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Softwareentwicklung Für Die Naturwissenschaften: Bausteine Computergestützter Datenauswertung, Die Den Ansprüchen Der Wissenschaft Gerecht Wird
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ISBN10: 3662716062
ISBN13: 9783662716069
Publisher: Springer Spektrum
Published: May 22 2026
Pages: 613
Language: German
ISBN13: 9783662716069
Publisher: Springer Spektrum
Published: May 22 2026
Pages: 613
Language: German
Ein Kernaspekt der Wissenschaft ist die Nachvollziehbarkeit. Gleichzeitig wird durch die zunehmende Digitalisierung immer mehr Software verwendet und von Wissenschaftler*innen entwickelt. Allerdings wird die Qualität der meisten Software den Ansprüchen der Wissenschaft nicht gerecht. Dieses Buch bietet einen umfassenden Überblick über alle relevanten Aspekte für die Entwicklung von langlebiger, robuster und wartbarer Software. Behandelt werden die Entwicklungsinfrastruktur, die Code-Qualität, die Grundzüge von Softwarearchitektur und schlie lich Hinweise zur praktischen Umsetzung und Anwendung des Gelernten in einem Gesamtsystem zur wissenschaftlichen Datenauswertung. Die Themen werden auf konzeptioneller Ebene diskutiert und sind somit unabhängig von einer konkreten Programmiersprache. Weiterführende Fragen laden zum Nachdenken und Diskutieren ein.
Die Zielgruppe sind Naturwissenschaftler*innen in der Chemie, Physik und Biologie, die Software für ihre wissenschaftliche Arbeit entwickeln müssen, aber in ihrem Studium nie die dafür notwendigen Kompetenzen erlernen. Der Inhalt Das Wesen der Wissenschaft - Softwareentwicklung und Codequalität - Infrastruktur - Editoren / IDEs - Lizenzen und Urheberrechte - Versionsverwaltung - Versionsnummern - Externe Dokumentation - Bugverwaltung - Sauberer Code - Programmierparadigmen - Objektorientierte Programmierung (OOP) - Namen - Funktionen und Methoden - Formatierung: Layout und Stil - Dokumentation im Code - Entwurfsmuster (Design Patterns) - Tests - Testautomatisierung und testgetriebene Entwicklung - Refactoring - Codeoptimierung - Softwarearchitektur - Single-Responsibility-Prinzip - Open-Closed-Prinzip - Liskov-Substitutionsprinzip - Interface-Segregation-Prinzip - Dependency-Inversion-Prinzip - Datenverarbeitung und -analyse - Datenformate: beständig und plattformunabhängig - Datenaufnahme: Metadaten - Datenverarbeitung und -analyse: selbstdokumentierend - Datenpräsentation: Darstellungs- und Berichterstellung - Zusammenfassung und Ausblick.
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