Large ground-based astronomical telescopes deliver blurry images due to perturbations introduced by Earth's atmosphere. To recover sharp images, these distortions must be optically corrected in real time by an adaptive optics (AO) system. The control system that performs this task must operate thousands of optical sensors and correction elements at kHz speed to keep up with the fast-changing atmospheric turbulence. We are developing a free and open-source software (FOSS) package for high-performance, low-latency computing pipelines with stringent real-time requirements for astronomical adaptive optics (AO). The Compute and Control for Adaptive Optics (CACAO) toolkit’s modular design allows for customization for multiple applications, including imaging life-bearing planets orbiting nearby stars, which requires exquisite image quality with large telescopes. Over the last year, the software framework has undergone major improvements for modularity, ease-of-use, and support for modern AI/ML techniques.
This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 727 citations· ⚡54
The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.
M. Pikkarainen, Jukka Haikara, O. Salo et al.· Empirical Software Engineeri...· 401 citations· ⚡48
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
The perception of the impact of agile methods is predominantly positive, and several challenge areas were discovered, but based on this study, agile methods are here to stay.
M. Laanti, O. Salo, P. Abrahamsson· Information and Software Tec...· 260 citations· ⚡20
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MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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