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Implications of application programming interfaces for Third-Party New App Development and Copycatting

PRODUCTION AND OPERATIONS MANAGEMENT 2019年第8期28卷 1887-1902页

作者： Xue, Ling Song, Peijian Rai, Arun Zhang, Cheng Zhao, Xia Georgia State Univ J Mack Robinson Coll Business Atlanta GA 30302 USA Nanjing Univ Sch Business Nanjing 210093 Jiangsu Peoples R China Fudan Univ Sch Management Shanghai 200433 Peoples R China Univ Georgia Terry Coll Business Athens GA 30602 USA

Digital platforms can use application programming interfaces (APIs) to support third-party development of new apps and achieve growth at an unprecedented scale. However, there is also a dilemma between original new development and copycatting by third-party suppliers. Motivated by this tension, we examined how APIs provided by digital platforms may influence two types of third-party new app development: original apps and app copycatting. We also investigated how these influences are dependent on app market conditions. We empirically tested our theoretical conjectures using data on a leading web browser platform, and applying analytics techniques on app source code to identify original apps and copycat apps. Based on a difference-in-differences identification strategy, our findings suggest that the provision of platform APIs enhance the original new development of apps. While platform APIs may facilitate app copycatting as well, our findings suggest that platform APIs can enhance app suppliers' relative attractiveness to original new development in comparison to copycatting. The enhancing effect of platform APIs on original new development is strengthened by app market potential and high market-level app complexity. The enhancing effect of platform APIs on app copycatting is strengthened by app market potential and high market concentration. Our study has important theoretical and practical implications.

关键词： new product development platform application programming interfaces innovation copycat

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Improving efficiency of COVID-19 aggregate case and death surveillance data transmission for jurisdictions: current and future role of application programming interfaces (APIs)

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2022年第10期29卷 1807-1809页

作者： Khan, Diba Park, Meeyoung Lerma, Samuel Soroka, Stephen Gaughan, Denise Bottichio, Lyndsay Bray, Monika Fukushima, Mary Bregman, Brooke Wiedeman, Caleb Duck, William Dee, Deborah Gundlapalli, Adi Suthar, Amitabh B. Ctr Dis Control & Prevent Coronavirus Dis Response Atlanta GA 30333 USA Calif Dept Publ Hlth Sacramento CA USA Tennessee Dept Publ Hlth Nashville TN USA

During the coronavirus disease-2019 (COVID-19) pandemic, the Centers for Disease Control and Prevention (CDC) supplemented traditional COVID-19 case and death reporting with COVID-19 aggregate case and death surveillance (ACS) to track daily cumulative numbers. Later, as public health jurisdictions (PHJs) revised the historical COVID-19 case and death data due to data reconciliation and updates, CDC devised a manual process to update these records in the ACS dataset for improving the accuracy of COVID-19 case and death data. Automatic data transfer via an application programming interface (API), an intermediary that enables software applications to communicate, reduces the time and effort in transferring data from PHJs to CDC. However, APIs must meet specific content requirements for use by CDC. As of March 2022, CDC has integrated APIs from 3 jurisdictions for COVID-19 ACS. Expanded use of APIs may provide efficiencies for COVID-19 and other emergency response planning efforts as evidenced by this proof-of-concept. In this article, we share the utility of APIs in COVID-19 ACS.

关键词： COVID-19 surveillance CDC application programming interfaces

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Invisible actors: Web application programming interfaces, television, and social media

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CONVERGENCE-THE INTERNATIONAL JOURNAL OF RESEARCH INTO NEW MEDIA TECHNOLOGIES 2016年第4期22卷 426-439页

作者： Lahey, Michael Kennesaw State Univ Digital Writing & Media Arts Dept Marietta GA USA

This article focuses on the role web application programming interfaces (APIs) play in the television (TV) industry's social media efforts. Web APIs are coding interfaces that allow different databases of information to communicate with one another. The widespread implementation of web APIs as a standard for information sharing offers a way for TV companies to more easily cobble together a presence in connected viewing environments. In this light, web API acts as, what Joshua Braun calls, `transparent intermediaries' that actively shape the range of possibilities available in these types of intermedial partnerships. I explain web APIs before showing how they relate to media studies through the TV show Psych's forays into designing social media experiences. Additionally, I will explain how web API-connected digital environments are used to facilitate what Tiziana Terranova calls soft control as web APIs embody Web 2.0 ideologies that celebrate information sharing between businesses that track audience attention.

