@conference {apiace:2024:msr, title = {APIstic: A Large Collection of OpenAPI Metrics}, booktitle = {21st IEEE/ACM International Conference on Mining Software Repositories (MSR)}, year = {2024}, note = {(to appear)}, month = {April}, address = {Lisbon, Portugal}, abstract = {In the rapidly evolving landscape of web services, the significance of efficiently designed and well-documented APIs is paramount. In this paper, we present APIstic an API analytics dataset and exploration tool to navigate and segment APIs based on an extensive set of precomputed metrics extracted from OpenAPI specifications, sourced from GitHub, SwaggerHub, BigQuery and APIs.guru. These pre-computed metrics are categorized into structure, data model, natural language description, and security metrics. The extensive dataset of varied API metrics provides crucial insights into API design and documentation for both researchers and practitioners. Researchers can use APIstic as an empirical resource to extract refined samples, analyze API design trends, best practices, smells, and patterns. For API designers, it serves as a benchmarking tool to assess, compare, and improve API structures, data models, and documentation using metrics to select points of references among 1,275,568 valid OpenAPI specifications. The paper discusses potential use cases of the collected data and presents a descriptive analysis of selected API analytics metrics. }, keywords = {dataset, metrics, OpenAPI}, author = {Souhaila Serbout and Cesare Pautasso} } @inproceedings {saw:2011:shark, title = {Goals, questions and metrics for architectural decision models}, year = {2011}, month = {May}, pages = {21{\textendash}28}, publisher = {ACM}, address = {Waikiki, Hawaii, USA}, abstract = {Architectural decisions are the key element behind the design process leading to a software architecture. Making software architects aware of the implications of their decisions is only the beginning of what can be achieved by capturing the rationale and the constraints influencing the decision making process in a reusable body of architectural knowledge. In this paper we propose a metric-based approach to the analysis of architectural decision models. Using a hierarchically-structured approach we identify a number of useful goals and stakeholders involved in the architectural design process. Next, we sketch a set of metrics to provide data for the evaluation of the aforementioned goals. Our aim is to stimulate a discussion on how to find indicators relevant for software architects by measuring the intrinsic properties of architectural knowledge.}, keywords = {architectural decision modeling, metrics, SAW, software architecture, visualization}, isbn = {978-1-4503-0596-9}, doi = {10.1145/1988676.1988682}, author = {Marcin Nowak and Cesare Pautasso} }