Investigation of the Sharkskin melt instability using optical Fourier analysis

in Journal of Applied Polymer Science (2019), 137(24), 48806

An optical method allowing the characterization of melt flow instabilities typically occurring during an extrusion process of polymers and polymer compounds is presented. It is based on a camera‐acquired ... [more ▼]

An optical method allowing the characterization of melt flow instabilities typically occurring during an extrusion process of polymers and polymer compounds is presented. It is based on a camera‐acquired image of the extruded compound with a reference length scale. Application of image processing and transformation of the calibrated image to the frequency domain yields the magnitude spectrum of the instability. The effectiveness of the before mentioned approach is shown on Styrene‐butadiene rubber (SBR) compounds, covering a wide range of silica filler content, extruded through a Göttfert capillary rheometer. The results of the image‐based analysis are compared with the results from the sharkskin option, a series of highly sensitive pressure transducers installed inside the rheometer. A simplified version of the code used to produce the optical analysis results is included as supplementary material. [less ▲]

A Coordinated Europeanization of the Comics Industry through Distribution: The Politics of the Global Journey of Astérix and Tintin through the Strategic Distribution of their Magazines and Contents in the 1960s

in On_Culture: The Open Journal for the Study of Culture (2019), 8(Winter),

Researchers have usually focused on the Tintin and Astérix series’ global book diffusion through translation. However, little has been discussed about the distribution policies of the comics magazine ... [more ▼]

Researchers have usually focused on the Tintin and Astérix series’ global book diffusion through translation. However, little has been discussed about the distribution policies of the comics magazine format, a key factor in the development of European comics. This paper will consider the continentalization of western European national comics industries via the intra-EEC networking of distribution channels during the 1960s. By facilitating the exchange of comics features in the Franco-Belgian area, publishers such as Casterman, Le Lombard, and Dargaud ensured the rise of the industry and of the products they wanted to disseminate. Contemplating the motivations of publishers this article will delve deeper into the emergence of cooperative and competitive distribution channels among national publishers and between countries. Through the archives of Casterman and primary sources this article intends to contribute to a greater understanding of how the carefully planned distribution network of comics influenced the development of the European industry as a whole. [less ▲]

Écrire (dans la langue de) l’autre. Italies du départ, Italies de l’accueil

Poster (2019, December 19)

Inter-regional innovation cooperation and structural heterogeneity:Does being a rural, or border region, or both, make a difference?

in Journal of Rural Studies (2019)

This paper analyses the determinants of inter-regional innovation cooperation in European knowledge networks. Our main goal is to assess whether structural heterogeneity in the context of the “urban ... [more ▼]

This paper analyses the determinants of inter-regional innovation cooperation in European knowledge networks. Our main goal is to assess whether structural heterogeneity in the context of the “urban-rural dichotomy†and international borders can explain differences in the regions’ engagement in inter-regional innovation coopera-tion. We estimate a gravity equation to model innovation cooperation, proxied by inter-regional co-patent ap-plications, as a function of region-specific context conditions as well as technological and geographical distance. Our data comprise dyadic information on 203 NUTS2 regions in 15 European countries (EU-15) for the year 2010. The empirical results show that the basic gravity mechanisms drive the direction and strength of in-novation cooperation between EU regions; i.e., geographical distance acts as an impediment to inter-regional co-patent applications. Regarding the importance of structural heterogeneity, we find that pairs of rural regions have lower levels of innovation cooperation compared to urban regions. Similarly, border regions are generally disadvantaged compared to non-border regions in terms of the intensity of innovation cooperation. However, while the latter result points to a negative border effect, our gravity model estimates also show that pairs of border regions are more active in terms of close geographical innovation cooperation (e.g., through international cross-border cooperation), which partly compensates for the negative border effect. This finding not only holds for urban but also rural border regions and may reflect policy attempts to support border regions, e.g., by strengthening the level of international cross-border cooperation within the EU. [less ▲]

Review of Clara Rauchegger and Anna Wallerman (eds.) The Eurosceptic Challenge: National Implementation and Interpretation of EU Law (Hart 2019)

in European Law Blog (2019)

Book review published on European Law Blog

Deep Pattern Mining for Program Repair

Doctoral thesis (2019)

Error-free software is a myth. Debugging thus accounts for a significant portion of software maintenance and absorbs a large part of software cost. In particular, the manual task of fixing bugs is tedious ... [more ▼]

