Recovering variability information from the source code of similar software products

2012 ◽  
Author(s):  
Slawomir Duszynski ◽  
Martin Becker
Keyword(s):  
Source Code ◽  
Software Products

An Investigation on Quality Perspective of Software Functional Artifacts

2020 ◽  
pp. 109-133
Author(s):  
Vimaladevi M. ◽  
Zayaraz G.
Keyword(s):  
Quality Improvement ◽  
Source Code ◽  
Quality Analysis ◽  
Complex Nature ◽  
Design Development ◽  
Software Products ◽  
Intelligent Software ◽  
Software Engineering Process ◽  
Automated Technique ◽  
The Cost

Software engineering process and practices paramount the crisis of cost, quality, and schedule constraints in developing software products. This chapter surveys the quality improvement techniques for the two fundamental artifacts of software product development, namely the architecture design and the source code. The information from top level research databases are compiled and an overall picture of quality enhancement in current software trends during the design, development, and maintenance phases are presented. This helps both the software developers and the quality analysts to gain understanding of the current state of the art for quality improvement of design and source code and the usage of various practices. The results indicate the need for more realistic, precise, automated technique for architectural quality analysis. The complex nature of the current software products requires the system developed to be beyond robust and resilient and building intelligent software that is anti-fragile and self-adaptive is favored. Innovative proposals that reduce the cost and time are invited.

scholarly journals Resolving Code Smells in Software Product Line using Refactoring and Reverse Engineering

2020 ◽  
Author(s):  
Sami Ouali
Keyword(s):  
Reverse Engineering ◽  
Source Code ◽  
Software Product Line ◽  
Product Line ◽  
Production Costs ◽  
Code Smells ◽  
Product Lines ◽  
Software Products ◽  
Software Product ◽  
External Behavior

Software Product Lines (SPL) are recognized as a successful approach to reuse in software development. Its purpose is to reduce production costs. This approach allows products to be different with respect of particular characteristics and constraints in order to cover different markets. Software Product Line engineering is the production process in product lines. It exploits the commonalities between software products, but also to preserve the ability to vary the functionality between these products. Sometimes, an inappropriate implementation of SPL during this process can conduct to code smells or code anomalies. Code smells are considered as problems in source code which can have an impact on the quality of the derived products of an SPL. The same problem can be present in many derived products from an SPL due to reuse. A possible solution to this problem can be the refactoring which can improve the internal structure of source code without altering external behavior. This paper proposes an approach for building SPL from source code. Its purpose is to reduce code smells in the obtained SPL using refactoring source code. Another part of the approach consists on obtained SPL’s design based on reverse engineering.

scholarly journals Towards Automatic Updates of Software Dependencies based on Artificial Intelligence

2020 ◽  
Vol V (III) ◽  
pp. 174-180
Author(s):  
Naveed Jhamat ◽  
Zeeshan Arshad ◽  
Kashif Riaz
Keyword(s):  
Current Knowledge ◽  
Source Code ◽  
Third Party ◽  
Management Tools ◽  
Software Products ◽  
Code Refactoring ◽  
Software Reusability ◽  
Software Code ◽  
Dependency Management ◽  
And Performance

Software reusability encourages developers to heavily rely on a variety of third-party libraries and packages, resulting in dependent software products. Often ignored by developers due to the risk of breakage but dependent software have to adopt security and performance updates in their external dependencies. Existing work advocates a shift towards Automatic updation of dependent software code to implement update dependencies. Emerging automatic dependency management tools notify the availability of new updates, detect their impacts on dependent software and identify potential breakages or other vulnerabilities. However, support for automatic source code refactoring to fix potential breaking changes (to the best of my current knowledge) is missing from these tools. This paper presents a prototyping tool, DepRefactor, that assist in the programmed refactoring of software code caused by automatic updating of their dependencies. To measure the accuracy and effectiveness of DepRefactor, we test it on various students project developed in C#.

scholarly journals Automatic Calculation of Process Metrics and their Bug Prediction Capabilities

2017 ◽  
Vol 23 (2) ◽  
pp. 537-559
Author(s):  
Péter Gyimesi
Keyword(s):  
Open Source ◽  
Query Language ◽  
Source Code ◽  
Positional Information ◽  
Machine Learning Algorithms ◽  
Graph Database ◽  
Software Products ◽  
Online Appendix ◽  
Process Metrics ◽  
Time Required

