Nteract

Jupyter notebooks---documents that contain live code, equations, visualizations, and narrative text---now are among the most popular means to compute, present, discuss and disseminate scientific findings. In principle, Jupyter notebooks should easily allow to reproduce and extend scientific computations and their findings; but in practice, this is not the case. The individual code cells in Jupyter notebooks can be executed in any order, with identifier usages preceding their definitions and results preceding their computations. In a sample of 936 published notebooks that would be executable in principle, we found that 73% of them would not be reproducible with straightforward approaches, requiring humans to infer (and often guess) the order in which the authors created the cells. In this paper, we present an approach to (1) automatically satisfy dependencies between code cells to reconstruct possible execution orders of the cells; and (2) instrument code cells to mitigate the impact of non-reproducible statements (i.e., random functions) in Jupyter notebooks. Our Osiris prototype takes a notebook as input and outputs the possible execution schemes that reproduce the exact notebook results. In our sample, Osiris was able to reconstruct such schemes for 82.23% of all executable notebooks, which has more than three times better than the state-of-the-art; the resulting reordered code is valid program code and thus available for further testing and analysis.

Unlike text reading, the eye-movement behaviours associated with reading Python, a computer programming language, are largely understudied through a psycholinguistic lens. A general understanding of the eye movements involved in reading while troubleshooting Python, and how these behaviours compare to proofreading text, is critical for developing educational interventions and interactive tools for helping programmers debug their code. These data may also highlight to what extent humans use their underlying text reading ability when reading source code. The current work provides a profile of global reading behaviours associated with reading Python source code for debugging purposes. To this end, we recorded experienced programmers’ eye movements while they determined whether 21 different Python functions would produce the desired output, an incorrect output, or an error message. Some reading behaviours seem to mirror those found in text reading (e.g. effects of stimulus complexity), while others may be specific to reading code. Results suggest that semantic errors that produce undesired outputs in programming source code may influence early stages of processing, likely due to the largely top-down strategy employed by experienced programmers when reading source code. The findings are framed to invigorate discussion and further exploration into psycholinguistic analysis of human source code reading.

W artykule opisane są sposoby wspierania tez w telewizyjnych programach informacyjnych. Jako materiał badawczy służą wydania trzech najpopularniejszych w Polsce programów: Faktów, Wiadomości oraz Teleexpressu. Analizie poddano informacje wyemitowane w dniach 1–3 marca 2017 r. W wyniku analizy udało się ustalić źródła pochodzenia tez – są cytatami, parafrazami wypowiedzi osób publicznych lub konkluzjami dziennikarskimi, które stanowią efekt interpretacji zjawisk społeczno-politycznych. Tezy, o których mowa, są werbalizowane przez dziennikarzy (prowadzących program lub terenowych) lub zawarte w narracjach towarzyszących prezentowanym materiałom filmowym. Dodatkowo pojawiają się także w graficznie animowanych napisach banerowych. Wsparcie tez najczęściej ma postać werbalną – media posługują się przede wszystkim dwiema technikami: ab auctoritate (wypowiedzi eksperta, polityka) oraz ab exemplo. Drugą grupę stanowią graficzne sposoby wspierania tez, gdzie przesłanki, dowody i przykłady najczęściej zaczerpnięte są ze źródeł internetowych: dominują tu owoce aktywności osób publicznych w mediach społecznościowych. Ponadto prezentowane są skany różnych dokumentów urzędowych, listów otwartych, rzadziej pojawiają się wizualizacje danych w postaci tabel, wykresów i diagramów. Wykryto także tezy bez wsparcia – jego rolę pełni wiarygodność medium. Ciekawy zabiegiem jest zachęcanie do aktywności inferencyjnej widzów programu – prezentowane są wyłącznie przesłanki, stworzenie konkluzji to już zadanie odbiorcy.

PT Akselerasi Sumber Berkah is a local company engaged in the production and distribution of beauty and health products, under the brand name Beaudelab. This company was established in 2019. PT Akselerasi Sumber Berkah is located in West Denpasar, Bali. In processing sales data, the company uses Microsoft Excel. The weakness of the data or information generated is still in the form of tables that do not display more informative information in the form of graphs, making it difficult for companies to see sales developments and other information in a short time. Therefore, in this study, a sales data visualization using tableau was built to assist companies in processing table data into information in the form of graphs so that it does not take a long time to see the company's sales development. The research method used in this research is the nine steps kimball method. In this research through the stages of analyzing company data, designing a data warehouse, extract transform load process, implementing data visualization, and testing the system. This system was tested using the user acceptance test method and has obtained results with a percentage of 93% or strongly agree so that this sales data visualization is in accordance with the needs of the company. The results of this study are in the form of 3 pages that display company information in the form of graphs to assist in decision making.

