CeBit 2013: Shareconomy – Higher impact on source code ?

CeBit 2013: Shareconomy & cloud computing & software quality go hand in hand.

Only the ones who share win. Based on this assumption completely different business models have been developed, which on the one hand live on the participation of the community and on the other hand are driven by the circumstance that you do not necessarily need to own a product in order to use it.

Cloud computing is a very good example for the shareconomy. As tempting as the idea of organisations sharing resources may sound, there are plenty of risks when it comes to software.

If many use the same software, many are affected by software bugs. While in the past many used the same software products, in the context of cloud computing and shareconomy these products are run on the same servers in the same datacenters. This causes new dependencies.

In the past programming errors could have an effect on one or more computers that used the same software in the exact same context. Nowadays, software errors can have an impact to all users being affected at the same time or it can even lead to a total system failure as happened before at Amazon and Facebook:

http://www.cio.de/was_ist_cloud_computing/2273066/
http://www.sueddeutsche.de/digital/blackout-bei-facebook-ein-paar-stunden-echtes-leben-1.1302305

In the shareconomy software quality ist even more important. But developing high quality software that can be maintained and extended efficiently is no rocket science anymore.

Read more: http://blog.softwarediagnostics.com/cebit-2013-shareconomy-higher-impact-on-source-code/

Mithilfe von ‚Software-Lagekarten‘ behalten IT-Management und Entwicklungsteams das Steuer in der Hand. Auf einen Blick können Codequalität, Entwicklungs-Hotspots, Codeabdeckung durch Tests, Bugfixes, Teamaktivitäten oder Codenutzung durch Endanwender eingesehen werden. So werden Projektrisiken frühzeitig erkannt – und vermieden.

Software Diagnostics bietet mit der Transparency Platform die Möglichkeit wirtschaftliche Entscheidungen auf Grundlage objektiver Daten über den Projektstatus aus objektiven Quellen wie Quellcode, Laufzeitumgebungen, Test-Systemen, Versionierungs-Systemen, Bugtracking-Systemen zutreffen.

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