一句话：针对工具插桩困难和行为数据低层细粒度的问题，研究从未插桩应用交互中推断高层开发活动。
论文关注开发者行为数据收集与分析中的两个挑战：其一，在真实工作场景中，对IDE、Web浏览器等常用软件工具进行插桩往往困难且需要大量资源；其二，收集到的行为数据通常是低层、细粒度的事件序列，必须抽象为高层开发活动才能用于后续分析。为此，论文研究如何从与未插桩应用程序的交互中推断开发活动，以在不依赖广泛插桩的前提下获得高层活动信息。摘要未给出具体推断方法与实验评估，但其核心贡献在于提出并界定这一问题，为理解开发者行为、设计支持开发者的技术与工具提供基础。
Studying developers' behavior is crucial for designing effective techniques and tools to support developers' daily work. However, there are two challenges in collecting and analyzing developers' behavior data. First, instrumenting many software tools commonly used in real work settings (e.g., IDEs, web browsers) is difficult and requires significant resources. Second, the collected behavior data consist of low-level and fine-grained event sequences, which must be abstracted into high-level development activities for further analysis.
DOI 原文 ·
@inproceedings{paperbot4461,
title = {Inference of development activities from interaction with uninstrumented applications},
author = {Lingfeng Bao and Zhenchang Xing and Xin Xia and David Lo and Ahmed E. Hassan},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3182537}
}