Solutions to Automotive Software Engineering Challenges

International Journal of Computer & Organization Trends  (IJCOT)          
© 2015 by IJCOT Journal
Volume - 5 Issue - 1
Year of Publication : 2015
Authors : Adnan Shaout , Gamal Waza
DOI : 10.14445/22492593/IJCOT-V16P303


Adnan Shaout , Gamal Waza "Solutions to Automotive Software Engineering Challenges", International Journal of Computer & organization Trends (IJCOT), V5(1):14-20 Jan - Feb 2015, ISSN:2249-2593, Published by Seventh Sense Research Group.


The amount of software in cars has been growing over the years. Furthermore, cars in the future also expect to demand more and more software functionalities. Adding to the complexity, the automotive industry has specific constraints and requirements that mandate unique solutions. These specific constraints also bring many challenges to software engineering in cars. In this paper, the automotive software engineering concerns and challenges will be addressed. Software engineering methods such as traditional, agile and/or spiral will be evaluated against the unique environment found in the automotive industry. The Decision Analysis and Resolution (DAR) evaluation process was chosen for evaluating the seven most used software engineering methods in automotive industry with respect to selected prioritized parameters. The selected parameters for the evaluation were Reliability, Low Cost, Reusability, Flexibility, Adaptability, Sustainability, Certifiable, Suitability, Scalability, Simplicity, Efficiency and Controllability. Results have shown that the Spiral software development model is the most suitable process for automotive software engineering. Spiral model scored didn’t score high in all parameters. For example, “low cost” parameter was one of the parameters where spiral model scored low. Finally, although evaluation shows spiral was the most suited based on the prioritized parameters, slight change in parameter priority can results in different software development process.


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Software Engineering Methods; Automotive; Software Performance Parameters; DAR Process; Software Challenges