Purpose This study aims to identify the developer's objectives, current state-of-the-art
techniques, challenges and performance evaluation metrics, and presents outlines of a …

Learning and remembering how to use APIs is difficult. While code-completion tools can
recommend API methods, browsing a long list of API method names and their …

Nowadays software applications, and especially mobile apps, undergo frequent release
updates through app stores. After installing/updating apps, users can post reviews and …

Third-party libraries play a key role in software development as they can relieve developers
of the heavy burden of re-implementing common functionalities. However, third-party …

Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using
learned models, ie, Software-2.0, has gained substantial adoption. However, we do not …

Purpose: With this Systematic Literature Review (SLR), we aim to discover technologies to
construct a Goal-Question-Metrics (GQM) based metrics recommender for software …

Traditional code search engines often do not perform well with natural language queries
since they mostly apply keyword matching. These engines thus need carefully designed …

Automatic API recommendation has been studied for years. There are two orthogonal lines
of approaches for this task, ie, information-retrieval-based (IR-based) and neural-based …

As code search is a frequent developer activity in software development practices, improving
the performance of code search is a critical task. In the text retrieval based search …

In recent software development and distribution scenarios, app stores are playing a major
role, especially for mobile apps. On one hand, app stores allow continuous releases of app …