Generation Of Diagrams Research Articles

ADG: automated generation and evaluation of many-body diagrams

The goal of the present paper is twofold. First, a novel expansion many-body method applicable to superfluid open-shell nuclei, the so-called Bogoliubov in-medium similarity renormalization group (BIMSRG) theory, is formulated. This generalization of standard single-reference IMSRG theory for closed-shell systems parallels the recent extensions of coupled cluster, self-consistent Green’s function or many-body perturbation theory. Within the realm of IMSRG theories, BIMSRG provides an interesting alternative to the already existing multi-reference IMSRG (MR-IMSRG) method applicable to open-shell nuclei. The algebraic equations for low-order approximations, i.e., BIMSRG(1) and BIMSRG(2), can be derived manually without much difficulty. However, such a methodology becomes already impractical and error prone for the derivation of the BIMSRG(3) equations, which are eventually needed to reach high accuracy. Based on a diagrammatic formulation of BIMSRG theory, the second objective of the present paper is thus to describe the third version (v3.0) of the ADG code that automatically (1) generates all valid BIMSRG(n) diagrams and (2) evaluates their algebraic expressions in a matter of seconds. This is achieved in such a way that equations can easily be retrieved for both the flow equation and the Magnus expansion formulations of BIMSRG. Expanding on this work, the first future objective is to numerically implement BIMSRG(2) (eventually BIMSRG(3)) equations and perform ab initio calculations of mid-mass open-shell nuclei.

Development of Licorice Flavonoids Loaded Microemulsion for Transdermal Delivery Using CCD-Optimal Experimental Approach: Formulation Development and Characterization

In this research, we sought to surmount the poor dissolvability and transdermal absorption rate of licorice flavonoids (LFs) by fabricating a LFs microemulsion. LFs content was determined using high performance liquid chromatography. Initial studies such as dissolution testing, emulsification testing, and pseudo ternary phase diagram generation were implemented for screening components and optimized adopting the central composite design. While the tested responses were solubility, droplet size and PDI, thirteen trials were performed using two different variables, oil percentage and optimized emulsifier and co-emulsifier ratio. Microemulsions were then characterized for droplet size, PDI, transmission electron microscopy, viscosity, electrical conductivity, pH, entrapment efficiency, drug content and stability. Additionally, skin release profile, percutaneous absorption and retention were investigated adopting Franz diffusion cell. The optimal formulation was found to compose of laureth-9 (emulsifier, 6.72 g), propylene glycol (co-emulsifier, 1.80 g), isopropyl myristate (IPM, oil, 1.48 g), LFs (1.50 g) and at least more than 85% deionized water. The optimized and storage for 3 months of microemulsion was found to clear, light yellow color without phase separation or precipitation indicated the stability of the preparation to long-term placement. The mean droplet size, PDI, entrapment efficiency and drug content were discovered as 12.68 ± 0.12 nm, 0.049 ± 0.005, 97.28 ± 0.13% and 122.67 ± 0.40 mg·g−1, respectively. Furthermore, the optimal formulation sustained release LFs, remarkably deliver more LFs through the skin layer (644.95 ± 6.73 μg cm−2) and significantly retained LFs in the skin layer (9.98 μg cm−2). The study concluded that optimized microemulsion has potential and enhanced the dissolvability and cumulative penetration amount of LFs.

Charge Transfer at the Hetero‐Interface of WSe2/InSe Induces Efficient Doping to Achieve Multi‐Functional Lateral Homo‐Junctions

AbstractCharge transfer at the hetero‐interface is at the center of van der Waals (vdWs) heterostructure devices for multi‐functional applications. Compared with the extensively investigated photogenerated carrier transfer driven by the built‐in electric field from the conduction or valence band offset, the charge transfer due to the Fermi level difference of the two adjacent constitutes, and its influence on the opto‐/electronic performance of vdWs heterostructure devices are not clarified. Herein, by taking an example of WSe2/InSe heterostructure, it is demonstrated that the charge transfer at the hetero‐interface is an efficient “doping” strategy to dramatically modulate the carrier densities of atomically thin counterparts due to the extension of “band bending” across the entire heterostructure, paving the way for the creation of lateral WSe2 p‐n and n‐n+ homo‐junctions with multi‐functionalities, including promising rectification, photovoltaic, and photodetection abilities. Moreover, the device physics of lateral homo‐junctions, including potential distribution, band diagram, and photocurrent generation mechanisms, is revealed by gate‐dependent Kelvin probe force microscopy and scanning photocurrent measurements. This work not only provides a general avenue to build 2D lateral homo‐junctions, but also give deeper insights into the device physics of the junctions by coupling scanning probe and scanning photocurrent techniques.

