This software solution will be used in more than 1 million cars every year
In April 2018, Objective Software GmbH, a company with more than 20 years in the automotive and financial sectors, offices in four countries, and more than 130 employees, turned to us as an embedded software development company to get help for a software project. At the time, they were looking for a perfectly coordinated dream team of experts in Autosar software architecture and embedded software development with customer processes experience.
The goal was to create an embedded logger for collecting statistical data on cars, suitable for big and small ECUs, supporting both classic and adaptive platforms.
One day, automobile manufacturers will remotely update software systems and monitor engine conditions or powertrain performance. Big Data will help in fleet management, in planning roadways and traffic flows, in creating customized insurance products, etc.
Collection and analysis of diagnostic data in the automotive industry is of paramount importance for both lifecycle support as well as tailoring product development.
The embedded logger can provide any type of statistical data from a car, from engine or exhaust system performance to the frequency of using car wipers. For automobile manufacturers, this software solution helps them gather the most complete and accurate data during new technology development or improvement, as well as in the aftermarket maintenance, process optimization, therefore saving customer's time and money.
The team that was working on this project consisted of the software architect, who was a team leader based in Munich, and three embedded software developers, who were participating in the project remotely.
Such an organization of work made it possible to make decisions on the spot and at the same time save client resources, thanks to remote collaboration.
A well-performed requirements analysis is a key element for project planning and resources estimation. That’s why, before starting to write code, we thoroughly analyzed the requirements in their entire scope and worked out the architecture and software detailed design. All technical requirements were divided into independent tasks; for each of them, a ticket (or tickets) with story point estimation was created. Based on this estimate, a development plan with final product delivery at the end of August (for classic) and the end of November (for Adaptive platform) was created. This plan matched well with the customer’s expectations.
