Representing concerns in source code

Author:

Robillard Martin P.1,Murphy Gail C.2

Affiliation:

1. McGill University, Montreal, QC, Canada

2. University of British Columbia, Vancouver, BC, Canada

Abstract

A software modification task often addresses several concerns . A concern is anything a stakeholder may want to consider as a conceptual unit, including features, nonfunctional requirements, and design idioms. In many cases, the source code implementing a concern is not encapsulated in a single programming language module, and is instead scattered and tangled throughout a system. Inadequate separation of concerns increases the difficulty of evolving software in a correct and cost-effective manner. To make it easier to modify concerns that are not well modularized, we propose an approach in which the implementation of concerns is documented in artifacts, called concern graphs. Concern graphs are abstract models that describe which parts of the source code are relevant to different concerns. We present a formal model for concern graphs and the tool support we developed to enable software developers to create and use concern graphs during software evolution tasks. We report on five empirical studies, providing evidence that concern graphs support views and operations that facilitate the task of modifying the code implementing scattered concerns, are cost-effective to create and use, and robust enough to be used with different versions of a software system.

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Cited by 100 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. FeatRacer: Locating Features Through Assisted Traceability;IEEE Transactions on Software Engineering;2023-12

2. Capturing Contextual Relationships of Buggy Classes for Detecting Quality-Related Bugs;2023 IEEE International Conference on Software Maintenance and Evolution (ICSME);2023-10-01

3. Too Simple? Notions of Task Complexity used in Maintenance-based Studies of Programming Tools;2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC);2023-05

4. Detecting Scattered and Tangled Quality Concerns in Source Code to Aid Maintenance and Evolution Tasks;2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion);2023-05

5. A Hierarchical Topical Modeling Approach for Recommending Repair of Quality Bugs;2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER);2023-03

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3