal data. In order to gain a better understanding on how industry ICT practitioners perceive the practical relevance of software privacy and privacy requirements and how these professionals are implementing data privacy concepts, we conducted a survey with ICT practitioners from software development organizations to get an overview of how these professionals are implementing data privacy concepts during software design. We performed a systematic literature review to identify related works with software privacy and privacy requirements and what methodologies and techniques are used to specify them. In addition, we conducted a survey with ICT practitioners from different organizations. Findings revealed that ICT practitioners lack a comprehensive knowledge of software privacy and privacy requirements and the Brazilian General Data Protection Law (Lei Geral de Proteção de Dados Pessoais, LGPD, in Portuguese), nor they are able to work with the laws and guidelines governing data privacy. Organizations are demanded to define an approach to contextualize ICT practitioners with the importance of knowledge of software privacy and privacy requirements, as well as to address them during software development, since LGPD must change the way teams work, as a number of features and controls regarding consent, documentation, and privacy accountability will be required

Information Aggregation in Exponential Family Markets

We consider the design of prediction market mechanisms known as automated market makers. We show that we can design these mechanisms via the mold of \emph{exponential family distributions}, a popular and well-studied probability distribution template used in statistics. We give a full development of this relationship and explore a range of benefits. We draw connections between the information aggregation of market prices and the belief aggregation of learning agents that rely on exponential family distributions. We develop a very natural analysis of the market behavior as well as the price equilibrium under the assumption that the traders exhibit risk aversion according to exponential utility. We also consider similar aspects under alternative models, such as when traders are budget constrained

Calculating risk change with management actions using Bayesian networks for the South River, Virginia, USA

Ecological managers often implement one or more management options to manage risk without the direct integration of a quantitative risk assessment and evaluation of management alternatives. Throughout the decision making process a manager should consider multiple stressors as well as stressor interactions and the resulting effects. In my study, I used Bayesian networks in a relative risk assessment model framework (BN-RRM) to integrate two management options into existing risk assessment models for biotic endpoints and water quality endpoints in the mercury contaminated site, South River, VA. The two management options assessed were agricultural best management practices (BMPs) and bank stabilization. The primary management goal expressed by managers is no regrets. In other words, managers do not want to make the site worse in any way, such as reducing mercury levels at the detriment of habitat, loss of other species, degradation of water quality, or other environmental parameters. The Bayesian networks represent the expected effects of a management option and the potential for unintended consequences. Agricultural BMPs did not change the skew of the risk distributions, but aligns with the no regrets management focus because risk did not increase. Bank stabilization management shifted the risk distribution for smallmouth bass so that there was greater likelihood of zero risk. The risk distribution for the water quality-fishing endpoint changed because likelihood of medium and high risk increased. If bank stabilization is implemented without consideration of Belted Kingfisher nests, there was 100% likelihood of high risk to the Kingfisher. My research provides South River managers with a tool that describes how management options are expected to change risk to biotic and water quality endpoints. Adaptive management for the South River is a long-term process. The BN-RRM models can be updated with new monitoring data to inform future management decisions

A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems

abstract: Text Classification is a rapidly evolving area of Data Mining while Requirements Engineering is a less-explored area of Software Engineering which deals the process of defining, documenting and maintaining a software system's requirements. When researchers decided to blend these two streams in, there was research on automating the process of classification of software requirements statements into categories easily comprehensible for developers for faster development and delivery, which till now was mostly done manually by software engineers - indeed a tedious job. However, most of the research was focused on classification of Non-functional requirements pertaining to intangible features such as security, reliability, quality and so on. It is indeed a challenging task to automatically classify functional requirements, those pertaining to how the system will function, especially those belonging to different and large enterprise systems. This requires exploitation of text mining capabilities. This thesis aims to investigate results of text classification applied on functional software requirements by creating a framework in R and making use of algorithms and techniques like k-nearest neighbors, support vector machine, and many others like boosting, bagging, maximum entropy, neural networks and random forests in an ensemble approach. The study was conducted by collecting and visualizing relevant enterprise data manually classified previously and subsequently used for training the model. Key components for training included frequency of terms in the documents and the level of cleanliness of data. The model was applied on test data and validated for analysis, by studying and comparing parameters like precision, recall and accuracy.Dissertation/ThesisMasters Thesis Engineering 201

User Story Extraction from Online News with FeatureBased and Maximum Entropy Method for Software Requirements Elicitation