关键词： application programming interfaces connected viewing design digital infrastructure Psych social TV soft control

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Static Analysis for Improved Modularity of Procedural Web application programming interfaces

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IEEE ACCESS 2020年 8卷 128182-128199页

作者： Barros, Alistair Ouyang, Chun Wei, Fuguo Queensland Univ Technol Sch Informat Syst Brisbane Qld 4000 Australia

Despite their rapid growth, the utilisation of application programming interfaces (APIs) poses challenges for companies under pressure to yield productive systems integration. APIs of larger systems tend to be large, complex and have reduced modularity and quality, which makes them cumbersome to comprehend and use. These challenges can be addressed by static API analysis that focuses on studying API code itself and deriving business entities and dependencies from operational signatures. However, existing techniques for static analysis of APIs face the challenges in deriving a sufficient coverage of business entity relationship types from implementation-oriented API operational signatures carrying limited semantic insights. The paper aims to address such problems by supporting static analysis techniques for APIs that improve their modularity. Our approach adopts an object-oriented paradigm where the concept of "object" is exemplified by the notion of business entity. It systematically applies interface analysis methods and techniques for eliciting knowledge of business entities and their attributes, for deriving the temporal order of calling operations across multiple business entities, and for learning and extracting various ways of invoking a service via APIs. The approach is implemented as an open-source tool and applied to a group of widely-deployed services in practice for validation. The research contributes to identifying key aspects of both the structure and behaviour of APIs, which will lead to building a simplified but comprehensive interface (presentation) layer to assist service users in understanding complex and overloaded interfaces as well as to facilitate efficient and effective service integration.

关键词： application programming interfaces APIs business entity service interface analysis service interface synthesis service variants web services

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Generation of Digital Twins for Exchanging Information via application programming interfaces

Generation of Digital Twins for Exchanging Information via A...

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Industrial Cyber-Physical Systems (ICPS)

作者： Nico Braunisch Marko Ristin-Kaufmann Uwe Schmidt Robert Lehmann Martin Wollschlaeger Hans Wernher van de Venn TU Dresden Institute of Applied Computer Science Zurich University of Applied Sciences (ZHAW) Institute of Mechatronic Systems (IMS)

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

In the rapidly evolving landscape of Industry 4.0, the Asset Administration Shell (AAS) is a fundamental building block for developing digital twins. This paper presents an innovative approach to automatically generate application programming interfaces (API) for AAS-based systems from a formalized specification. So far, the convention was to manually specify the API for AAS by tedious translation of the abstract specification published in form of a book. We propose, instead, to formalize the abstract specification, and automatically translate it into API. We thus streamline the development process, ensure effectiveness, and minimize the risk of errors in the representation of digital twins otherwise inherent in the manual procedure. Our proposed approach places great importance on automating the development of AAS APIs, using common and widespread YAML/OpenAPI as a serialization format due to its clarity and simplicity. Additionally, the paper examines other Interface Descriptions such as Protobuf, SOAP, GraphQL, and WSDL, emphasising the significance of clearly defined interfaces for efficient AAS API utilisation. Our method guarantees scalability and flexibility, specifically in relation to SDK generation, whereby different AAS interfaces are generated to support smooth integration within the constantly changing landscape of Industry 4.0. This comprehensive approach facilitates the entire lifecycle of digital twin development, spanning from API generation to SDK development, to ensure resilient and adaptable solutions agnostic to particular serialization formats.

关键词： Scalability Manuals Digital twins Fourth Industrial Revolution Simple object access protocol application programming interfaces

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Sometimes you need to see through walls: a field study of application programming interfaces 04

Sometimes you need to see through walls: a field study of ap...