Since the source code is only one of many types of documents that must be maintained as a software system evolves, modern software development could be improved by better interoperability between source code and other software documents. The Software Concordance is a prototype programming environment that uses hypermedia services and a uniform document model to achieve this interoperability. The Software Concordance editor allows developers to enhance their inline documentation with multimedia objects and hyperlinks, while still supporting advanced program analysis including lexing, parsing and type checking. We motivate the need for environments like the Software Concordance, describe the design and implementation of its program editor, and discuss lessons learned while creating it. The system is based on a uniform, Web compatible document model for both program source code and nonprogram software documents and a corresponding API. Important technical problems addressed by this research include creating a persistent representation of program lexemes that the analysis suite considers to be ephemeral (such as keywords), providing a simple incremental parsing system, and embedding multimedia in source code without disrupting program analysis. Based on insight gained in the process of implementing the document API, a new approach to the design of a more suitable program analysis infrastructure is suggested.

A significant slowdown in processor performance growth is associated with approaching the physical limits of reducing transistor size. This has led to the situation where traditional ways of increasing performance (increasing the clock frequency or the number of cores) no longer fully deliver performance gains. In modern processors, SIMD (Single Instruction, Multiple Da-ta) instruction-set architectures play an important role in increasing computing performance. They allow a processor to perform one operation on multiple data streams simultaneously on a single core. In such a situation, parallel processing at the data level, implemented using SIMD instructions, becomes key. Directing the compilation process with special directives, options, and proper data organization makes it possible to obtain an optimized, vectorized code without explicitly using SIMD instructions in the program source code. However, the effectiveness of such mechanisms largely depends on a number of factors: the processor architectural features, the compiler version, the source code quality, and the optimizer state. The article analyzes some existing methods and tools for vectorizing code using SIMD instructions and proposes an ap-proach to automating vectorization by inserting labels into source code, detecting section boundaries in compiled code, analyzing instructions within sections, and generating a report with a link to the source code. A comparative analysis of existing vectorization tools and the developed prototype is conducted. The proposed approach allows for automating the verifica-tion of code vectorization with line-level accuracy and works even with aggressive optimiza-tion, including function embedding.

Perpetrators might employ computer programs (software) to perform their offenses or to cover their wrongdoings. Program's source code, in particular variables and their values diverge in their scope and duration in RAM. Object oriented languages encapsulate variables and operations in classes and allow for objects to be instantiated, which simplify software design but add to the complexity of its execution behavior and its data and control flow. This paper explores execution behaviors and information left by program execution in support for legal actions against perpetrators in the court of law. Our investigation model assumes no information is provided by the operating system; only raw RAM dumps. Our methodology employs information from the presumed program source code and its object oriented design. It explores various execution states and scenarios to uncover the evidence of potential software usage. These scenarios are designed to show that scope, access modifiers, and storage information of various source code variables can be used to identify program's activities. Results show that investigators have good chances locating various variables' values that are uniquely corresponded to the presumed software and its execution states. In some cases, values are successfully identified in memory dumps even after the process is stopped.

Automated recovery of system features and their designs from program source codes is important in reverse engineering and system comprehension. It also helps in the testing of software. An error that is made by users in an input to an execution of a transaction and discovered only after the completion of the execution is called a posttransaction user-input error (PTUIE) of the transaction. For a transaction in any database application, usually, it is essential to-provide transactions for correcting the effect that could result from any PTUIE of the transaction. We discover some probable properties that exist between the control flow graph of a transaction and the control flow graphs of transactions for correcting PTUIE of the former transaction. Through recognizing these properties, we present a novel approach for the automated approximate recovery of provisions and designs for transactions to correct PTUIE of transactions in a database application. The approach recognizes these properties through analyzing the source codes of transactions in the database application statically.

Superhost Airbnb is an experienced host and provides excellent service to its customers. Superhost has features that can increase the number of bookings and revenue. SuperHost profile is one thing that can be used as a reference for other hosts to improve the quality of service. In this study, an analysis of exploration and visualization of Airbnb hosts' data in the city of Amsterdam and the city of Madrid to find out the profile of superhost from the aspect of price and consumer reviews. The city of Amsterdam and the city of Madrid are chosen because the two cities are the leading destinations for tourists in Europe. The study was conducted using a machine learning approach that has four work steps, namely understanding business processes, data retrieval, data processing, and exploratory analysis and data visualization. The tools used in this study are Jupyter Notebook with the Python programming language. The results obtained from this study are superhost in Madrid, mostly offering rental prices in the price range of $60 - $80. They get the highest reviews from customers based on cleanliness, communication, and check-in. As for Amsterdam, the superhost offers the most rental prices in the price range above $ 140. Superhosts in this price range gets the most reviews from customers in all review groups.

