The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Corey H Basch - One of the best experts on this subject based on the ideXlab platform.
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Readability of prostate cancer information online a cross sectional study
American Journal of Men's Health, 2018Co-Authors: Sarah Maclean, Danna Ethan, Joseph Fera, Phillip Garcia, Corey H BaschAbstract:Reading and understanding health information, both components of health literacy, can influence patient decisions related to disease management. Older adults, the population of males at greatest risk for prostate cancer, may have compromised capacity to understand and use health information. The purpose of this study was to determine the Readability of prostate cancer materials on the Internet using five recommended Readability tests. Using a cleared Internet browser, a search was conducted for “prostate cancer.” The URLs of the first 100 websites in English were recorded to create the sample. The Readability scores for each website were determined using an online, recommended service. This service generates five commonly recommended Readability tests. All five tests revealed that the majority of websites had difficult Readability. There were no significant differences identified between websites with .org, .gov, or .edu extension versus those with .com, .net, or other extension. It is apparent that the I...
Sofya Raskhodnikova - One of the best experts on this subject based on the ideXlab platform.
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Bipartite graphs of small Readability
Theoretical Computer Science, 2020Co-Authors: Rayan Chikhi, Vladan Jovicic, Stefan Kratsch, Paul Medvedev, Martin Milanič, Sofya Raskhodnikova, Nithin VarmaAbstract:We study a parameter of bipartite graphs called Readability, introduced by Chikhi et al. (Discrete Applied Mathematics 2016) and motivated by applications of overlap graphs in bioinformatics. The behavior of the parameter is poorly understood. The complexity of computing it is open and it is not known whether the decision version of the problem is in NP. The only known upper bound on the Readability of a bipartite graph (Braga and Meidanis, LATIN 2002) is exponential in the maximum degree of the graph. Graphs that arise in bioinformatic applications have low Readability. In this paper we focus on graph families with Readability o(n), where n is the number of vertices. We show that the Readability of n-vertex bipartite chain graphs is between \(\varOmega (\log n)\) and \(\mathcal {O}(\sqrt{n})\). We give an efficiently testable characterization of bipartite graphs of Readability at most 2 and completely determine the Readability of grids, showing in particular that their Readability never exceeds 3. As a consequence, we obtain a polynomial-time algorithm to determine the Readability of induced subgraphs of grids. One of the highlights of our techniques is the appearance of Euler’s totient function in the proof of the upper bound on the Readability of bipartite chain graphs. We also develop a new technique for proving lower bounds on Readability, which is applicable to dense graphs with a large number of distinct degrees.
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COCOON - Bipartite Graphs of Small Readability
Lecture Notes in Computer Science, 2018Co-Authors: Rayan Chikhi, Vladan Jovicic, Stefan Kratsch, Paul Medvedev, Martin Milanič, Sofya Raskhodnikova, Nithin VarmaAbstract:We study a parameter of bipartite graphs called Readability, introduced by Chikhi et al. (Discrete Applied Mathematics 2016) and motivated by applications of overlap graphs in bioinformatics. The behavior of the parameter is poorly understood. The complexity of computing it is open and it is not known whether the decision version of the problem is in NP. The only known upper bound on the Readability of a bipartite graph (Braga and Meidanis, LATIN 2002) is exponential in the maximum degree of the graph. Graphs that arise in bioinformatic applications have low Readability. In this paper we focus on graph families with Readability o(n), where n is the number of vertices. We show that the Readability of n-vertex bipartite chain graphs is between \(\varOmega (\log n)\) and \(\mathcal {O}(\sqrt{n})\). We give an efficiently testable characterization of bipartite graphs of Readability at most 2 and completely determine the Readability of grids, showing in particular that their Readability never exceeds 3. As a consequence, we obtain a polynomial-time algorithm to determine the Readability of induced subgraphs of grids. One of the highlights of our techniques is the appearance of Euler’s totient function in the proof of the upper bound on the Readability of bipartite chain graphs. We also develop a new technique for proving lower bounds on Readability, which is applicable to dense graphs with a large number of distinct degrees.