Error-free software is a myth. Debugging thus accounts for a significant portion of software maintenance and absorbs a large part of software cost. In particular, the manual task of fixing bugs is tedious, error- prone and time-consuming. In the last decade, automatic bug-fixing, also referred to as automated program repair (APR) has boomed as a promising endeavor of software engineering towards alleviating developers’ burden. Several potentially promising techniques have been proposed making APR an increasingly prominent topic in both the research and practice communities. In production, APR will drastically reduce time-to-fix delays and limit downtime. In a development cycle, APR can help suggest changes to accelerate debugging. As an emergent domain, however, program repair has many open problems that the community is still exploring. Our work contributes to this momentum on two angles: the repair of programs for functionality bugs, and the repair of programs for method naming issues. The thesis starts with highlighting findings on key empirical studies that we have performed to inform future repair approaches. Then, we focus on template-based program repair scenarios and explore deep learning models for inferring accurate and relevant patterns. Finally, we integrate these patterns into APR pipelines, which yield the state of the art repair tools. The dissertation includes the following contributions: • Real-world Patch Study: Existing APR studies have shown that the state-of-the-art techniques in automated repair tend to generate patches only for a small number of bugs even with quality issues (e.g., incorrect behavior and nonsensical changes). To improve APR techniques, the community should deepen its knowledge on repair actions from real-world patches since most of the techniques rely on patches written by human developers. However, previous investigations on real-world patches are limited to statement level that is not sufficiently fine-grained to build this knowledge. This dissertation starts with deepening this knowledge via a systematic and fine-grained study of real-world Java program bug fixes. • Fault Localization Impact: Existing test-suite-based APR systems are highly dependent on the performance of the fault localization (FL) technique that is the process of the widely studied APR pipeline. However, APR systems generally focus on the patch generation, but tend to use similar but different strategies for fault localization. To assess the impact of FL on APR, we identify and investigate a practical bias caused by the FL step in a repair pipeline. We propose to highlight the different FL configurations used in the literature, and their impact on APR systems when applied to the real bugs. Then, we explore the performance variations that can be achieved by “tweaking” the FL step. • Fix Pattern Mining: Fix patterns (a.k.a. fix templates) have been studied in various APR scenarios. Particularly, fix patterns have been widely used in different APR systems. To date, fix pattern mining is mainly studied in three ways: manually summarization, transformation inferring and code change action statistics. In this dissertation, we explore mining fix patterns for static bugs leveraging deep learning and clustering algorithms. • Avatar: Fix pattern based patch generation is a promising direction in the APR community. Notably, it has been demonstrated to produce more acceptable and correct patches than the patches obtained with mutation operators through genetic programming. The performance of fix pattern based APR systems, however, depends on the fix ingredients mined from commit changes in development histories. Unfortunately, collecting a reliable set of bug fixes in repositories can be challenging. We propose to investigate the possibility in an APR scenario of leveraging code changes that address violations by static bug detection tools. To that end, we build the Avatar APR system, which exploits fix patterns of static analysis violations as ingredients for patch generation. • TBar: Fix patterns are widely used in patch generation of APR, however, the repair performance of a single fix pattern is not studied. We revisit the performance of template-based APR to build comprehensive knowledge about the effectiveness of fix patterns, and to highlight the importance of complementary steps such as fault localization or donor code retrieval. To that end, we first investigate the literature to collect, summarize and label recurrently-used fix patterns. Based on the investigation, we build TBar, a straightforward APR tool that systematically attempts to apply these fix patterns to program bugs. We thoroughly evaluate TBar on the Defects4J benchmark. In particular, we assess the actual qualitative and quantitative diversity of fix patterns, as well as their effectiveness in yielding plausible or correct patches. • Debugging Method Names: Except the issues about semantic/static bugs in programs, we note that how to debug inconsistent method names automatically is important to improve program quality. In this dissertation, we propose a deep learning based approach to spotting and refactoring inconsistent method names in programs. [less ▲]

Selecting fault revealing mutants

in Empirical Software Engineering (2019)

Mutant selection refers to the problem of choosing, among a large number of mutants, the (few) ones that should be used by the testers. In view of this, we investigate the problem of selecting the fault ... [more ▼]

Mutant selection refers to the problem of choosing, among a large number of mutants, the (few) ones that should be used by the testers. In view of this, we investigate the problem of selecting the fault revealing mutants, i.e., the mutants that are killable and lead to test cases that uncover unknown program faults. We formulate two variants of this problem: the fault revealing mutant selection and the fault revealing mutant prioritization. We argue and show that these problems can be tackled through a set of ‘static’ program features and propose a machine learning approach, named FaRM, that learns to select and rank killable and fault revealing mutants. Experimental results involving 1,692 real faults show the practical benefits of our approach in both examined problems. Our results show that FaRM achieves a good trade-off between application cost and effectiveness (measured in terms of faults revealed). We also show that FaRM outperforms all the existing mutant selection methods, i.e., the random mutant sampling, the selective mutation and defect prediction (mutating the code areas pointed by defect prediction). In particular, our results show that with respect to mutant selection, our approach reveals 23% to 34% more faults than any of the baseline methods, while, with respect to mutant prioritization, it achieves higher average percentage of revealed faults with a median difference between 4% and 9% (from the random mutant orderings). [less ▲]

European urban forests: landscape typology of urban forest ecosystem services

Presentation (2019, December 17)

A Review of RFI Mitigation Techniques in Microwave Radiometry

in Remote Sensing (2019), 11(24), 3042

Radio frequency interference (RFI) is a well-known problem in microwave radiometry (MWR). Any undesired signal overlapping the MWR protected frequency bands introduces a bias in the measurements, which ... [more ▼]

Radio frequency interference (RFI) is a well-known problem in microwave radiometry (MWR). Any undesired signal overlapping the MWR protected frequency bands introduces a bias in the measurements, which can corrupt the retrieved geophysical parameters. This paper presents a literature review of RFI detection and mitigation techniques for microwave radiometry from space. The reviewed techniques are divided between real aperture and aperture synthesis. A discussion and assessment of the application of RFI mitigation techniques is presented for each type of radiometer. [less ▲]

Silent Cold War: International Tourism and East-West Commodity Exchanges in Socialist Romania of the 1960s-1980s

Presentation (2019, December 16)