Chapter 11 - How Teams Manage Their Work

Based on our survey results, C now takes a slight lead over C++ compared to the previous year, increasing by 6%, though both are still leading programming languages for automotive software development.

For the first time in our annual results, the use of Python, which is the preferred language for AI and ML applications, increased over C++ use, with 48% of teams using Python, an increase of 12% year over year.

The use of Rust also saw a slight increase of 2% since last year, while other languages had similar results as last year. The Rust language is growing in importance for safety-critical environments, including automotive, because of its native mechanisms that help prevent the writing of unsafe code.

Automotive Development Focus 

When looking at the collected responses by automotive development focus, we found the following programming languages used for the various automotive components.

Most areas, predictably, use C/C++. Those working in Dealer Management use Java/JavaScript the most because the components have connections outside of the actual product. Energy Management, Manufacturing, Supply Chain, and 3D Visualization/Digital Twins/Immersive Design use Python the most. 
 

Many automotive development teams have adopted methods and processes that help them quickly adapt and develop quality software faster. In comparison to last year’s results, we can conclude that respondents are increasing the number of methods they are using, with Agile, Model-driven, and Automatic Code Generation development methods all increasing from year to year. 

Teams adopting faster methods and processes are still running into activities that take too much time. 

The most time-consuming activity this year continued to be “verifying and validating software,” with 44% of respondents citing this activity as a pain point (an increase of 2%). Teams short on time in this area would benefit from using verification methods like Perforce Static Analysis, which help to prevent, identify, and fix errors in automotive software systems.

“Documenting work and reviewing documentation” was also high on the list, increasing by 6% and taking teams more time this year than “reviewing code for errors/coding rule violations.” In this case, development teams could use Perforce ALM to keep track of issue management and review associated documentation. 

“Managing Multiple Variant Configurations” also increased somewhat this year. Tools such as Perforce P4 that support version control and features that support managing analysis data across different project streams in Perforce Static Analysis can drastically reduce time spent on such activities. 

As more software is added to vehicles, it is important to look at the operating system (OS) that development teams are using in the embedded software.

For the 46% who build from a base automotive OS, the leading operating system teams are building from was AUTOSAR OS (32%), followed by Automotive Grade Linux (23%).