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Bipartite Graphs of Small Readability
arXiv: Discrete Mathematics, 2018Co-Authors: Rayan Chikhi, Vladan Jovicic, Stefan Kratsch, Paul Medvedev, Martin Milanič, Sofya Raskhodnikova, Nithin VarmaAbstract:We study a parameter of bipartite graphs called Readability, introduced by Chikhi et al. (Discrete Applied Mathematics, 2016) and motivated by applications of overlap graphs in bioinformatics. The behavior of the parameter is poorly understood. The complexity of computing it is open and it is not known whether the decision version of the problem is in NP. The only known upper bound on the Readability of a bipartite graph (following from a work of Braga and Meidanis, LATIN 2002) is exponential in the maximum degree of the graph. Graphs that arise in bioinformatic applications have low Readability. In this paper, we focus on graph families with Readability $o(n)$, where $n$ is the number of vertices. We show that the Readability of $n$-vertex bipartite chain graphs is between $\Omega(\log n)$ and $O(\sqrt{n})$. We give an efficiently testable characterization of bipartite graphs of Readability at most $2$ and completely determine the Readability of grids, showing in particular that their Readability never exceeds $3$. As a consequence, we obtain a polynomial time algorithm to determine the Readability of induced subgraphs of grids. One of the highlights of our techniques is the appearance of Euler's totient function in the analysis of the Readability of bipartite chain graphs. We also develop a new technique for proving lower bounds on Readability, which is applicable to dense graphs with a large number of distinct degrees.
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on the Readability of overlap digraphs
Discrete Applied Mathematics, 2016Co-Authors: Rayan Chikhi, Paul Medvedev, Martin Milanič, Sofya RaskhodnikovaAbstract:We introduce the graph parameter Readability and study it as a function of the number of vertices in a graph. Given a digraph D , an injective overlap labeling assigns a unique string to each vertex such that there is an arc from x to y if and only if x properly overlaps y . The Readability of D is the minimum string length for which an injective overlap labeling exists. In applications that utilize overlap digraphs (e.g.,?in bioinformatics), Readability reflects the length of the strings from which the overlap digraph is constructed. We study the asymptotic behavior of Readability by casting it in purely graph theoretic terms (without any reference to strings). We prove upper and lower bounds on Readability for certain graph families and general graphs.
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CPM - On the Readability of Overlap Digraphs
Combinatorial Pattern Matching, 2015Co-Authors: Rayan Chikhi, Paul Medvedev, Martin Milanič, Sofya RaskhodnikovaAbstract:We introduce the graph parameter Readability and study it as a function of the number of vertices in a graph. Given a digraph \(D\), an injective overlap labeling assigns a unique string to each vertex such that there is an arc from \(x\) to \(y\) if and only if \(x\) properly overlaps \(y\). The Readability of \(D\) is the minimum string length for which an injective overlap labeling exists. In applications that utilize overlap digraphs (e.g., in bioinformatics), Readability reflects the length of the strings from which the overlap digraph is constructed. We study the asymptotic behaviour of Readability by casting it in purely graph theoretic terms (without any reference to strings). We prove upper and lower bounds on Readability for certain graph families and general graphs.
Rayan Chikhi - One of the best experts on this subject based on the ideXlab platform.
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Bipartite graphs of small Readability
Theoretical Computer Science, 2020Co-Authors: Rayan Chikhi, Vladan Jovicic, Stefan Kratsch, Paul Medvedev, Martin Milanič, Sofya Raskhodnikova, Nithin VarmaAbstract:We study a parameter of bipartite graphs called Readability, introduced by Chikhi et al. (Discrete Applied Mathematics 2016) and motivated by applications of overlap graphs in bioinformatics. The behavior of the parameter is poorly understood. The complexity of computing it is open and it is not known whether the decision version of the problem is in NP. The only known upper bound on the Readability of a bipartite graph (Braga and Meidanis, LATIN 2002) is exponential in the maximum degree of the graph. Graphs that arise in bioinformatic applications have low Readability. In this paper we focus on graph families with Readability o(n), where n is the number of vertices. We show that the Readability of n-vertex bipartite chain graphs is between \(\varOmega (\log n)\) and \(\mathcal {O}(\sqrt{n})\). We give an efficiently testable characterization of bipartite graphs of Readability at most 2 and completely determine the Readability of grids, showing in particular that their Readability never exceeds 3. As a consequence, we obtain a polynomial-time algorithm to determine the Readability of induced subgraphs of grids. One of the highlights of our techniques is the appearance of Euler’s totient function in the proof of the upper bound on the Readability of bipartite chain graphs. We also develop a new technique for proving lower bounds on Readability, which is applicable to dense graphs with a large number of distinct degrees.