2DProts: database of family-wide protein secondary structure diagrams.

SummarySecondary structures provide a deep insight into the protein architecture. They can serve for comparison between individual protein family members. The most straightforward way how to deal with protein secondary structure is its visualization using 2D diagrams. Several software tools for the generation of 2D diagrams were developed. Unfortunately, they create 2D diagrams based on only a single protein. Therefore, 2D diagrams of two proteins from one family markedly differ. For this reason, we developed the 2DProts database, which contains secondary structure 2D diagrams for all domains from the CATH and all proteins from PDB databases. These 2D diagrams are generated based on a whole protein family, and they also consider information about the 3D arrangement of secondary structure elements. Moreover, 2DProts database contains multiple 2D diagrams, which provide an overview of a whole protein family's secondary structures. 2DProts is updated weekly and is integrated into CATH.Availability and ImplementationFreely accessible at https://2dprots.ncbr.muni.cz. The web interface was implemented in JavaScript. The database was implemented in Python.Supplementary information Supplementary data are available at Bioinformatics online.

Generation of interaction diagrams of pad-reinforced and non-padded vessel/nozzle structures via employing various plastic collapse techniques

The present research investigates the effect of pad reinforcement on the load-carrying capacities of a thin-walled pressurized cylindrical vessel with a radial nozzle structure. The main objective is to generate the plastic collapse moment boundaries versus a spectrum of steady internal pressures employing various criteria, namely the Plastic Work Curvature (PWC) and the Plastic Work (PW) criteria in addition to the Twice-Elastic-Slope (TES) Method. Initially, a validation study is conducted utilizing the finite element method to determine the out-of-plane (OP) plastic collapse moments utilizing the TES Method concerning two experimentally tested pad-reinforced vessel/nozzle structures. The validation study revealed very good outcomes. A non-padded vessel/nozzle is also analyzed for comparison purposes. The pad reinforcement enormously enhanced both the in-plane and the OP load-carrying capacities. The TES Method displayed a noticeable deficiency in determining the plastic collapse moments for the non-padded structure concerning the late medium to the high internal pressure spectra.

Generation of unstructured meshes using Delaunay triangles for tidal analysis of the port of Acapulco, Mexico

The main objective of the research is to suggest the use of unstructured meshes in the SWAN wave model because structured meshes require more adjustments in geographically small areas such as rivers, beaches or even bays. Third-party tools and data such as bathymetry, Meteorological Research Forecast (WRF), WaveWatch III (WWIII) and Simulating Waves Nearshore (SWAN) models were used to carry out the research. The aforementioned software and its own developments were used in Acapulco Bay, Guerrero, Mexico for the elaboration of maps that would serve as input in the generation of Delaunay diagrams, which in turn were fundamental parts in the configuration of the experiments and, with this, perform the analysis on the images of the simulations. With the results obtained, it is expected to confirm the validity of the wave data for the bay; therefore, it is considered a useful tool in the process of analysing the natural phenomena present in the port.

Effects of renal denervation on the expression profile of circular RNA in the serum of patients with resistant hypertension

ObjectiveRenal denervation (RDN) is a new treatment option for resistant hypertension (RH), although it has been shown that reduced sympathetic nerve activity after RDN is the main cause of blood pressure decline. In view of the possible correlation between circRNA and hypertension and the metabolic state of the body after RDN, we investigated the potential role of circRNA in RDN treatment of RH. MethodsSerum samples of patients with RH were collected before and 48 h after RDN. We explored the mechanism underlying RDN with high-throughput integration of circRNA data. ResultsThere were 338 circRNAs that were differentiated before and after RDN; 170 were upregulated and 168 were downregulated (≥1.2-fold, P < 0.05), and the expression of five of them changed significantly (≥1.5-fold, P < 0.05). We used reverse transcription-quantitative polymerase chain reaction to confirm these results in 13 other patients with RH. hsa_circRNA_000367 was upregulated and hsa_circRNA_405119 was downregulated after RDN. We predicted their downstream miRNA–mRNA network and analyzed their putative function via the circRNA–miRNA–mRNA pathway. GO/KEGG analysis showed that their functional annotation may be related to nerve injury and hypertension. We used the Venn Diagram Generator to obtain the intersection of predicted target and sympathetic nerve-related genes (from GeneCards website). ConclusionThe mechanism underlying RDN may be closely related to upregulated hsa_circRNA_000367 or downregulated hsa_circRNA_405119 and involve regulated multiple pathways and multiple cellular and molecular biological processes. These circRNAs may potentially be used as treatment effect biomarkers in RDN.

