INFORMATION AND SOFTWARE TECHNOLOGY

期刊名
INFORMATION AND SOFTWARE TECHNOLOGY

INFORM SOFTWARE TECH

ISSN / eISSN
0950-5849
目标和范围
Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal's scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include:

• Software management, quality and metrics,
• Software processes,
• Software architecture, modelling, specification, design and programming
• Functional and non-functional software requirements
• Software testing and verification & validation
• Empirical studies of all aspects of engineering and managing software development

Short Communications is a new section dedicated to short papers addressing new ideas, controversial opinions, "Negative" results and much more. Read the Guide for authors for more information.

The journal encourages and welcomes submissions of systematic literature studies (reviews and maps) within the scope of the journal. Information and Software Technology is the premiere outlet for systematic literature studies in software engineering.
研究方向

计算机:信息系统

计算机:软件工程

CiteScore
9.10 查看趋势图
CiteScore 学科排名
类别 分区 排名
Computer Science - Computer Science Applications Q1 #123/817
Computer Science - Information Systems Q1 #66/394
Computer Science - Software Q1 #69/407
Web of Science 核心收藏夹
Science Citation Index Expanded (SCIE) Social Sciences Citation Index (SSCI)
Indexed -
类别 (Journal Citation Reports 2024) 分区
COMPUTER SCIENCE, INFORMATION SYSTEMS Q2
COMPUTER SCIENCE, SOFTWARE ENGINEERING Q1
H-index
88
出版国家或地区
NETHERLANDS
出版商
Elsevier
出版周期
Monthly
年文章数
164
Open Access
NO
通讯方式
ELSEVIER SCIENCE BV, PO BOX 211, AMSTERDAM, NETHERLANDS, 1000 AE
认证评论
注: 认证评论选取于全球各个学术评论平台和社交媒体。
August 2020 submission
January 2021 minor revision
April 2022 acceptance
Quanyi Zou, et al. "Joint feature representation learning and progressive distribution matching for cross-project defect prediction." Information and Software Technology (2021).
2021-04-12

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