Safety Analysis versus Type Inference
نویسندگان
چکیده
Safety analysis is an algorithm for determining if a term in an untyped lambda calculus with constants is safe, i.e., if it does not cause an error during evaluation. This ambition is also shared by algorithms for type inference. Safety analysis and type inference are based on rather different perspectives, however. Safety analysis is global in that it can only analyze a complete program. In contrast, type inference is local in that it can analyze pieces of a program in isolation. In this paper we prove that safety analysis is sound , relative to both a strict and a lazy operational semantics. We also prove that safety analysis accepts strictly more safe lambda terms than does type inference for simple types. The latter result demonstrates that global program analyses can be more precise than local ones.
منابع مشابه
Safety Analysis versus Type Inferencefor Partial
Safety analysis is an algorithm for determining if a term in an untyped lambda calculus with constants is safe, i.e., if it does not cause an error during evaluation. We prove that safety analysis accepts strictly more safe lambda terms than does type inference for Thatte's partial types.
متن کاملSafety Analysis Versus Type Inference for Partial Types
Safety analysis is an algorithm for determining if a term in an untyped lambda calculus with constants is safe, i.e., if it does not cause an error during evaluation. We prove that safety analysis accepts strictly more safe lambda terms than does type inference for Thatte’s partial types.
متن کاملSafety Analysis versus Type InferenceJens
Safety analysis is an algorithm for determining if a term in an untyped lambda calculus with constants is safe, i.e., if it does not cause an error during evaluation. This ambition is also shared by algorithms for type inference. Safety analysis and type inference are based on rather diierent perspectives, however. Safety analysis is global in that it can only analyze a complete program. In con...
متن کاملRisk Analysis of Operating Room Using the Fuzzy Bayesian Network Model
To enhance Patient’s safety, we need effective methods for risk management. This work aims to propose an integrated approach to risk management for a hospital system. To improve patient’s safety, we should develop flexible methods where different aspects of risk and type of information are taken into consideration. This paper proposes a fuzzy Bayesian network to model and analyze risk in the op...
متن کاملBinding-time Analysis: Abstract Interpretation versus Type Inference
Interpretation versus Type Inference Jens Palsberg Michael I. Schwartzbach [email protected] [email protected] Computer Science Department, Aarhus University Ny Munkegade, DK–8000 Aarhus C, Denmark
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Inf. Comput.
دوره 118 شماره
صفحات -
تاریخ انتشار 1995