Effects of Visualizing Technical Debts on a Software Maintenance Project
November 18, 2019 Β· Declared Dead Β· π Brazilian Symposium on Software Quality
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ronivon Dias, Pedro Neto, Irvayne Ibiapina, Guilherme Avelino e Otavio Castro
arXiv ID
1911.07565
Category
cs.SE: Software Engineering
Cross-listed
cs.HC
Citations
1
Venue
Brazilian Symposium on Software Quality
Last Checked
5 months ago
Abstract
The technical debt (TD) metaphor is widely used to encapsulate numerous software quality problems. She describes the trade-off between the short term benefit of taking a shortcut during the design or implementation phase of a software product (for example, in order to meet a deadline) and the long term consequences of taking said shortcut, which may affect the quality of the software product. TDs must be managed to guarantee the software quality and also reduce its maintenance and evolution costs. However, the tools for TD detection usually provide results only considering the files perspective (class and methods), that is not usual during the project management. In this work, a technique is proposed to identify/visualize TD on a new perspective: software features. The proposed technique adopts Mining Software Repository (MRS) tools to identify the software features and after the technical debts that affect these features. Additionally, we also proposed an approach to support maintenance tasks guided by TD visualization at the feature level aiming to evaluate its applicability on real software projects. The results indicate that the approach can be useful to decrease the existent TDs, as well as avoid the introduction of new TDs.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted