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- research-articleFebruary 2024
A Codebert Based Empirical Framework for Evaluating Classification-Enabled Vulnerability Prediction Models
ISEC '24: Proceedings of the 17th Innovations in Software Engineering ConferenceArticle No.: 6, Pages 1–11https://doi.org/10.1145/3641399.3641405Software vulnerabilities are discovered quite frequently and cause substantial damage and security breaches. In the realm of cybersecurity, the detection of vulnerabilities plays a pivotal role in safeguarding critical systems and data. In this paper, ...
- research-articleAugust 2023
Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction
- Sonika Chandrakant Rathi,
- Sanjay Misra,
- Ricardo Colomo-Palacios,
- R. Adarsh,
- Lalita Bhanu Murthy Neti,
- Lov Kumar
Expert Systems with Applications: An International Journal (EXWA), Volume 223, Issue Chttps://doi.org/10.1016/j.eswa.2023.119806Abstract Context:The application of Software Fault Prediction (SFP) in the software development life cycle to predict the faulty class at the early stage has piqued the interest of various scholars. In the SFP domain, during research analysis, it got ...
- research-articleFebruary 2023
A Comparative Analysis on the Detection of Web Service Anti-Patterns Using Various Metrics
ISEC '23: Proceedings of the 16th Innovations in Software Engineering ConferenceArticle No.: 10, Pages 1–7https://doi.org/10.1145/3578527.3578534Nowadays, the application of machine learning for developing prediction models is one of the most critical research areas. Early prediction of anti-patterns using machine learning can help developers, and testers fix the design issues and utilize the ...
- research-articleAugust 2022
Detection of web service anti-patterns using weighted extreme learning machine
Computer Standards & Interfaces (CSAI), Volume 82, Issue Chttps://doi.org/10.1016/j.csi.2022.103621Highlights- The web service anti-pattern prediction model developed using Weighted Extreme Learning Machine algorithm (WELM) provides better performance compared to the ...
‘Anti-Pattern’ is a term often used by software engineers and practitioners nowadays. An anti-pattern is a supplement of the design pattern. Similar to design patterns, an anti-pattern is a template and a repeatable way of solving a ...
- ArticleJuly 2022
Software Functional Requirements Classification Using Ensemble Learning
Computational Science and Its Applications – ICCSA 2022 WorkshopsPages 678–691https://doi.org/10.1007/978-3-031-10548-7_49AbstractSoftware requirement classification is crucial in segregating the user requirements into functional and quality requirements, based on their feedback or client demand. Doing so manually is time-consuming and not feasible. This can lead to delays ...
- ArticleJuly 2022
Software Sentiment Analysis Using Machine Learning with Different Word-Embedding
- Venkata Krishna Chandra Mula,
- Sanidhya Vijayvargiya,
- Lov Kumar,
- Surender Singh Samant,
- Lalita Bhanu Murthy
Computational Science and Its Applications – ICCSA 2022 WorkshopsPages 396–410https://doi.org/10.1007/978-3-031-10548-7_29AbstractSoftware sentiment analysis has applications in numerous software engineering tasks ranging from code suggestions to evaluating app reviews which help to save the development team valuable time and increase productivity. In recent years, sentiment ...
- articleMay 2022
Cross-Project Software Refactoring Prediction Using Optimized Deep Learning Neural Network With the Aid of Attribute Selection
International Journal of Open Source Software and Processes (IJOSSP-IGI), Volume 13, Issue 1Pages 1–31https://doi.org/10.4018/IJOSSP.300756Cross-project refactoring prediction is prominent research that comprises model training from one project database and testing it for a database under a separate project. While performing the refactoring process on the cross project, software programs ...
- ArticleSeptember 2021
Empirical Analysis on Effectiveness of NLP Methods for Predicting Code Smell
Computational Science and Its Applications – ICCSA 2021Pages 43–53https://doi.org/10.1007/978-3-030-87013-3_4AbstractA code smell is a surface indicator of an inherent problem in the system, most often due to deviation from standard coding practices on the developer’s part during the development phase. Studies observe that code smells made the code more ...