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Proceedings of the 2004 ACM conference on Computer supported cooperative work

作者： Cleidson R. B. de Souza David Redmiles Li-Te Cheng David Millen John Patterson Universidade Federal do Pará Belém Brasil and University of California Irvine Irvine CA University of California Irvine Irvine CA IBM T. J. Watson Research Center Cambridge MA

ISBN: (纸本)9781581138108

Information hiding is one of the most important and influential principles in software engineering. It prescribes that software modules hide implementation details from other modules in order to decrease the dependency between them. This separation also decreases the dependency among software developers implementing modules, thus simplifying some aspects of collaboration. A common instantiation of this principle is in the form of application programming interfaces (APIs). We performed a field study of the use of APIs and observed that they served many roles. We observed that APIs were successful indeed in supporting collaboration by serving as contracts among stakeholders as well as by reifying organizational boundaries. However, the separation that they accomplished also hindered other forms of collaboration, particularly among members of different teams. Therefore, we think argue that API's do not only have beneficial purposes. Based on our results, we discuss implications for collaborative software development tools.

关键词： interfaces application programming interfaces collaborative software development qualitative studies

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Challenges of application programming interfaces Security: A Conceptual Model in the Changing Cyber Defense Environment and Zero Trust Architecture

Challenges of Application Programming Interfaces Security: A...

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IEEE International Scientific Conference on Informatics

作者： William Steingartner Darko Galinec Vinko Zebić Faculty of Electrical Engineering and Informatics Technical University of Košice Košice Slovakia Department of Informatics and Computing Zagreb University of Applied Sciences Zagreb Croatia Croatian Military Academy "Dr. Franjo Tuđman" Croatian Armed Forces Ministry of Defence Zagreb Croatia

ISBN: (数字)9798350387681

ISBN: (纸本)9798350387698

application programming interfaces (APIs) for connecting applications are the most important for interoperability between disparate information systems today. It allows that the application that offers such an interface does not allow direct access to the server and all data, but each interface provides only the corresponding necessary data. The efficiency and speed of APIs enable information systems to retrieve formatted data that can be sequentially processed and used. In this paper API security will be discussed as a challenge today. The integration of today’s applications takes place in the conditions of a changing environment of information systems and growing threats of cyber defense and security. The new approach to security was created, which is reflected through the principles of Zero Trust Architecture (ZTA). To enable a comprehensive overview of API security challenges, in this work, the authors designed and presented a new extensive conceptual non-hierarchical model of API cyber defense. In addition to known cybersecurity threats, it takes into account the threats inherent in non-compliance with the principles of ZTA which is also known as Zero Trust Security Model, or Zero Trust Network Access (ZTNA). The designed model covers, amongst others, the intersection between the strategy of secure API construction and Zero Trust Architecture.

关键词： Runtime Organizations Vectors Zero Trust Security Servers Protection Informatics application programming interfaces Testing

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Why APIs? Anticipated value, barriers, and opportunities for standards-based application programming interfaces in healthcare: perspectives of US thought leaders

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JAMIA OPEN 2022年第2期5卷 ooac023页

作者： Gordon, William J. Rudin, Robert S. Brigham & Womens Hosp Dept Med 75 Francis St Boston MA 02115 USA Mass Gen Brigham Somerville MA USA Harvard Med Sch Dept Biomed Informat Boston MA 02115 USA RAND Corp Hlth Care Div Boston MA USA

Lay Summary application programming interfaces ("APIs") are a technical way of getting data out of a computer system. Recently, the United States passed legislation (the 21st Century Cures Act) requiring the use of APIs for electronic health record systems, which are where most healthcare providers document clinical encounters with patients and where other clinical data is held. In this article, we asked national experts in health information technology to describe some of the ways in which APIs could be used, how they are valuable, and what some barriers may be to broader use. We found 6 main categories, or "use cases," for APIs in healthcare-patients, providers, administrative, public health, social services, and population-health. We also describe why these use cases are important, as well as barriers within each use case. As more and more health data are made available via APIs, these use cases will drive the success of these technological innovations. Objective Improving health data interoperability through application programming interfaces (APIs) is a focus of US policy initiatives and could have tremendous impact on many aspects of care delivery, such as innovation, operational efficiency, and patient-centered care. To better understand the landscape of API use cases, we interviewed US thought leaders involved in developing and implementing standard-based APIs. Materials and Methods We conducted semi-structured virtual interviews with US subject matter experts (SMEs) on APIs. SMEs were asked to describe API use cases along with value and barriers for each use case. Written summaries were checked by the SME and analyzed by the study team to identify findings and themes. Results We interviewed 12 SMEs representing diverse sectors of the US healthcare system, including academia, industry, public health agencies, electronic health record vendors, government, and standards organizations. Use cases for standards-based APIs fell into six categories: patient-facing,