Restricted Power Diagrams on the GPU

AbstractWe propose a method to simultaneously decompose a 3D object into power diagram cells and to integrate given functions in each of the obtained simple regions. We offer a novel, highly parallel algorithm that lends itself to an efficient GPU implementation. It is optimized for algorithms that need to compute many decompositions, for instance, centroidal Voronoi tesselation algorithms and incompressible fluid dynamics simulations.We propose an efficient solution that directly evaluates the integrals over every cell without computing the power diagram explicitly and without intersecting it with a tetrahedralization of the domain. Most computations are performed on the fly, without storing the power diagram. We manipulate a triangulation of the boundary of the domain (instead of tetrahedralizing the domain) to speed up the process. Moreover, the cells are treated independently one from another, making it possible to trivially scale up on a parallel architecture.Despite recent Voronoi diagram generation methods optimized for the GPU, computing integrals over restricted power diagrams still poses significant challenges; the restriction to a complex simulation domain is difficult and likely to be slow. It is not trivial to determine when a cell of a power diagram is completely computed, and the resulting integrals (e.g. the weighted Laplacian operator matrix) do not fit into fast (shared) GPU memory. We address all these issues and boost the performance of the state‐of‐the‐art algorithms by a factor 2 to 3 for (unrestricted) Voronoi diagrams and a ×50 speed‐up with respect to CPU implementations for restricted power diagrams. An essential ingredient to achieve this is our new scheduling strategy that allows us to treat each Voronoi/power diagram cell with optimal settings and to benefit from the fast memory.

Venn diagrams in bioinformatics

Venn diagrams are widely used tools for graphical depiction of the unions, intersections and distinctions among multiple datasets, and a large number of programs have been developed to generate Venn diagrams for applications in various research areas. However, a comprehensive review comparing these tools has not been previously performed. In this review, we collect Venn diagram generators (i.e. tools for visualizing the relationships of input lists within a Venn diagram) and Venn diagram application tools (i.e. tools for analyzing the relationships between biological data and visualizing them in a Venn diagram) to compare their functional capacity as follows: ability to generate high-quality diagrams; maximum datasets handled by each program; input data formats; output diagram styles and image output formats. We also evaluate the picture beautification parameters of the Venn diagram generators in terms of the graphical layout and briefly describe the functional characteristics of the most popular Venn diagram application tools. Finally, we discuss the challenges in improving Venn diagram application tools and provide a perspective on Venn diagram applications in bioinformatics. Our aim is to assist users in selecting suitable tools for analyzing and visualizing user-defined datasets.

Annotated functional decomposition

AbstractExperiences gained from the domain‐specific courses showed that students focus mostly on how to implement solutions and less on what must be considered within the solution. In the case of information systems‐related courses, students focus on system development using specific languages and frameworks while often disregard the required logical checks and constraints. This paper introduces annotated functional decomposition (AFD) to assist students in overcoming the challenge of understanding the logic of an information system. AFD leverages methodological concepts from computational thinking and represents a problem decomposition approach that is extended with additional levels of decomposition. These levels of decomposition are orthogonal and implemented with annotations that enrich a decomposition with information regarding control and data flow, as well as reuse and implementation details. AFD could be exercised with a supporting AFD Tool developed as an Eclipse IDE plugin that performs syntax and semantic checks along with the generation of UML sequential diagrams. The AFD Tool and its source code are available free of charge. Quantitative and qualitative evaluations of AFD Tool usage during an information systems course revealed that students who used AFD achieved higher average grades than those who used UML for solving the same problems, and moreover that students perceived AFD as easy to understand and use.