In Engineering and Scientific computing, a significant number of software systems that are being commonly used by the Engineering community are developed and deployed as Open Source Systems (OSS). This collaborative development model has been widely accepted in both academia and industry. As these systems are typically developed by developers who are experts in their fields (e.g., Engineering), some of those programmers may be lacking an essential skillset today's software quality and engineering concepts (e.g., source code maintainability and analyzability, source code vulnerability, parallelization, etc.). An empirical study is presented that examines some of the source code quality aspects and programming practices (e.g., jumps statements, usage of recursion) from software engineering perspective in ten open source Engineering software systems. The studied systems are written in the C/C++ programming languages and comprised of over ten million lines of code, and present numerous tasks of the engineering community, including computer-aided design, computational fluid dynamics, and finite element analysis. Static analysis methods are applied to each system to determine the number of jump statements (Goto and Break statements) and functions that are recursively invoked. Functions that contain direct or indirect recursive calls are determined and counted. The results show that number of the used jump statements and functions that have recursive calls are significant and thus pose more of a roadblock to effectively and automatically maintain, comprehend, analyze, and re-engineer systems. Lastly, this leads to inefficiencies in a software engineer's ability to accomplish these common tasks. The study showed that issues in source code stemming from the lack of coding standards have increased over time and are prevalent.

A method to remove variations in source codes

Chapter 2 - Information Visualization: Scope, Techniques and Opportunities for Geovisualization

Introduction: Being overweight due to lifestyle and dietary habits may lead to non-communicable diseases such as heart disease, stroke, and diabetes in the future. Generation Z is the generation born in 1995-2010. Use of shallots has antiobesity effects because it can reduce body fat and body weight Methods: The poultry eggs used in the acceptability of shredded are chicken eggs and this study was conducted by 25 moderately trained panelists with hedonic quality test. Data processing using Kruskall Wallis test to determine the real difference of ebelabon (egg shredded level delicious) with the addition of roasted onions 0%, 5%, 10% and 15% of the total poultry egg shredded served, shredded Data processing and analysis using SPSS software and presented in the form of tables, graphs, and narrative text. Results: The results showed that there was no significant difference in the acceptability of shredded poultry eggs. Based on the results of statistical analysis of four parameters on moderately trained panelists that the most preferred taste and overall were in formula 4, namely the addition of roasted onions 15% of the total shredded poultry eggs. Conclusion: As for the selected formula, formula 4 will be further tested by testing the content of macronutrients such as calories (energy), protein, fat and carbohydrates and carried out interventions for overweight students or generation Z who are currently studying.

In a variety of disciplines, from biology and physics to computer science and the social sciences, computational topology has become a potent tool for data analysis and visualisation. This study explores computational topology's uses in data analysis and visualisation, showing its potential for revealing hidden structures and patterns in large, complicated datasets.The paper starts out by giving a general introduction of computational topology and outlining its core ideas and methods. The use of it for extracting important information from big, high-dimensional datasets is then explored in relation to data analysis. Computational topology allows for the discovery of topological properties such as holes, voids, and connection patterns by modelling data as topological structures, such as simplicial complexes or persistent homology diagrams.The study also explores the function of computational topology in data visualisation, highlighting its capacity to offer clear and insightful visual representations of challenging datasets. Computational topology enables the construction of simpler and aesthetically pleasing representations while preserving the fundamental topological properties of the data through methods like topological simplification and dimensionality reduction.The usefulness of computational topology in several application domains, such as genomics, image analysis, and network analysis, is demonstrated through a number of case studies. These instances show how computational topology can improve activities like data exploration, clustering, classification, and anomaly detection, resulting in fresh perceptions and learnings.This study emphasises the enormous potential of computational topology for applications in data processing and visualisation. Computational topology provides a new perspective that complements current approaches by utilising the inherent geometric and topological properties of data. This allows researchers and practitioners to better understand complex datasets and make decisions based on the knowledge gleaned from them.

The analysis of human gait from biometric data has applications in areas such as safety, bio-inspired robotics and health. Low-cost motion sensors such as Kinect have enabled the acquisition of biometric gait data in terrestrial environments. However, these devices have limitations that can impact the quality of the acquired data. In this scenario, different signal processing techniques can be applied to reduce noise. Visualization of this data, whether original or processed, is often performed in the form of graphs, having limited utility for professionals not experienced in signal analysis. In this sense, the visualization of gait data in a three-dimensional model can contribute to better decision-making by professionals, especially in healthcare. This work aims to perform the graphic animation of the human gait in a three-dimensional model, from data collected by the Kinect 2.0 sensor. To reduce the noise of the acquired data, a pre-processing was performed with the application of moving average and Butterworth filters. Videos of the animations in isometric and side views were created and evaluated in a field research on the artificiality/naturalness of animation, using the mean opinion score (MOS) technique. A total of 22 participants answered the questionnaire. The one-way ANOVA statistical test showed that videos in isometric and side view processed with moving average filter (window=15 and repetitions=3) that obtained higher MOS metric values ​​were evaluated as significantly more natural than other processed videos or not.