NDLI: Software development effort estimation for distributed embedded-systems

Content Provider	IEEE Xplore Digital Library
Author	Winne, O. Beikirch, H.
Copyright Year	2013
Description	Author affiliation: Fak. fur Inf. und Elektrotechnik, Univ. Rostock, Rostock, Germany (Beikirch, H.) \|\| Lamtec Leipzig GmbH & Co. KG, Taucha, Germany (Winne, O.)
Abstract	Mastering the increased complexity of today's programmable electronic systems (PES) is topic of many research and development projects. The risen complexity in real time embedded-systems has been identified as a barrier for a fast time-to-market product development in many projects. At the same time, more and more flexibility, scalability and distributed intelligence are required for new PES. But what does it mean in detail that a PES is more or less complex and how can complexity and its influence on the effort for developing a distributed PES be examined already in the design phase of a development project? This paper discusses a method to estimate complexity and development effort for distributed PES. In addition, the method can be used to compare different possible solutions to achieve an optimised design decision. Therefor, the effort estimation method COCOMO (Constructive Cost Model) was expanded for distributed PES (COCOMOdist). It was validated exemplarily within a practical development project (Distributed Burner Control), resulting in several interesting conclusions.
Starting Page	622
Ending Page	629
File Size	682174
Page Count	8
File Format	PDF
ISBN	9781467322300
e-ISBN	9781467322324
DOI	10.1109/EUROCON.2013.6625046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-01
Publisher Place	Croatia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Complexity theory Software Estimation Safety Computer architecture Real-time systems Compounds design of distributed real-time systems COCOMO distributed embedded-systems effort estimation complexity
Content Type	Text
Resource Type	Article

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