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We are delighted to welcome you to ISSTA 2021, the 30th edition of the International Symposium on Software Testing and Analysis. The conference was initially scheduled to take place in Aarhus, Denmark, but due to the ongoing pandemic, it will take place online instead. ISSTA celebrates 30 editions this year! To mark the occasion, we are organizing two panels on the past and future of software testing and analysis, featuring senior members of our community.

Debugging in computer science

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The purpose of the ISO/IEC/IEEE 29119 series of software testing standards is to define an internationally-agreed set of standards for software testing that can be used by any organization when performing any form of software testing. ISO/IEC/IEEE 29119-3 includes templates and examples of test documentation. The templates are arranged within clauses reflecting the overall test process description structure in ISO/IEC/IEEE 29119-2, i.e. by the test process in which they are being produced. Annex A outlines the contents of each document and maps each document to ISO/IEC/IEEE 29119-2. Annex B contains an overview of the examples. Annexes C to R contain examples of the application of the templates. Annex S provides mappings to existing standards. Annex T explains the use of the term Test Model in this document. The Bibliography for this part of ISO/IEC/IEEE 29119 is at the end of the document. ISO/IEC/IEEE 29119-3 supports dynamic testing, functional and non-functional testing, manual and automated testing, and scripted and unscripted testing. The documentation templates defined in ISO/IEC/IEEE 29119-3 can be used in conjunction with any software development lifecycle model.

Computer programs --- Debugging in computer science. --- Testing.

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This book provides researchers and system developers with a high-level overview of the complex problems encountered when developing better user interaction with modern large-scale data-driven computing systems and describes a roadmap to solving these issues in the future.

Computer software. --- Debugging in computer science. --- Computer science.

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Long description: Python in seiner raffiniertesten Form Python Tipps und Tricks mit fortgeschrittenem Niveau Problemlösungen für den Programmieralltag NumPy-Grundlagen Python One-Liners zeigt Ihnen, wie man One Liners, Einzeiler, liest und schreibt: prägnante Ausdrücke zu nützlicher Funktionalität, verpackt in einer einzigen Codezeile. Sie lernen systematisch jede Zeile von Python-Code zu entschlüsseln und zu verstehen, und werden wie ein Experte eloquentes, stark komprimiertes Python schreiben. In den fünf Kapiteln des Buches werden Tipps und Tricks, reguläre Ausdrücke, Machine Learning, Kernthemen der Datenwissenschaft und hilfreiche Algorithmen behandelt. Die ausführlichen Erläuterungen von Einzeilern führen in wichtige Konzepte der Informatik ein und fördern Ihre Programmier- und Analysefähigkeiten. Sie lernen fortgeschrittene Python-Funktionen wie Listenverständnis, Slicing, Lambda-Funktionen, reguläre Ausdrücke, Map- und Reduce-Funktionen und Slice-Zuweisungen kennen. Sie erwerben darüber hinaus Kenntnisse in diesen Bereichen: - Nutzung von Datenstrukturen zur Lösung von Problemen aus der realen Welt, wie z. B. die Verwendung boolescher Indizierung zum Auffinden von Städten mit überdurchschnittlicher Umweltverschmutzung. - Verwendung der NumPy-Grundlagen wie Array, Form, Achse, Typ, Broadcasting, fortgeschrittene Indizierung, Slicing, Sortierung, Suche, Aggregation und Statistik. - Berechnen Sie grundlegende Statistiken von mehrdimensionalen Datenfeldern und die K-Means-Algorithmen für unsupervised Learning. - Erstellen Sie fortgeschrittenere reguläre Ausdrücke unter Verwendung von Gruppierungs- und benannten Gruppen, negativen Lookaheads, maskierten Zeichen, Leerzeichen, Zeichensätzen (und negativen Zeichensätzen) und greedy/non greedy Operatoren. - Ein breites Spektrum von Informatik-Themen verstehen, einschließlich Anagramme, Palindrome, Obermengen, Permutationen, Fakultäten, Primzahlen, Fibonacci-Zahlen, Obfuszierung, Suche und algorithmische Sortierung. Am Ende des Buches werden Sie wissen, wie man Python in seiner raffiniertesten Form schreibt und prägnante, schöne Python-Kunstwerke in nur einer einzigen Zeile schafft. Biographical note: Christian Mayer hat einen Doktortitel in Informatik und ist der Gründer der beliebten Python-Site Finxter (https:blog.finxter.com). Mayer ist außerdem der Autor der Coffee Break Python-Reihe.

Word --- Machine Learning --- Aufgaben --- NumPy --- debugging --- Reguläre Ausdrücke --- Schritt für Schritt --- GUI-Automatisierung --- PDF --- Web Scraping --- Slicing --- Lambda-Funktionen

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Program debugging has always been a difficult and time-consuming task in the context of software development, where spectrum-based fault localization (SBFL) is one of the most widely studied families of techniques. While it’s not particularly difficult to learn about the process and empirical performance of a particular SBFL technique from the available literature, researchers and practitioners aren’t always familiar with the underlying theories. This book provides the first comprehensive guide to fundamental theories in SBFL, while also addressing some emerging challenges in this area. The theoretical framework introduced here reveals the intrinsic relations between various risk evaluation formulas, making it possible to construct a formula performance hierarchy. Further extensions of the framework provide a sufficient and necessary condition for a general maximal formula, as well as performance comparisons for hybrid SBFL methods. With regard to emerging challenges in SBFL, the book mainly covers the frequently encountered oracle problem in SBFL and introduces a metamorphic slice-based solution. In addition, it discusses the challenge of multiple-fault localization and presents cutting-edge approaches to overcoming it. SBFL is a widely studied research area with a massive amount of publications. Thus, it is essential that the software engineering community, especially those involved in program debugging, software maintenance and software quality assurance (including both newcomers and researchers who want to gain deeper insights) understand the most fundamental theories – which could also be very helpful to ensuring the healthy development of the field.

Software engineering. --- Management information systems. --- Computer programming. --- Software Engineering. --- Software Management. --- Programming Techniques. --- Computers --- Electronic computer programming --- Electronic data processing --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Computer software engineering --- Engineering --- Programming --- Communication systems --- Debugging in computer science. --- Computer software --- Testing. --- Computer programs --- Troubleshooting in computer science --- Data editing --- Software failures --- Debugging --- Testing --- Software, Computer --- Computer systems --- Software engineering --- Software Testing. --- Management. --- Computer program testing --- Debugging in computer science