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Mutation testing is widely considered as a high-end test criterion due to the vast number of mutants it generates. Although many efforts have been made to reduce the computational cost of mutation testing, its scalability issue remains in practice. In this paper, we introduce a novel method to speed up mutation testing based on state infection information. In addition to filtering out uninfected test...
Regular expressions (regexes) permit to describe set of strings using a pattern-based syntax. Writing a correct regex that exactly captures the desired set of strings is difficult, also because a regex is seldom syntactically incorrect, and so it is rare to detect faults at parse time. We propose a fault-based approach for generating tests for regexes. We identify fault classes representing possible...
In this paper we define the average coding rate of a variable-to-fixed length (VF) lossless source code as the expectation of the pointwise coding rate, which is called average pointwise coding rate. It has been shown that the Tunstall code is asymptotically optimal under the criterion optimizing the average pointwise coding rate. In this paper, we propose a new VF code attaining optimal average pointwise...
In this extended abstract we develop a technique to extend any bound for cyclic codes constructed from its defining sets (ds-bounds) to abelian (or multivariate) codes. We use this technique to improve the searching of new bounds for abelian codes.
Information Retrieval (IR) identifies trace links based on textual similarities among software artifacts. However, the vocabulary mismatch problem between different artifacts hinders the performance of IR-based approaches. A growing body of work addresses this issue by combining IR techniques with code dependency analysis such as method calls. However, so far the performance of combined approaches...
Congestion is a major problem for the data-processing Ethernet Networks, because it causes data loss and application failure in consequence. To this end, this kind of network needs to be suitably controlled in order to guarantee good performances. IEEE 802.1Qau standard is in progress to find an efficient congestion control mechanism, which may ensure a properly use of the available resources and...
Privacy is an important issue that has raised particular concerns among many research areas. This issue dramatically increases with the proliferation of the Web services composition paradigm. This is mainly due to the high dynamism and untrustworthiness characteristics of the services to be composed, which impose high levels of risk on the interacting parties. Existing technologies for managing and...
Energy-aware software is self-adaptive in nature which dynamically changes its behaviour to save energy. Context information plays a major role in developing such self-adaptive and energy-aware software. Any changes in context information may exhibit different number of operating conditions at run-time. The software should be efficiently developed to be more energy-efficient under different operating...
Platforms for publishing research papers are increasing largely that contribute to big data as their volume is humongous and are unstandardized. Classification of this huge chunk of data is one of the biggest challenges in Information Retrieval. In this paper we discuss a scoring based unsupervised learning approach to extract relevant features and classify the research papers according to their content...
The search for Trendsetters in social networks turned to be a complex research topic that has gained much attention. The work here presented uses big data analytics to find who better spreads the word in a social network and is innovative in their choices. The analysis on the Yelp platform can be divided in three parts: first, we justify the use of Tips frequency as a variable to profile business...
Frequent sequence mining methods often make use of constraints to control which subsequences should be mined, e.g., length, gap, span, regular-expression, and hierarchy constraints. We show that many subsequence constraints—including and beyond those considered in the literature—can be unified in a single framework. In more detail, we propose a set of simple and intuitive "pattern expressions"...
Advances in social networking and communication technologies have witnessed an increasing number of applications where data is not only characterized by rich content information, but also connected with complex relationships representing social roles and dependencies between individuals. To enable knowledge discovery from such networked data, network representation learning (NRL) aims to learn vector...
This paper focuses on the identification of overlapping communities, allowing nodes to simultaneously belong to several communities, in a decentralised way. To that aim it proposes LOCNeSs, an algorithm specially designed to run in a decentralised environment and to limit propagation, two essential characteristics to be applied in mobile networks. It is based on the exploitation of the preferential...
Information-Centric Networking (ICN) has emerged as a promising way for the efficient content delivery over the Internet, and it can be seen as a super large-scale caching distributed system. However, as one of the most important problems, the cache consistency issue, which refers to whether cached contents in routers are outdated, is still not investigated thoroughly in ICN. Thus, in this paper,...
Real-life systems involving interacting objects are typically modeled as graphs and can often grow very large in size. Revealing the community structure of such systems is crucial in helping us better understand their complex nature. However, the ever-increasing size of real-world graphs, and our evolving perception of what a community is, make the task of community detection very challenging. One...
Lifelong learning models are popularly used with big data analysis as it learns better with the volume and variety of data. The model learns independently through an augmented learning mechanism that does not require manual support. Learning wrong and irrelevant rules are expected as it follows an unsupervised approach and therefore, the model is supported with a filtering mechanism. The rules that...
Decision makers tend to define their optimization problems as multi-objective optimization problems. Generating the whole nondominated set is often unrealistic due to its size but also because most of these points are irrelevant to the decision maker. Another approach consists in obtaining preference information and integrating it a priori, in order to reduce the size of the nondominated set and have...
An increasing number of attacks use advanced tactics, techniques and methods to compromise target systems and environments. Such multi-step attacks are often able to bypass existing prevention and detection systems, such as Intrusion Detection Systems (IDSs), firewalls and anti-virus solutions. These security systems either use an anomaly-based or a signature-based detection approach. For systems...
This article reviews the state of archival science where basic concepts have been subject to a long stream of criticisms without satisfactory resolution of the issues identified. It establishes a ground for progress by articulating criteria for evaluating archival concepts and proposes a path forward by enriching archival science with concepts and methods from systemic functional linguistics and graph...
Short text stream classification is a challengingand significant task due to the characteristics of short length, weak signal, high velocity and especially topic drifting in short text stream. However, this challenge has received little attention from the research community. Motivated by this, we propose a new feature extension approach for short text stream classification using a large scale, general...
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