Detecting Scattered and Tangled Quality Concerns in Source Code to Aid Maintenance and Evolution Tasks. Krasniqi, R. In 2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), pages 184–188, Melbourne, Australia, May, 2023. IEEE. ![Detecting Scattered and Tangled Quality Concerns in Source Code to Aid Maintenance and Evolution Tasks [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 5 downloads Quality concerns, such as reliability, security, usability concerns, among others, are typically well-defined and prioritized at the requirement level with the set goal of achieving high quality, robust, user-friendly, and trustworthy systems. However, quality concerns are challenging to address at the implementation level. Often they are scattered across multiple modules in the codebase. In other instances, they are tangled with functional ones within a single module. Reasoning about quality concerns and their interactions with functional ones while being hindered by the effects of scattered and tangled code can only yield to more unseen problems. For example, developers can inadvertently retrofit new bugs or wrongly implement new features that deviate from original system requirement specifications. The goal of this thesis is twofold. First, we aim to detect quality concerns implemented at code level to differentiate them from functional ones when they are scattered across the codebase. Second, we aim to untangle quality concerns from unrelated changes to gain a detailed knowledge about the history of specific quality changes. This knowledge is crucial to support consistency between the requirements-and-design and to verify architecture conformance. From the practical stance, developers could gain a breadth of understanding about quality concerns and their relations with other artifacts. Thus, with more confidence, they could perform code modifications, improve module traceability, and provide a better holistic assessment of change impact analysis.
@inproceedings{krasniqi_detecting_2023,
address = {Melbourne, Australia},
title = {Detecting {Scattered} and {Tangled} {Quality} {Concerns} in {Source} {Code} to {Aid} {Maintenance} and {Evolution} {Tasks}},
isbn = {9798350322637},
url = {https://ieeexplore.ieee.org/document/10172720/},
doi = {10.1109/ICSE-Companion58688.2023.00051},
abstract = {Quality concerns, such as reliability, security, usability concerns, among others, are typically well-defined and prioritized at the requirement level with the set goal of achieving high quality, robust, user-friendly, and trustworthy systems. However, quality concerns are challenging to address at the implementation level. Often they are scattered across multiple modules in the codebase. In other instances, they are tangled with functional ones within a single module. Reasoning about quality concerns and their interactions with functional ones while being hindered by the effects of scattered and tangled code can only yield to more unseen problems. For example, developers can inadvertently retrofit new bugs or wrongly implement new features that deviate from original system requirement specifications. The goal of this thesis is twofold. First, we aim to detect quality concerns implemented at code level to differentiate them from functional ones when they are scattered across the codebase. Second, we aim to untangle quality concerns from unrelated changes to gain a detailed knowledge about the history of specific quality changes. This knowledge is crucial to support consistency between the requirements-and-design and to verify architecture conformance. From the practical stance, developers could gain a breadth of understanding about quality concerns and their relations with other artifacts. Thus, with more confidence, they could perform code modifications, improve module traceability, and provide a better holistic assessment of change impact analysis.},
language = {en},
urldate = {2023-07-20},
booktitle = {2023 {IEEE}/{ACM} 45th {International} {Conference} on {Software} {Engineering}: {Companion} {Proceedings} ({ICSE}-{Companion})},
publisher = {IEEE},
author = {Krasniqi, Rrezarta},
month = may,
year = {2023},
keywords = {Conference Short Papers},
pages = {184--188},
}
Downloads: 5
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