Akamas listed as AI-Augmented Software Engineering tool in Gartner Hype Cycle

Gartner reports "Hype Cycle for Software Engineering 2022" (ID G00771312, published August 1st, 2022)" and "Hype Cycle for Open-Source Software 2022” (ID G00771218, published July, 20th 2022) cover critical areas of interest for software engineering leaders who want to track innovations that leverage

Akamas Sogeti book
State of AI applied to Quality Engineering 2021-22 by Sogeti

Akamas in cooperation with Tricentis contributed to the “State of AI applied to Quality Engineering 2021-22” report by Sogeti. This report focuses on AI as an essential element for Quality Engineering, with section 6 addressing the role of AI in performance

Akamas 451 Research Coverage initiation
Coverage initiation: “Akamas promises full-stack optimization with goal-oriented ML”

451 Research “Initial Coverage” report by Jean Atelsek and Liam Rogers (published: July 2021). Read how 451 Research assesses Akamas capabilities: “Akamas has applied reinforcement learning to meet this challenge, developing an optimization engine and scoring algorithm that enables users

Collaborative filtering approach Akamas LCTES
Collaborative Filtering: the new state-of-the-art for compiler autotuning

Selecting the right compiler optimizations is known to have huge impacts on application performance. However, optimization options constantly increase and their effect is highly dependent on the specific program, preventing a manual approach. This paper by Akamas Research and Politecnico

Akamas CMG paper 2015 winner
Capacity planning for Java applications – how to deal with GC hidden bottlenecks

Java automatic memory management provides safety and development efficiency, but also adds further challenges for Performance Engineers and Capacity Managers. This paper by Akamas CTO Stefano Doni won the prestigious 2015 Computer Measurement Group Best Paper Award. Highlights: How Java