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Wiedner Hauptstraße 76, Stiege 2, 2. Stock; 1040 Wien
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by appointment per e-mail
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MISO (MIgrating SOftware) ist eine junge und dynamische Forschungsgruppe die sich mit alten und unbeweglichen (Software)Systemen beschäftigt. In der sich immer schneller verändernden Welt der IT ist der Weg von "heißem Eisen" zu "Legacy" sehr kurz geworden. Trotzdem, oder gerade deshalb, begleiten uns gewisse Technologien seit jeher bei der Digitalisierung der Welt. Ein Alleinstellungsmerkmal dieses spannenden Forschungsumfelds und damit Kernbestandteil unserer DNA ist die unzertrennliche Verbindung von Wissenschaft und Industrie. Über 30 oder 40 Jahre gewachsene Legacy-IT-Systeme entstehen nicht unter Laborbedingungen, Erfahrungen und Untersuchungsobjekte findet man daher vorrangig in "freier Wildbahn". Ziel dieser Gruppe ist die Erforschung von allen Arten von Legacy, dem Lernen aus Altbewährtem (und Fehlschlägen) und der Vermittlung von Wissen, das auf dem kollektiven Erfahrungsschatz der IT-Historie beruht.
We are offering supervision for all projects within our scope, including seminar, internship, bachelor thesis, and master thesis projects. You are encouraged to either choose a project from our “current research topics” or propose your own idea.
Software evolution is the process of change of a software system from creation through closure. A fundamental stage in the life cycle of software is software maintenance. Maintenance starts with the delivery of the software in it’s life cycle and extends to the closure. Historically, maintenance has been underestimated in its complexity and the need for appropriate methods and tools for proper operation. The maintenance phase claims about two-thirds of the total budget for the creation and operation of a software system. The aim of this course is to provide basic principles and methods of software maintenance and evolution.
The course provides a theoretical and practical introduction to software development on the mainframe in the PL/I and/or COBOL programming language.
An empirical engineering analysis of large scale migration case studies, their solution concepts and derived reasonable abstractions. This topic contrast the current state of the industry with the academic state of the art based on three case studies of successful legacy system migration efforts in representative domains (transportation, insurance and e-government) conducted over the last five years. On the one hand this will show newly established but proven industry best practices with a focus on deviations from published material. On the other hand focusing on lessons learned will highlight mistakes repeatedly made although already published in academic circles. The overall goal is to show the current state of the art of system migration for the 21st century by analyzing a series of case studies and highlighting common success factors as well as problems that can be translated into research questions to be addressed in the next decades. While in industry the search for a “silver-bullet” solution (like a completely automated, pain free transformation) is still common place, this work will highlight that large migration and reengineering efforts are subject to the influence of a large number of (soft) factors: