Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Zahedi, Mansooreh"'
Context: Machine learning (ML) and deep learning (DL) analyze raw data to extract valuable insights in specific phases. The rise of continuous practices in software projects emphasizes automating Continuous Integration (CI) with these learning-based
Externí odkaz:
http://arxiv.org/abs/2406.19765
Background: The development of AI-enabled software heavily depends on AI model documentation, such as model cards, due to different domain expertise between software engineers and model developers. From an ethical standpoint, AI model documentation c
Externí odkaz:
http://arxiv.org/abs/2406.18071
Online research platforms, such as Prolific, offer rapid access to diverse participant pools but also pose unique challenges in participant qualification and skill verification. Previous studies reported mixed outcomes and challenges in leveraging on
Externí odkaz:
http://arxiv.org/abs/2402.01925
Autor:
Ferreyra, Nicolás E. Díaz, Shahin, Mojtaba, Zahedi, Mansooreh, Quadri, Sodiq, Scandariato, Ricardo
Self-Admitted Technical Debt (SATD) encompasses a wide array of sub-optimal design and implementation choices reported in software artefacts (e.g., code comments and commit messages) by developers themselves. Such reports have been central to the stu
Externí odkaz:
http://arxiv.org/abs/2401.12768
Autor:
Nasab, Ali Rezaei, Dashti, Maedeh, Shahin, Mojtaba, Zahedi, Mansooreh, Khalajzadeh, Hourieh, Arora, Chetan, Liang, Peng
Fairness is one of the socio-technical concerns that must be addressed in software systems. Considering the popularity of mobile software applications (apps) among a wide range of individuals worldwide, mobile apps with unfair behaviors and outcomes
Externí odkaz:
http://arxiv.org/abs/2401.08097
README files play an important role in providing installation-related instructions to software users and are widely used in open source software systems on platforms such as GitHub. However, these files often suffer from various documentation issues,
Externí odkaz:
http://arxiv.org/abs/2312.03250
Software documentation captures detailed knowledge about a software product, e.g., code, technologies, and design. It plays an important role in the coordination of development teams and in conveying ideas to various stakeholders. However, software d
Externí odkaz:
http://arxiv.org/abs/2308.09940
Background: Machine Learning (ML) methods are being increasingly used for automating different activities, e.g., Test Case Prioritization (TCP), of Continuous Integration (CI). However, ML models need frequent retraining as a result of changes in the
Externí odkaz:
http://arxiv.org/abs/2305.12736
This research conducted a systematic review of the literature on machine learning (ML)-based methods in the context of Continuous Integration (CI) over the past 22 years. The study aimed to identify and describe the techniques used in ML-based soluti
Externí odkaz:
http://arxiv.org/abs/2305.12695
Continuous Integration (CI) has become a well-established software development practice for automatically and continuously integrating code changes during software development. An increasing number of Machine Learning (ML) based approaches for automa
Externí odkaz:
http://arxiv.org/abs/2304.02829