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COCOON - Bipartite Graphs of Small Readability
Lecture Notes in Computer Science, 2018Co-Authors: Rayan Chikhi, Vladan Jovicic, Stefan Kratsch, Paul Medvedev, Martin Milanič, Sofya Raskhodnikova, Nithin VarmaAbstract:We study a parameter of bipartite graphs called Readability, introduced by Chikhi et al. (Discrete Applied Mathematics 2016) and motivated by applications of overlap graphs in bioinformatics. The behavior of the parameter is poorly understood. The complexity of computing it is open and it is not known whether the decision version of the problem is in NP. The only known upper bound on the Readability of a bipartite graph (Braga and Meidanis, LATIN 2002) is exponential in the maximum degree of the graph. Graphs that arise in bioinformatic applications have low Readability. In this paper we focus on graph families with Readability o(n), where n is the number of vertices. We show that the Readability of n-vertex bipartite chain graphs is between \(\varOmega (\log n)\) and \(\mathcal {O}(\sqrt{n})\). We give an efficiently testable characterization of bipartite graphs of Readability at most 2 and completely determine the Readability of grids, showing in particular that their Readability never exceeds 3. As a consequence, we obtain a polynomial-time algorithm to determine the Readability of induced subgraphs of grids. One of the highlights of our techniques is the appearance of Euler’s totient function in the proof of the upper bound on the Readability of bipartite chain graphs. We also develop a new technique for proving lower bounds on Readability, which is applicable to dense graphs with a large number of distinct degrees.
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Bipartite Graphs of Small Readability
arXiv: Discrete Mathematics, 2018Co-Authors: Rayan Chikhi, Vladan Jovicic, Stefan Kratsch, Paul Medvedev, Martin Milanič, Sofya Raskhodnikova, Nithin VarmaAbstract:We study a parameter of bipartite graphs called Readability, introduced by Chikhi et al. (Discrete Applied Mathematics, 2016) and motivated by applications of overlap graphs in bioinformatics. The behavior of the parameter is poorly understood. The complexity of computing it is open and it is not known whether the decision version of the problem is in NP. The only known upper bound on the Readability of a bipartite graph (following from a work of Braga and Meidanis, LATIN 2002) is exponential in the maximum degree of the graph. Graphs that arise in bioinformatic applications have low Readability. In this paper, we focus on graph families with Readability $o(n)$, where $n$ is the number of vertices. We show that the Readability of $n$-vertex bipartite chain graphs is between $\Omega(\log n)$ and $O(\sqrt{n})$. We give an efficiently testable characterization of bipartite graphs of Readability at most $2$ and completely determine the Readability of grids, showing in particular that their Readability never exceeds $3$. As a consequence, we obtain a polynomial time algorithm to determine the Readability of induced subgraphs of grids. One of the highlights of our techniques is the appearance of Euler's totient function in the analysis of the Readability of bipartite chain graphs. We also develop a new technique for proving lower bounds on Readability, which is applicable to dense graphs with a large number of distinct degrees.
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on the Readability of overlap digraphs
Discrete Applied Mathematics, 2016Co-Authors: Rayan Chikhi, Paul Medvedev, Martin Milanič, Sofya RaskhodnikovaAbstract:We introduce the graph parameter Readability and study it as a function of the number of vertices in a graph. Given a digraph D , an injective overlap labeling assigns a unique string to each vertex such that there is an arc from x to y if and only if x properly overlaps y . The Readability of D is the minimum string length for which an injective overlap labeling exists. In applications that utilize overlap digraphs (e.g.,?in bioinformatics), Readability reflects the length of the strings from which the overlap digraph is constructed. We study the asymptotic behavior of Readability by casting it in purely graph theoretic terms (without any reference to strings). We prove upper and lower bounds on Readability for certain graph families and general graphs.