- ArticleSeptember 2021
Deep-Learning Approach with DeepXplore for Software Defect Severity Level Prediction
- Lov Kumar,
- Triyasha Ghosh Dastidar,
- Lalitha Bhanu Murthy Neti,
- Shashank Mouli Satapathy,
- Sanjay Misra,
- Vipul Kocher,
- Srinivas Padmanabhuni
Computational Science and Its Applications – ICCSA 2021Pages 398–410https://doi.org/10.1007/978-3-030-87007-2_28AbstractFixing the defects of earlier releases and working on fast and efficient fixing of those software defects is detrimental for the release of further versions. Bug tracking systems like Bugzilla get thousands of software defect reports every day. ...
- ArticleSeptember 2021
An Empirical Analysis on the Prediction of Web Service Anti-patterns Using Source Code Metrics and Ensemble Techniques
Computational Science and Its Applications – ICCSA 2021Pages 263–276https://doi.org/10.1007/978-3-030-87007-2_19AbstractToday’s software program enterprise uses web services to construct distributed software systems based on the Service Oriented Architecture (SOA) paradigm. The web service description is posted by a web service provider, which may be observed and ...
- ArticleSeptember 2021
A Novel Approach for the Detection of Web Service Anti-Patterns Using Word Embedding Techniques
Computational Science and Its Applications – ICCSA 2021Pages 217–230https://doi.org/10.1007/978-3-030-87007-2_16AbstractAn anti-pattern is defined as a standard but ineffective solution to solve a problem. Anti-patterns in software design make it hard for software maintenance and development by making source code very complicated for understanding. Various studies ...
- short-paperApril 2021
An Empirical Study to investigate the Effectiveness of Different Variants of SMOTE for Improving Web Service Anti-Patterns Prediction
ISEC '21: Proceedings of the 14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)Article No.: 19, Pages 1–5https://doi.org/10.1145/3452383.3452410In today’s world, IT professionals must ensure that all enterprise applications are running smoothly and are communicating with each other. Service-Oriented Architecture(SOA) provides the organization with a framework that makes the management of ...
- research-articleMarch 2020
Prediction of Web Service Anti-patterns Using Aggregate Software Metrics and Machine Learning Techniques
ISEC '20: Proceedings of the 13th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)Article No.: 8, Pages 1–11https://doi.org/10.1145/3385032.3385042Service-Oriented Architecture(SOA) can be characterized as an approximately coupled engineering intended to meet the business needs of an association/organization. Service-Based Systems (SBSs) are inclined to continually change to enjoy new client ...
- research-articleFebruary 2019
Change-Proneness of Object-Oriented Software Using Combination of Feature Selection Techniques and Ensemble Learning Techniques
ISEC '19: Proceedings of the 12th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)Article No.: 8, Pages 1–11https://doi.org/10.1145/3299771.3299778Change-prone modules are characterized as the programming parts in the source code which have high probability to alter in the future. Change-proneness prediction helps software testers to streamline and concentrate their testing assets on the modules ...
- research-articleFebruary 2019
Method Level Refactoring Prediction on Five Open Source Java Projects using Machine Learning Techniques
ISEC '19: Proceedings of the 12th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)Article No.: 7, Pages 1–10https://doi.org/10.1145/3299771.3299777Introduction: Identifying code segments in large and complex systems in need of refactoring is non-trivial for software developers. Our research aim is to develop recommendation systems for suggesting methods which require refactoring. Materials and ...
- research-articleJanuary 2019
Software reusability metrics prediction and cost estimation by using machine learning algorithms
International Journal of Knowledge-based and Intelligent Engineering Systems (KIES), Volume 23, Issue 4Pages 317–328https://doi.org/10.3233/KES-190421In this research, a highly robust and efficient software design optimization model has been proposed for object-oriented programming based software solutions while considering the importance of quality and reliability. Due to a piece of ...
- research-articleFebruary 2018
Feature Selection Techniques to Counter Class Imbalance Problem for Aging Related Bug Prediction: Aging Related Bug Prediction
ISEC '18: Proceedings of the 11th Innovations in Software Engineering ConferenceArticle No.: 2, Pages 1–11https://doi.org/10.1145/3172871.3172872Aging-Related Bugs (ARBs) occur in long running systems due to error conditions caused because of accumulation of problems such as memory leakage or unreleased files and locks. Aging-Related Bugs are hard to discover during software testing and also ...