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The fast-growing Web API landscape brings clients more options than ever before---in theory. In practice, they cannot easily switch between different providers offering similar functionality. We discuss a vision for developing Web APIs…

Conversational AI systems increasingly function as primary interfaces for information seeking, yet how they present sources to support information evaluation remains under-explored. This paper investigates how source transparency design…

While the recently emerged Microservices architectural style is widely discussed in literature, it is difficult to find clear guidance on the process of refactoring legacy applications. The importance of the topic is underpinned by high…

Recommender systems utilize users' historical data to learn and predict their future interests, providing them with suggestions tailored to their tastes. Calibration ensures that the distribution of recommended item categories is consistent…

Fragmentation is a serious problem in the Android ecosystem. This problem is mainly caused by the fast evolution of the system itself and the various customizations independently maintained by different smartphone manufacturers. Many…

With the development of deep learning (DL) techniques, rotating machinery intelligent diagnosis has gone through tremendous progress with verified success and the classification accuracies of many DL-based intelligent diagnosis algorithms…

Software development is getting changed so rapidly. It will be highly benefited if we can accelerate software development process by guiding developers. Appropriate guidelines and accurate recommendations to developers during development…

Context: Web APIs are one of the most used ways to expose application functionality on the Web, and their understandability is important for efficiently using the provided resources. While many API design rules exist, empirical evidence for…

Different software tools have been developed with the purpose of performing offline evaluations of recommender systems. However, the results obtained with these tools may be not directly comparable because of subtle differences in the…

The last several years have brought a growing body of work on ensuring that recommender systems are in some sense consumer-fair -- that is, they provide comparable quality of service, accuracy of representation, and other effects to their…

Algorithmic fairness is receiving significant attention in the academic and broader literature due to the increasing use of predictive algorithms, including those based on artificial intelligence. One benefit of this trend is that algorithm…

Evaluating the quality of retrieval-augmented generation (RAG) and document reranking systems remains challenging due to the lack of scalable, user-centric, and multi-perspective evaluation tools. We introduce RankArena, a unified platform…

Software developers study and reuse existing source code to understand how to properly use application programming interfaces (APIs). However, manually finding sufficient and adequate code examples for a given API is a difficult and a…

Patients increasingly rely on online reviews when choosing healthcare providers, yet the sheer volume of these reviews can hinder effective decision-making. This paper summarises a mixed-methods study aimed at evaluating a proposed…

Object-oriented Application Programing Interfaces (APIs) support software reuse by providing pre-implemented functionalities. Due to the huge number of included classes, reusing and understanding large APIs is a complex task. Otherwise,…

Explainable information retrieval is an emerging research area aiming to make transparent and trustworthy information retrieval systems. Given the increasing use of complex machine learning models in search systems, explainability is…

Deep research systems represent an emerging class of agentic information retrieval methods that generate comprehensive and well-supported reports to complex queries. However, most existing frameworks rely on dynamic commercial search APIs,…

Open Source Software projects add labels to open issues to help contributors choose tasks. However, manually labeling issues is time-consuming and error-prone. Current automatic approaches for creating labels are mostly limited to…

Trace alignment algorithms have been used in process mining for discovering the consensus treatment procedures and process deviations. Different alignment algorithms, however, may produce very different results. No widely-adopted method…

Automatic Web service composition is a research direction aimed to improve the process of aggregating multiple Web services to create some new, specific functionality. The use of semantics is required as the proper semantic model with…