Visualizing UML’s Sequence and Class Diagrams Using Graph-Based Clusters

The paper discusses the creation of UML diagram based recommendation system using java and class files as the input. The existing systems do not make use of techniques available in text-mining for creating UML diagrams. The overall methodology makes use of keyphrase extraction, contextual similarity calculation, and graph-based clusters in creating UML diagrams. The existing systems survey of state-of-art UML diagram generation techniques and keyphrase extraction survey is also provided. A comparative analysis of the existing tools for generating UML-diagrams is also provided. The recommendation system generated is useful to maintenance engineers and software developers.

Automatic Feynman diagram generation for nonlinear optical spectroscopies and application to fifth-order spectroscopy with pulse overlaps.

Perturbative nonlinear optical spectroscopies are powerful methods to understand the dynamics of excitonic and other condensed phase systems. Feynman diagrams have long provided the essential tool to understand and interpret experimental spectra and to organize the calculation of spectra for model systems. When optical pulses are strictly time ordered, only a small number of diagrams contribute, but in many experiments, pulse-overlap effects are important for interpreting results. When pulses overlap, the number of contributing diagrams can increase rapidly, especially with higher order spectroscopies, and human error is especially likely when attempting to write down all the diagrams. We present an automated Diagram Generator (DG) that generates all the Feynman diagrams needed to calculate any nth-order spectroscopic signal. We characterize all perturbative nonlinear spectroscopies by their associated phase-discrimination condition as well as the time intervals where pulse amplitudes are nonzero. Although the DG can be used to automate impulsive calculations, its greatest strength lies in automating finite pulse calculations where pulse overlaps are important. We consider third-order transient absorption spectroscopy and fifth-order exciton-exciton interaction 2D (EEI2D) spectroscopy, which are described by six or seven diagrams in the impulsive limit, respectively, but 16 or 240 diagrams, respectively, when pulses overlap. The DG allows users to automatically include all relevant diagrams at a relatively low computational cost, since the extra diagrams are only generated for the inter-pulse delays where they are relevant. For EEI2D spectroscopy, we show the important effects of including the overlap diagrams.

Геопространственное веб-приложение для поддержки исследований изменения климата Казахстана

Climate change modelling data is represented by large datasets that require certain expertise and computational resources for its transformation and adjustment to user needs. Geospatial web applications and geoportals are considered as a solution to this problem in this article. Global web resources do not provide geoinformation services for research on climate change in Kazakhstan due to aggregation or low resolution of the source data coupled with limited functionality for interactive geo-visualization and data analysis. The article describes the web application “Kazakhstan Climate Change” developed by the authors, the purpose of which is aimed at supporting research on spatial-temporal patterns of climate change in Kazakhstan. The data derived from CMIP5 models served as the source data. Based on the initial indicators such as temperature and precipitation, using the developed Python scripts and R Climpact climate script packages, additional indicators such as evapotranspiration, drought indices, heat supply indices and indices of the length of the growing season were calculated in order to determine the impact of climate change on water resources and agriculture. The key advantages of the web application include time-series geo-visualization, interactive generation of diagrams and tables for analysis, in particular for selected units of water management zoning. The geospatial web application “Kazakhstan Climate Change” responds to the challenges of presenting large climate datasets in the easy-to-perceive style and in an easily comprehensible way for geospatial analysis. The functionality of the web application allows users, without GIS skills, to explore climate change scenarios on their own, this opportunity is of practical value for scientific and educational community, for policymakers in the field of climate change and water resources management.

Finding the Next Superhard Material through Ensemble Learning.

An ensemble machine-learning method is demonstrated to be capable of finding superhard materials by directly predicting the load-dependent Vickers hardness based only on the chemical composition. A total of 1062 experimentally measured load-dependent Vickers hardness data are extracted from the literature and used to train a supervised machine-learning algorithm utilizing boosting, achieving excellent accuracy (R2 = 0.97). This new model is then tested by synthesizing and measuring the load-dependent hardness of several unreported disilicides and analyzing the predicted hardness of several classic superhard materials. The trained ensemble method is then employed to screen for superhard materials by examining more than 66 000 compounds in crystal structure databases, which show that 68 known materials have a Vickers hardness ≥40 GPa at 0.5 N (applied force) and only 10 exceed this mark at 5 N. The hardness model is then combined with the data-driven phase diagram generation tool to expand the limited number of reported high hardness compounds. Eleven ternary borocarbide phase spaces are studied, and more than ten thermodynamically favorable compositions with a hardness above 40 GPa (at 0.5 N) are identified, proving this ensemble model's ability to find previously unknown materials with outstanding mechanicalproperties.

