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As a result of the importance of academic collaboration at smart conferences, various researchers have utilized recommender systems to generate effective recommendations for participants. Recent research has shown that the personality traits of users can be used as innovative entities for effective recommendations. Nevertheless, subjective perceptions involving the personality of participants at smart...
Background: Test quality is a prerequisite for achieving production system quality. While the concept of quality is multidimensional, most of the effort in testing context hasbeen channelled towards measuring test effectiveness. Objective: While effectiveness of tests is certainly important, we aim to identify a core list of testing principles that also address other quality facets of testing, and...
Traceability Link Recovery (TLR) is a fundamental software maintenance task in which links are established between related software artifacts of different types (e.g., source code, documentation, requirements specifications, etc.) within a system. Existing approaches to TLR often require a human to analyze a long list of potential links and distinguish valid links from invalid ones. Here we present...
Security is still the main obstacle that is preventing businesses from moving towards the Cloud, which makes choosing the right Cloud service provider CSP a critical decision. We propose in this paper a methodology for evaluation and selection of Cloud security services based on a Multi-Criteria Analysis (MCA) process using a set of evaluation criteria and quantitative metrics. We then give a general...
In order to generate effective results, it is essential for a recommender system to model the information about the user interests (user profiles). A profile usually contains preferences that reflect the recommendation technique, so collaborative systems represent a user with the ratings given to items, while content-based approaches assign a score to semantic/text-based features of the evaluated...
Considering metrics based on finite directed graph, introduced by Etzion and Firer, we characterize the graphs such that every linear code admits a G-canonical decomposition. This decomposition will play an important role in this work, since it will be the main tool to give a sufficient condition for a finite directed graph to satisfy both the MacWilliams Identity and the MacWilliams Extension Property.
In batch systems monitoring information at the level of individual jobs is crucial to optimize resource utilization and prevent misusage. However, especially the usage of network resources is difficult to track. In order to understand usage patterns in modern computing clusters, a more detailed monitoring than existent solutions is required. A monitoring on job level leads to dynamic graphs of processes...
Estimation of data veracity is recognized as one of the grand challenges of big data. Typically, the goal of truth discovery is to determine the veracity of multi-source, conflicting data and return, as outputs, a veracity label and a confidence score for each data value, along with the trustworthiness score of each source claiming it. Although a plethora of methods has been proposed, it is unlikely...
Code obfuscation techniques are widely used in industry to increase protection of source code and intellectual property. The idea is that even if attackers gain hold of source code, it will be hard for them to understand what it does and how. Thus obfuscation techniques are specifically targeted at human comprehension of code. We suggest that the ideas and experience embedded in obfuscations can be...
A Network of Teams (NoT) is a set of overlapping teams working toward a common goal. NoTs arise in several contexts such as large software projects, sensors cooperating for target tracking, and terrorist cell networks. Modeling a NoT as a simplicial complex, we consider the problem of quantifying the strength of a NoT using metrics based purely on its structure. While the design of a metric clearly...
The MapReduce paradigm has become ubiquitous within Big Data Analytics. Within this field, Social Networks exist as an important area of applications as it relies on the large scale analysis of graphs. To enable the scalability of Social Networks, we consider the application of MapReduce design patterns for the determination of graph-based metrics. Specifically, we detail the application of a MapReduce-based...
Aligning software-related activities with corporate strategies and goals is increasingly important for several reasons such as increasing the customer satisfaction in software-based products and services. Several approaches have been proposed to create such an alignment. GQM+Strategies is an approach that applies measurement principles to link goals and strategies on different levels of an organisation...
Traditional text categorization methods only deal with the content of the documents and use some statistic based metrics to represent the documents. The representation is then used by a machine learning approach to determine the document class. In this picture, the meaning of the document is missing. In order to add meaning into the text categorization process, we start with using part-of-speech tagging...
Bloat, and particularly object churn, is a common performance problem in framework-intensive applications. Object churn consists of an excessive use of temporary objects. Identifying and understanding sources of churn is a difficult and labor-intensive task, despite recent advances in automated analysis techniques. We present an interactive visualization approach designed to help developers quickly...
The multiplication of large-scale document collections has created the need for robust and adaptive access strategies in many applicative areas. In this paper, we depart from the traditional document search paradigm to move onto the construction of a collection navigation strategy. We thus detail a model where user clicks are taken as expression of interest rather than positive search feedback. In...
We address the relation between persuasion and virality in social networks and provide preliminary findings based on a Digg dataset. In particular we want to understand whether a content categorized as persuasive (according to various metrics) can be categorized as viral as well. Results show that the persuasive properties of a content are related to its virality in different ways. These findings...
In this paper we discuss that the specific consistency and latency requirements of world state updates in Massively Multi-User Virtual Environments (MMVEs) are determined by several characteristic factors of the virtual world, i.e. their Interaction Context. As this context is highly application-dependent, MMVE developers require a simple specification scheme which allows them to specify these requirements...
A new algorithm is proposed to detect small objects by background suppression. It relies on a modified version of the nonlocal means filter introduced by Buades et al. for background prediction. Background pixels are estimated by a weighted average depending on the similarity between neighborhoods pixels. For background suppression, the similarity criterion is modified to be less sensitive to point...
Identifiers are an important source of information during program understanding and maintenance. Programmers often use identifiers to build their mental models of the software artifacts. We have performed a preliminary study to examine the relation between the terms in identifiers, their spread in entities, and fault proneness. We introduced term entropy and context-coverage to measure how scattered...
Poorly-chosen identifiers have been reported in the literature as misleading and increasing the program comprehension effort. Identifiers are composed of terms, which can be dictionary words, acronyms, contractions, or simple strings. We conjecture that the use of identical terms in different contexts may increase the risk of faults. We investigate our conjecture using a measure combining term entropy...
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