AI-Based Software Defect Prediction for Trustworthy Android Apps
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00126420" target="_blank" >RIV/00216224:14330/22:00126420 - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/pdf/10.1145/3530019.3531330" target="_blank" >https://dl.acm.org/doi/pdf/10.1145/3530019.3531330</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3530019.3531330" target="_blank" >10.1145/3530019.3531330</a>
Alternative languages
Result language
angličtina
Original language name
AI-Based Software Defect Prediction for Trustworthy Android Apps
Original language description
The present time in the industry is a time where Android Applications are in a wide range with its widespread of the users also. With the increased use of Android applications, the defects in the Android context have also been increasing. The malware of defective software can be any pernicious program with malignant effects. Many techniques based on static, dynamic, and hybrid approaches have been proposed with the combination of Machine learning (ML) or Artificial Intelligence (AI) techniques. In this regard. Scientifically, it is complicated to examine the malignant effects. A single approach cannot predict defects alone, so multiple approaches must be used simultaneously. However, the proposed techniques do not describe the types of defects they address. The paper aims to propose a framework that classifies the defects. The Artificial Intelligence (AI) techniques are described, and the different defects are mapped to them. The mapping of defects to AI techniques is based on the types of defects found in the Android Context. The accuracy of the techniques and the working criteria has been set as the mapping metrics. This will significantly improve the quality and testing of the product. However, the appropriate technique for a particular type of defect could be easily selected. This will reduce the cost and time efforts put into predicting defects.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Conference on Evaluation and Assessment in Software Engineering 2022
ISBN
9781450396134
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
393-398
Publisher name
ACM
Place of publication
New York, USA
Event location
New York, USA
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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