AdaCore: Build Software that Matters
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Welch Allyn® devices — a Hillrom product family

Ada and SPARK: Beyond Static Analysis for Medical Devices

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Case Study_

Ada and SPARK: Beyond Static Analysis for Medical Devices

The need for safe and secure software — including Medical Device software — is becoming more important as cybersecurity threats in the healthcare sector become more frequent and severe. Beyond increasing the reliability, safety and security of their software, Ada and SPARK programming language adopters are also looking at controlling and reducing costs. Hillrom migrated to Ada and SPARK to verify the safety of the code by formally proving some properties, and improving its efficiency by removing dynamic checks, all the while keeping development and verification costs down. Read the full case study to find out more.
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Proven in Practice_

Customer success: real results with AdaCore technologies

Customer

deepsense.ai specializes in providing cutting-edge AI solutions tailored to enterprises and mid-sized companies. With a focus on driving forward-thinking approaches, we collaborate with global leaders to optimize their products and services while delivering additional value to their customers. Since 2014 we have successfully delivered over 200 AI projects, engaging with organizations such as Zebra Technologies, Sky, Volkswagen, Brainly, Hexagon, Getinge, Johnson & Johnson, Hitachi, AdaCore, LogicMonitor, Juniper, Whirlpool, L’Oréal, Nielsen, Nvidia, Intel, Google and many more.

Challenge

How can we boost the productivity of Ada software developers? We teamed up with deepsense.ai to create a proof-of-concept copilot solution for the Ada programming language.

Solution

deepsense.ai quickly delivered a Proof of Concept for a code completion tool using a state-of-the-art technological stack, including the newest available LLMs and libraries.

Results and Benefits

The co-pilot for the Ada programming language project aimed to enhance Ada developer productivity with an intelligent code completion tool. deepsense.ai overcame challenges in LLM evaluation, training, and data resource constraints through problem decomposition and choosing the suitable evaluation scheme. The project marked significant progress for AdaCore in leveraging ML efforts to improve Ada developers' productivity.

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