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CPM - On the Readability of Overlap Digraphs
Combinatorial Pattern Matching, 2015Co-Authors: Rayan Chikhi, Paul Medvedev, Martin Milanič, Sofya RaskhodnikovaAbstract:We introduce the graph parameter Readability and study it as a function of the number of vertices in a graph. Given a digraph \(D\), an injective overlap labeling assigns a unique string to each vertex such that there is an arc from \(x\) to \(y\) if and only if \(x\) properly overlaps \(y\). The Readability of \(D\) is the minimum string length for which an injective overlap labeling exists. In applications that utilize overlap digraphs (e.g., in bioinformatics), Readability reflects the length of the strings from which the overlap digraph is constructed. We study the asymptotic behaviour of Readability by casting it in purely graph theoretic terms (without any reference to strings). We prove upper and lower bounds on Readability for certain graph families and general graphs.
Westley Weimer - One of the best experts on this subject based on the ideXlab platform.
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Learning a Metric for Code Readability
IEEE Transactions on Software Engineering, 2010Co-Authors: Raymond P L Buse, Westley WeimerAbstract:In this paper, we explore the concept of code Readability and investigate its relation to software quality. With data collected from 120 human annotators, we derive associations between a simple set of local code features and human notions of Readability. Using those features, we construct an automated Readability measure and show that it can be 80 percent effective and better than a human, on average, at predicting Readability judgments. Furthermore, we show that this metric correlates strongly with three measures of software quality: code changes, automated defect reports, and defect log messages. We measure these correlations on over 2.2 million lines of code, as well as longitudinally, over many releases of selected projects. Finally, we discuss the implications of this study on programming language design and engineering practice. For example, our data suggest that comments, in and of themselves, are less important than simple blank lines to local judgments of Readability.
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a metric for software Readability
International Symposium on Software Testing and Analysis, 2008Co-Authors: Raymond P L Buse, Westley WeimerAbstract:In this paper, we explore the concept of code Readability and investigate its relation to software quality. With data collected from human annotators, we derive associations between a simple set of local code features and human notions of Readability. Using those features, we construct an automated Readability measure and show that it can be 80% effective, and better than a human on average, at predicting Readability judgments. Furthermore, we show that this metric correlates strongly with two traditional measures of software quality, code changes and defect reports. Finally, we discuss the implications of this study on programming language design and engineering practice. For example, our data suggests that comments, in of themselves, are less important than simple blank lines to local judgments of Readability.
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ISSTA - A metric for software Readability
Proceedings of the 2008 international symposium on Software testing and analysis - ISSTA '08, 2008Co-Authors: Raymond P L Buse, Westley WeimerAbstract:In this paper, we explore the concept of code Readability and investigate its relation to software quality. With data collected from human annotators, we derive associations between a simple set of local code features and human notions of Readability. Using those features, we construct an automated Readability measure and show that it can be 80% effective, and better than a human on average, at predicting Readability judgments. Furthermore, we show that this metric correlates strongly with two traditional measures of software quality, code changes and defect reports. Finally, we discuss the implications of this study on programming language design and engineering practice. For example, our data suggests that comments, in of themselves, are less important than simple blank lines to local judgments of Readability.
Rocco Oliveto - One of the best experts on this subject based on the ideXlab platform.
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Improving code Readability models with textual features
2016 IEEE 24th International Conference on Program Comprehension (ICPC), 2016Co-Authors: Simone Scalabrino, Mario Linares-vásquez, Denys Poshyvanyk, Rocco OlivetoAbstract:Code reading is one of the most frequent activities in software maintenance; before implementing changes, it is necessary to fully understand source code often written by other developers. Thus, Readability is a crucial aspect of source code that may significantly influence program comprehension effort. In general, models used to estimate software Readability take into account only structural aspects of source code, e.g., line length and a number of comments. However, source code is a particular form of text; therefore, a code Readability model should not ignore the textual aspects of source code encapsulated in identifiers and comments. In this paper, we propose a set of textual features aimed at measuring code Readability. We evaluated the proposed textual features on 600 code snippets manually evaluated (in terms of Readability) by 5K+ people. The results demonstrate that the proposed features complement classic structural features when predicting code Readability judgments. Consequently, a code Readability model based on a richer set of features, including the ones proposed in this paper, achieves a significantly higher accuracy as compared to all of the state-of-the-art Readability models.
