In light of the growing interest in type inference research for Python, both researchers and practitioners require a standardized process to assess the performance of various type inference techniques. This paper introduces TypeEvalPy, a comprehensive microbenchmarking framework for evaluating type inference tools. Type- EvalPy contains 154 code snippets with 845 type annotations across 18 categories that target various Python features. The framework manages the execution of containerized tools, transforms inferred types into a standardized format, and produces meaningful metrics for assessment. Through our analysis, we compare the performance of six type inference tools, highlighting their strengths and limitations. Our findings provide a foundation for further research and optimization in the domain of Python type inference.

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While cryptography is now readily available to everyone and can, provably, protect private information from attackers, we still frequently hear about major data leakages, many of which are due to improper use of cryptographic mechanisms. The problem is that many application developers are not cryptographic experts. Even though high-quality cryptographic APIs are widely available, programmers often select the wrong algorithms or misuse APIs due to a lack of understanding. Such issues arise with both simple operations such as encryption as well as with complex secure communication protocols such as SSL. In this paper, we provide a long-term solution that helps application developers integrate cryptographic components correctly and securely by bridging the gap between cryptographers and application developers. Our solution consists of a software product line (with an underlying feature model) that automatically identifies the correct cryptographic algorithms to use, based on the developer's answers to high-level questions in non-expert terminology. Each feature (i.e., cryptographic algorithm) maps into corresponding Java code and a usage protocol describing API restrictions. By composing the user's selected features, we automatically synthesize a secure code blueprint and a usage protocol that corresponds to the selected usage scenario. Since the developer may change the application code over time, we use the usage protocols to statically analyze the program and ensure that the correct use of the API is not violated over time.@en