关键词： interoperability FHIR application programming interfaces

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Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, applications, and Open Challenges

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IEEE ACCESS 2025年 13卷 61611-61640页

作者： Manthena, Harikha Shajarian, Shaghayegh Kimmell, Jeffrey C. Abdelsalam, Mahmoud Khorsandroo, Sajad Gupta, Maanak North Carolina Agr & Tech State Univ Comp Sci Dept Greensboro NC 27411 USA Tennessee Technol Univ Comp Sci Dept Cookeville TN 38505 USA

Machine learning (ML) has rapidly advanced in recent years, revolutionizing fields such as finance, medicine, and cybersecurity. In malware detection, ML-based approaches have demonstrated high accuracy;however, their lack of transparency poses a significant challenge. Traditional ML models often fail to provide interpretable justifications for their predictions, limiting their adoption in security-critical environments where understanding the reasoning behind a detection is essential for threat mitigation and response. Explainable AI (XAI) addresses this gap by enhancing model interpretability while maintaining strong detection capabilities. This survey presents a comprehensive review of state-of-the-art ML techniques for malware analysis, with a specific focus on explainability methods and research mainly from 2018 to 2024. We examine existing XAI frameworks, their application in malware classification and detection, and the challenges associated with making malware detection models more interpretable. Additionally, we explore recent advancements and highlight open research challenges in the field of explainable malware analysis. By providing a structured overview of XAI-driven malware detection approaches, this survey serves as a valuable resource for researchers and practitioners seeking to bridge the gap between ML performance and explainability in cybersecurity.

关键词： Malware Explainable AI Feature extraction Surveys Static analysis Accuracy Codes Computer security Heuristic algorithms application programming interfaces Explainable malware analysis interpretable malware analysis explainable AI AI for security malware detection malware classification

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RanViz: Ransomware Visualization and Classification Based on Time-Series Categorical Representation of API Calls

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IEEE ACCESS 2025年 13卷 56237-56254页

作者： Mokoma, Vhuhwavho Singh, Avinash Univ Pretoria Dept Comp Sci ZA-0002 Pretoria South Africa

Ransomware continues to pose a significant threat to individuals and organizations worldwide, causing disruptions, financial losses, and reputational damage. As ransomware attacks grow in sophistication, understanding their behaviour through effective analysis has become increasingly critical for mitigation and prevention. However, ransomware analysis presents several challenges. First, the sheer volume of application programming Interface (API) call data generated by ransomware during execution can overwhelm traditional analysis methods. Second, the temporal and categorical nature of this data makes identifying meaningful patterns complex. Third, the integration of machine learning (ML) models, which are essential for accurate classification, is hindered by the difficulty of modelling intricate API call behaviours. Without effective tools to address these issues, analysts risk missing critical behavioural indicators. To overcome these challenges, the proposed Ransomware Visualization (RanViz) system was developed to provide a comprehensive visual analytics and classification platform designed to enhance ransomware analysis. RanViz employs advanced visualization techniques to represent categorical API call time-series data, enabling analysts to intuitively understand ransomware behaviours that might otherwise remain obscured. The system incorporates ML models based on API call frequency, temporal interval, and sequence to classify unknown samples as either benign or ransomware. The models collectively achieve an accuracy of over 95% in detecting ransomware. By providing a unified platform that combines powerful visualization tools with high-performing ML models, RanViz simplifies ransomware analysis and offers a robust framework for accurate classification. This makes it an invaluable tool for digital forensics and cybersecurity professionals tasked with addressing the ever-evolving ransomware threat.

关键词： Ransomware Malware Data visualization application programming interfaces Encryption Visual analytics Organizations Computer security Complexity theory Ransomware analysis API calls machine learning ransomware time series visualization visualization

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