ADG: Automated generation and evaluation of many-body diagrams II. Particle-number projected Bogoliubov many-body perturbation theory

We describe the second version (v2.0.0) of the code ADG that automatically (1) generates all valid off-diagonal Bogoliubov many-body perturbation theory diagrams at play in particle-number projected Bogoliubov many-body perturbation theory (PNP-BMBPT) and (2) evaluates their algebraic expression to be implemented for numerical applications. This is achieved at any perturbative order p for a Hamiltonian containing both two-body (four-legs) and three-body (six-legs) interactions (vertices). All valid off-diagonal BMBPT diagrams of order p are systematically generated from the set of diagonal, i.e.,unprojected, BMBPT diagrams. The production of the latter were described at length in Arthuis et al. (2019) dealing with the first version of ADG. The automated evaluation of off-diagonal BMBPT diagrams relies both on the application of algebraic Feynman’s rules and on the identification of a powerful diagrammatic rule providing the result of the remaining p-tuple time integral. The new diagrammatic rule generalizes the one already identified in Arthuis et al. (2019) to evaluate diagonal BMBPT diagrams independently of their perturbative order and topology. The code ADG is written in Python3 and uses the graph manipulation package NetworkX. The code is kept flexible enough to be further expanded throughout the years to tackle the diagrammatics at play in various many-body formalisms that already exist or are yet to be formulated. Program summaryProgram Title:ADGCPC Library link to program files:https://doi.org/10.17632/6h4xrydwfb.2Licensing provisions: GPLv3Programming language: Python3Journal reference of previous version: P. Arthuis, T. Duguet, A. Tichai, R.-D. Lasseri and J.-P. Ebran, ”ADG: Automated generation and evaluation of many-body diagrams I. Bogoliubov many-body perturbation theory”, Computer Physics Communications 240 (2019), pp. 202-227.Does the new version supersede the previous version?: Yes.Reasons for the new version: Incorporation of a new formalism into the program.Summary of revisions: Addition of off-diagonal BMBPT to the formalisms for which diagrams can be generated, fix of a wrong symmetry factor, move of the codebase from Python2 to Python3 while maintaining support for Python2, various optimizations to reduce the time and memory necessary to the program.Nature of problem: As formal and numerical developments in many-body-perturbation-theory-based ab initio methods make higher orders reachable, manually producing and evaluating all the diagrams becomes rapidly untractable as both their number and complexity grow quickly, making it prone to mistakes and oversights.Solution method: Diagonal BMBPT diagrams are encoded as square matrices known as oriented adjacency matrices in graph theory, and then turned into graph objects using the NetworkX package. Off-diagonal BMBPT diagrams can then be generated from those graphs. Checks on the diagrams and evaluation of their time-integrated expression are eventually done on a purely diagrammatic basis. HF-MBPT diagrams are produced and evaluated as well using the same principle.

A universal approach to ratcheting problems of bree type incorporating arbitrary loading and material nonlinearity conditions

A universal solution procedure has been developed for solving a wide range of thermal ratcheting problems beyond those covered by Bree Diagram or modified Bree Diagrams. Both thermal and pressure cyclic loading histories considered can be in-phase or out-of-phase with a prescribed phase shift. Material strain hardening behavior is modeled through a modified Ramberg-Osgood stress-strain relationship which can recover the elastic-perfect-plastic material response as an idealized case considered originally by Bree. The universal procedure is made possible through a unified analytical treatment of the associated thermoplasticity phenomena in an incremental form. In addition to elucidating some specific mechanics aspects of ratcheting phenomena under realistic loading and material hardening conditions of interest, the procedure can be used to automate the Bree Diagram generation process under conditions beyond those available to design engineers today. Validations are performed by comparing with brute force finite element solutions for selected thermal ratcheting problems and recovering the original and modified Bree Diagrams used by Codes and Standards currently used by the pressure equipment industry. One key finding is that by considering strain hardening effects, Bree diagram actually “evolves”, primarily in the form of an expanded “shakedown” region, as cyclic thermal and pressure loading continues until a limiting condition is reached. This suggests that existing ratcheting design criteria can be overly conservative.

