An Abstract Interpretation Framework for Type and Effect Systems

2014 ◽  
Vol 134 (3-4) ◽  
pp. 355-393
Author(s):  
Letterio Galletta
Author(s):  
FELIPE BAÑADOS SCHWERTER ◽  
RONALD GARCIA ◽  
ÉRIC TANTER

AbstractEffect systems have the potential to help software developers, but their practical adoption has been very limited. We conjecture that this limited adoption is due in part to the difficulty of transitioning from a system where effects are implicit and unrestricted to a system with a static effect discipline, which must settle for conservative checking in order to be decidable. To address this hindrance, we develop a theory of gradual effect checking, which makes it possible to incrementally annotate and statically check effects, while still rejecting statically inconsistent programs. We extend the generic type-and-effect framework of Marino and Millstein with a notion of unknown effects, which turns out to be significantly more subtle than unknown types in traditional gradual typing. We appeal to abstract interpretation to develop and validate the concepts of gradual effect checking. We also demonstrate how an effect system formulated in the framework of Marino and Millstein can be automatically extended to support gradual checking. We use gradual effect checking to develop a fully gradual type-and-effect framework, which permits interaction between static and dynamic checking for both effects and types.


2014 ◽  
Vol 49 (1) ◽  
pp. 47-59
Author(s):  
Stefano Dissegna ◽  
Francesco Logozzo ◽  
Francesco Ranzato

2019 ◽  
Vol 3 (OOPSLA) ◽  
pp. 1-28 ◽  
Author(s):  
Sven Keidel ◽  
Sebastian Erdweg

2021 ◽  
Vol 54 (7) ◽  
pp. 1-37
Author(s):  
Jihyeok Park ◽  
Hongki Lee ◽  
Sukyoung Ryu

Understanding program behaviors is important to verify program properties or to optimize programs. Static analysis is a widely used technique to approximate program behaviors via abstract interpretation. To evaluate the quality of static analysis, researchers have used three metrics: performance, precision, and soundness. The static analysis quality depends on the analysis techniques used, but the best combination of such techniques may be different for different programs. To find the best combination of analysis techniques for specific programs, recent work has proposed parametric static analysis . It considers static analysis as black-box parameterized by analysis parameters , which are techniques that may be configured without analysis details. We formally define the parametric static analysis, and we survey analysis parameters and their parameter selection in the literature. We also discuss open challenges and future directions of the parametric static analysis.


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