Patrick and Radhia Cousot recieve ACM SIGPLAN Achievement Award

Programming Languages Achievement Award Given by ACM SIGPLAN to recognize an individual or individuals who has made a significant and lasting contribution to the field of programming languages. The contribution can be a single event or a life-time of achievement. Recipients of the Achievement Award

Patrick and Radhia Cousot are the co-inventors of abstract interpretation, a unifying theory of sound abstraction and approximation of structures involved in various domains of computer science, such as formal semantics, specification, proof, and verification. In particular, abstract interpretation has had a major impact on the development of the static analysis of software. In their original work, the Cousots showed how to relate a static analysis to a language's standard semantics by means of a second, abstract semantics that makes precise which features of the full language are being modeled and which are being discarded (or abstracted), providing for the first time both a formal definition of and clear methodology for designing and proving the correctness of static analyses. Subsequently, the Cousots contributed many of the building blocks of abstract interpretation in use today, including chaotic iteration, widening, narrowing, combinations of abstractions, and a number of widely used abstract domains. This work has developed a remarkable set of intellectual tools and has found its way into practice in the form of widely used libraries and frameworks. Finally, the Cousots and their collaborators have contributed to demonstrating the utility of static analysis to society. They led the development of the AstrĂˆe static analyzer, which is used in the medical, automotive, and aerospace industry for verifying the absence of a large class of common programming errors in low-level embedded systems code. This achievement stands as one of the most substantial successes of program verification to date.

ACM SIGPLAN Achievement Award
Patrick Cousot
Radhia Cousot


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nsfSupported by an Expeditions in Computing award from the National Science Foundation