Generation of hazard relation diagrams: formalization and tool support

Developing safety-critical, software-intensive embedded systems are characterized by the need to identify hazards and to define hazard-mitigating requirements at the earliest possible stage of development, i.e., during requirements engineering. These hazard-mitigating requirements must be adequate in the sense that they must specify the functionality required by the stakeholders in addition to rendering the system sufficiently safe during operation. The adequacy of hazard-mitigating requirements is determined during requirements validation. Yet, the validation of the adequacy of hazard-mitigating requirements is burdened by the fact that hazards and contextual information about hazards are a work product of safety assessment, and hazard-mitigating requirements are a work product of requirements engineering. These work products are poorly integrated such that during validation, the information needed to determine the adequacy of hazard-mitigating requirements is not available to stakeholders. In consequence, there is the risk that inadequate hazard-mitigating requirements remain covert and the system is falsely considered safe. To alleviate this issue, we have previously proposed (Tenbergen et al., in: Proceedings of the 21st international working conference on requirements engineering: foundation for software quality, pp 17–32, 2015), improved, and evaluated (Tenbergen et al. in Requir Eng J 23(2):291–329, 2018. https://doi.org/10.1007/s00766-017-0267-9 ) a novel diagram type called “Hazard Relation Diagrams.” In this paper, we present a semiautomated formal approach and tool support for their generation. We make use of a running example to illustrate the concepts.

A machine learning approach to estimation of phase diagrams for three-component lipid mixtures

The plasma membrane of eukaryotic cells is commonly believed to contain ordered lipid domains. The interest in understanding the origin of such domains has led to extensive studies on the phase behavior of mixed lipid systems. Three-component phase diagrams, composed of a high melting temperature (Tm) lipid, cholesterol, and a low Tm lipid have been valuable in studying lipid phase behavior. However, developing phase diagrams over the entire composition space and with precise tie-lines requires significant experimental effort. In this study, a machine learning approach was used to predict the Tm of lipids and generate phase diagrams from lipid mixtures. First, artificial neural network (ANN) was used for the prediction of Tm. The network was trained using available Tm data and was able to generate Tm values that closely matched literature results for its testing dataset. This model was then used to predict the Tm for lipids that have not yet been experimentally tested. Then, random forests (RF) and support vector machines (SVM) were trained and tested for their ability to predict a test three-component phase diagram. The model from the RF algorithm was able to generate a diagram that closely matched published results. This model was then used to generate phase diagrams for lipid mixtures at various temperatures and various degrees of unsaturation. This machine learning approach to the generation of lipid phase diagrams has the potential to save significant time and resources in studies of lipid phase behavior.

Modulation classification in the presence of adjacent channel interference using convolutional neural networks

SummaryThis paper investigates a vital issue in wireless communication systems, which is the modulation classification. A proposed framework for modulation classification based on deep learning (DL) is presented in the presence of adjacent channel interference (ACI). This framework begins with the generation of constellation diagrams from the received data. These constellation diagrams are fed to convolutional neural networks (CNNs) for modulation classification. The objective of this process is to eliminate the manual feature extraction from the received data and make feature extraction process as a built‐in step with CNNs. Three types of CNNs are considered in this paper and compared for this objective. These types are AlexNet, VGG‐16, and VGG‐19. The proposed classifier is applied on Rayliegh and Rician fading channels.

Static generation of UML sequence diagrams

UML sequence diagrams are visual representations of object interactions in a system and can provide valuable information for program comprehension, debugging, maintenance, and software archeology. Sequence diagrams generated from legacy code are independent of existing documentation that may have eroded. We present a framework for static generation of UML sequence diagrams from object-oriented source code. The framework provides a query refinement system to guide the user to interesting interactions in the source code. Our technique involves constructing a hypergraph representation of the source code, traversing the hypergraph with respect to a user-defined query, and generating the corresponding set of sequence diagrams. We implemented our framework as a tool, StaticGen (supporting software: StaticGen), analyzing a corpus of 30 Android applications. We provide experimental results demonstrating the efficacy of our technique (originally appeared in the Proceedings of Fundamental Approaches to Software Engineering—20th International Conference, FASE 2017, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2017, Uppsala, Sweden, April 22–29, 2017).