Software requirements query is the frst stage in software requirements engineering. Elicitation is the process of identifying software requirements from various sources such as interviews with resource persons, questionnaires, document analysis, etc. The user story is easy to adapt according to changing system requirements. The user story is a semi-structured language because the compilation of user stories must follow the syntax as a standard for writing features in agile software development methods. In addition, user story also easily understood by end-users who do not have an information technology background because they contain descriptions of system requirements in natural language. In making user stories, there are three aspects, namely the who aspect (actor), what aspect (activity), and the why aspect (reason). This study proposes the extraction of user stories consisting of who and what aspects of online news sites using feature extraction and maximum entropy as a classifcation method. The systems analyst can use the actual information related to the lessons obtained in the online news to get the required software requirements. The expected result of the extraction method in this research is to produce user stories relevant to the software requirements to assist systems analysts in generating requirements. This proposed method shows that the average precision and recall are 98.21% and 95.16% for the who aspect; 87,14% and 87,50% for what aspects; 81.21% and 78.60% for user stories. Thus, this result suggests that the proposed method generates user stories relevant to functional software

Use of the TOPSIS technique to choose the best supplier of quarry natural aggregate

Purpose. All over the world, natural substance – the most consumed after water – is the aggregate. The aim of this paper is to select the best supplier of Quarry Natural Aggregate (QNA). Methods. Selection of the best supplier of QNA is performed using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, and the method of weights based on ordinal ranking of criteria, and Lagrange multiplier. Findings. In this article, the proposed Multi-Criteria Decision Making (MCDM) approach helps the decision maker(s) to choose the best supplier of QNA amongst the considered and evaluated suppliers. Originality. During negotiation with suppliers, many are the decision makers which only attach an importance at two criteria (unit price and quality, or unit price and delivery time). Thereby, other criteria are not taken into account. Consequently, supplier selection would become not-efficient. The originality of this work is based on the multi-criteria approach to choose the best supplier of QNA. Practical implications. The efficient choice of the best supplier of QNA represents a practical and economical value for the enterprises of the civil engineering, public works, railway and hydraulic works.Мета. Обґрунтування та вибір оптимального постачальника кар’єрного щебню як природного заповнювача на основі використання багатокритеріального методу. Методика. Вибір найкращого постачальника кар’єрного природного заповнювача здійснювався за допомогою багатокритеріального методу аналізу варіантів за ступенем близькості до оптимального (TOPSIS) і методу вагових коефіцієнтів на основі порядкового ранжирування критеріїв та множника Лагранжа. Результати. Підхід, що описується в статті, заснований на багатокритеріальному прийнятті рішень і дозволяє обрати кращого постачальника природного заповнювача серед наявних та розглянутих на ринку компаній. В якості ілюстрації запропонована методологія застосована до чисельного прикладу. Це дозволило визначити вагу впливових на оцінку критеріїв, оцінку значень характеристик кожного розглянутого постачальника QNA, встановлення рейтингу розглянутих постачальників QNA і вибір альтернативи {a4} в якості кращого постачальника QNA. Наукова новизна. Вперше для вибору оптимального постачальника природного заповнювача крім факторів ціни і якості встановлено характер впливу на загальну оцінку також ряду інших факторів: вартість транспортування, транспортна відстань, час доставки, гарантійна політика й рівень відхилення. У даній роботі вперше пропонується багатокритеріальний підхід до вибору оптимального постачальника природного заповнювача кар’єра. Практична значимість. Ефективний вибір постачальника природного заповнювача кар’єра важливий з практичної та економічної точок зору для підприємств у галузі цивільного будівництва, громадських робіт, залізниці та гідротехнічних споруд.Цель. Обоснование и выбор оптимального поставщика карьерного щебня как природного заполнителя на основе использования многокритериального метода. Методика. Выбор лучшего поставщика карьерного природного заполнителя осуществлялся с помощью многокритериального метода анализа вариантов по степени близости к оптимальному (TOPSIS) и метода весовых коэффициентов на основе порядкового ранжирования критериев и множителя Лагранжа. Результаты. Подход, описываемый в статье, основан на многокритериальном принятии решений и позволяет выбрать лучшего поставщика природного заполнителя среди имеющихся и рассматриваемых на рынке компаний. В качестве иллюстрации предложенная методология применена к числовому примеру. Это позволило определить вес влияющих на оценку критериев, оценку значений характеристик каждого рассматриваемого поставщика QNA, установление рейтинга рассматриваемых поставщиков QNA и выбор альтернативы {a4} в качестве лучшего поставщика QNA. Научная новизна. Впервые для выбора оптимального поставщика природного заполнителя кроме факторов цены и качества установлен характер влияния на общую оценку также ряда других факторов: стоимость транспортирования, транспортное расстояние, время доставки, гарантийная политика и уровень отклонения. В данной работе впервые предлагается многокритериальный подход к выбору оптимального поставщика природного заполнителя карьера. Практическая значимость. Эффективный выбор поставщика природного заполнителя карьера важен с практической и экономической точек зрения для предприятий в области гражданского строительства, общественных работ, железной дороги и гидротехнических сооружений.The authors thank all the colleagues which have contributed to the realization of this research work