Machine Learning for Dynamic Software Analysis: Potentials and Limits

2018 ◽  
Keyword(s):  
Machine Learning ◽  
Software Analysis ◽  
Dynamic Software

scholarly journals A Study on Framework for Anti-Pattern Evaluation of System Software

2021 ◽  
Vol 9 (12) ◽  
pp. 1990-1995
Author(s):  
Shaik Mastanvali
Keyword(s):  
Machine Learning ◽  
Design Pattern ◽  
Design Patterns ◽  
Quality Characteristics ◽  
Machine Learning Method ◽  
Software Performance ◽  
Software Analysis ◽  
Confounding Variables ◽  
Dynamic Software ◽  
Implementation Problems

Abstract: Studies with a variety of viewpoints, goals, measurements, and quality characteristics have been conducted in order to determine the effect of design patterns on quality attributes. This has resulted in findings that are contradictory and difficult to compare. They want to explain these findings by taking into account confounding variables, practises, measurements, and implementation problems that have an impact on quality. Furthermore, there is a paucity of research that establishes a link between design pattern assessments and pattern creation studies, which is a significant limitation. For the purpose of detecting and categorising software performance anti-patterns, this article proposes a non-intrusive machine learning method dubbed Non-intrusive Performance Anti-pattern Detector (NiPAD). Keywords: software performance, anti-patterns, classification, machine learning, dynamic software analysis

scholarly journals Searching for improvements in predicting human eye colour from DNA

2021 ◽  
Author(s):  
Magdalena Kukla-Bartoszek ◽  
Paweł Teisseyre ◽  
Ewelina Pośpiech ◽  
Joanna Karłowska-Pik ◽  
Piotr Zieliński ◽  
...  
Keyword(s):  
Machine Learning ◽  
Regression Models ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Sequencing Analysis ◽  
Learning Approaches ◽  
Human Eye ◽  
Software Analysis ◽  
Whole Exome ◽  
Eye Colour

AbstractIncreasing understanding of human genome variability allows for better use of the predictive potential of DNA. An obvious direct application is the prediction of the physical phenotypes. Significant success has been achieved, especially in predicting pigmentation characteristics, but the inference of some phenotypes is still challenging. In search of further improvements in predicting human eye colour, we conducted whole-exome (enriched in regulome) sequencing of 150 Polish samples to discover new markers. For this, we adopted quantitative characterization of eye colour phenotypes using high-resolution photographic images of the iris in combination with DIAT software analysis. An independent set of 849 samples was used for subsequent predictive modelling. Newly identified candidates and 114 additional literature-based selected SNPs, previously associated with pigmentation, and advanced machine learning algorithms were used. Whole-exome sequencing analysis found 27 previously unreported candidate SNP markers for eye colour. The highest overall prediction accuracies were achieved with LASSO-regularized and BIC-based selected regression models. A new candidate variant, rs2253104, located in the ARFIP2 gene and identified with the HyperLasso method, revealed predictive potential and was included in the best-performing regression models. Advanced machine learning approaches showed a significant increase in sensitivity of intermediate eye colour prediction (up to 39%) compared to 0% obtained for the original IrisPlex model. We identified a new potential predictor of eye colour and evaluated several widely used advanced machine learning algorithms in predictive analysis of this trait. Our results provide useful hints for developing future predictive models for eye colour in forensic and anthropological studies.

scholarly journals Improving dynamic software analysis by applying grammar inference principles

2008 ◽  
Vol 20 (4) ◽  
pp. 269-290 ◽  
Author(s):  
Neil Walkinshaw ◽  
Kirill Bogdanov ◽  
Mike Holcombe ◽  
Sarah Salahuddin
Keyword(s):  
Software Analysis ◽  
Grammar Inference ◽  
Dynamic Software

scholarly journals An approach to assessment of dynamic software variability in mobile applications development

2018 ◽  
Keyword(s):  
Machine Learning ◽  
Programming Language ◽  
Mobile Applications ◽  
Product Line ◽  
Number Of Children ◽  
Java Programming ◽  
Complexity Metrics ◽  
Programming Tools ◽  
Dynamic Software ◽  
Code Complexity

The article describes the approach to the assessment of code reuse in Dynamic Product Line lines (DSPL). Some existing mechanisms to realize software variability in DSPL, such as machine learning, adaptive configurations based on Java programming tools which allow developing DSPL, especially in mobile applications domain, have been reviewed. During the development, some methods for the implementation of the variability specific to the selected programming language have been tested. For each of these mechanisms, such as Weighted Methods per Class, Response for a Class, Depth of Inheritance Tree, Coupling Between Objects, Number of Children, the code complexity metrics have been calculated. Based on these results the code reusability extent can be estimated for each of given variation mechanisms.

scholarly journals Quality Metrics measurement for Hybrid Systems (Aspect Oriented Programming – Object Oriented Programming)

2021 ◽  
Vol 3 (3) ◽  
pp. 82-99
Author(s):  
Mazen Ismaeel Ghareb ◽  
Gary Allen
Keyword(s):  
Software Metrics ◽  
Object Oriented ◽  
Quality Metrics ◽  
Object Oriented Programming ◽  
Software Analysis ◽  
Programming Software ◽  
Dynamic Software ◽  
Software Quality Metrics ◽  
Dynamic Metrics ◽  
New Framework

This paper explores a new framework for calculating hybrid system metrics using software quality metrics aspect-oriented and object-oriented programming. Software metrics for qualitative and quantitative measurement is a mix of static and dynamic software metrics. It is noticed from the literature survey that to date, most of the architecture considered only the evaluation focused on static metrics for aspect-oriented applications. In our work, we mainly discussed the collection of static parameters ,  long with AspectJ-specific dynamic software metrics.The structure may provide a new direction for research while predicting software attributes because earlier dynamic metrics were ignored when evaluating quality attributes such as maintainability, reliability, and understandability of Asepect Oriented software. Dynamic metrics based on the  fundamentals of software engineering are equally crucial for software analysis as are static metrics. A similar concept is borrowed with the introduction of dynamic software metrics to implement aspect-riented software development.Currently, we only propose a structure and model using static and dynamic parameters to test the aspect-oriented method, but we still need to validate the proposed approach.

scholarly journals Determining Microservice Boundaries: A Case Study Using Static and Dynamic Software Analysis

2020 ◽  
pp. 315-332
Author(s):  
Tiago Matias ◽  
Filipe F. Correia ◽  
Jonas Fritzsch ◽  
Justus Bogner ◽  
Hugo S. Ferreira ◽  
...  
Keyword(s):  
Software Analysis ◽  
Dynamic Software
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