Break to Adapt: Knowledge-Based Updates of Breaking Dependencies in JavaScript

Modern software libraries continually evolve to maintain activeness, improve performance, and enhance security. This evolution frequently introduces major version updates that include incompatible modifications (breaking changes), which often cause downstream projects to fail and significantly increase the effort required for maintenance. To reduce this burden on developers, recent studies propose automated approaches that leverage API characterization techniques and compilation error reports to guide LLM-based updates. However, these methods rely on static typing and compilation feedback, which are not available in dynamic languages such as JavaScript. As a result, when applied to JavaScript, they degrade to a knowledge-free setting and cannot effectively support automated dependency updates. In this paper, we propose a knowledge-based approach that mines explicit update knowledge, referred to as breaking change records, from library repositories to support automated dependency updates in the presence of breaking changes (i.e., breaking dependency updates). We first conduct an empirical investigation of how breaking change records are maintained in top-ranked JavaScript libraries. Our study reveals that 83.8% of libraries maintain such records within their repositories, often spread across multiple locations. However, the quality of these records varies considerably, with issues such as implicit references to changed objects and vague adaptation instructions. To address this issue, we systematically characterize breaking change records by identifying recurring patterns in both their locations and the types of information they convey. Building on these insights, we develop BDUpdater, an agent based framework that aggregates repository sources and refines raw records into structured breaking change lists, thereby mitigating the absence of API differencing tools. Leveraging this mined knowledge, BDUpdater pinpoints changed objects and statically identifies the affected client code, while supplying fine-grained change information to LLMs to guide accurate client code migration in the absence of compilation error messages. Our evaluation on 13 popular JavaScript libraries and 84 clients shows that BDUpdater recovers 90.5% of the breaking dependency updates with high semantic equivalence to developer-authored adaptations, while incurring an average cost of only $0.05 per client.