Identifying fault-prone code parts is useful for the developers to help reduce the time required for locating bugs. It is usually done by characterizing the already known bugs with certain kinds of metrics and building a predictive model from the data. For the characterization of bugs, software product and process metrics are the most popular ones. The calculation of product metrics is supported by many free and commercial software products. However, tools that are capable of computing process metrics are quite rare. In this study, we present a method of computing software process metrics in a graph database. We describe the schema of the database created and we present a way to readily get the process metrics from it. With this technique, process metrics can be calculated at the file, class and method levels. We used GitHub as the source of the change history and we selected 5 open-source Java projects for processing. To retrieve positional information about the classes and methods, we used SourceMeter, a static source code analyzer tool. We used Neo4j as the graph database engine, and its query language - cypher - to get the process metrics. We published the tools we created as open-source projects on GitHub. To demonstrate the utility of our tools, we selected 25 release versions of the 5 Java projects and calculated the process metrics for all of the source code elements (files, classes and methods) in these versions. Using our previous published bug database, we built bug databases for the selected projects that contain the computed process metrics and the corresponding bug numbers for files and classes. (We published these databases as an online appendix.) Then we applied 13 machine learning algorithms on the database we created to find out if it is feasible for bug prediction purposes. We achieved F-measure values on average of around 0.7 at the class level, and slightly better values of between 0.7 and 0.75 at the file level. The best performing algorithm was the RandomForest method for both cases.

scholarly journals Role of Open Source Software in Modern Development of Enterprise Information Systems

2021 ◽  
Vol 21 (2) ◽  
pp. 16-22
Author(s):  
A.A. Shinkarev ◽  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Source Code ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Software Products ◽  
Modern Development ◽  
Software Product ◽  
The Moment ◽  
Product Package

At the moment there are many open source software products and packages, and their number is increasing every day. So it can be concluded that publishing source code is becoming more and more popular in the world of software development. When publishing the source code of a software solution or software package for use in the developer community, special attention should be given to the license type – this affects which scenarios will be available for use of the published package or software solution. It is also necessary to draw up full and detailed documentation and decide on the ways to promote the published package among developers. The purpose of the study was to justify the feasibility and necessity of publishing software products, packages and libraries for their use by other developers to build their own systems and services. The author meant to describe the major open source licenses, identify their features and differences, and those situations for which this or that type of license is suitable, as well as to demonstrate the need of writing documentation and describe ways to promote and popularize published software products, packages, and libraries in the developer community. Materials and methods. The paper considers official license documents describing conditions of use, reproduction, and distribution. The author analyzes the main ways and means to promote open source software products. Results. The article substantiates the relevance of publishing and using the source code of a software product, package or library. The author describes the main provisions of the most common licenses and gives advice on choosing the type of license when publishing source code for free use. The necessity of writing documentation for the published software product is substantiated. The article also describes some of the ways to promote published packages, such as the choice of name, speaking at conferences, and publishing articles with case studies.

Feedback2Code: A Deep Learning Approach to Identifying User-Feedback-Related Source Code Files

2020 ◽  
Vol 30 (01) ◽  
pp. 1-22
Author(s):  
Shuhan Yan ◽  
Tianjiao Du ◽  
Beijun Shen ◽  
Yuting Chen ◽  
Zhilei Ren
Keyword(s):  
Deep Learning ◽  
Open Source ◽  
Software Maintenance ◽  
Source Code ◽  
User Feedback ◽  
Software Systems ◽  
Learning Approach ◽  
Software Products ◽  
Process Feedback ◽  
Core Idea

Users frequently raise feedback when using software products. Feedback from users regarding their experiences and expectations and software defects they found adds values to software maintenance and evolution — software managers collect user feedback and then dispatch feedback issues that developers (and/or maintainers) need to track and process. Feedback tracking is often supported by open source platforms and collaborative software systems. Meanwhile, there still exists a gap between feedback issues and source code: since user feedback is usually informal and arbitrary, engineers have to spend much effort on comprehending issues and identifying which source code files need to be improved or fixed. This paper introduces a deep learning approach, Feedback2Code , which facilitates identification of user-feedback-related source code files. The core idea is to (1) explore latent semantics of user feedback and source code using several deep learning techniques such as Multi-Layer Perceptron (MLP), Convolutional Neutral Network (CNN) and skip-gram and (2) establish a multi-correlation model to explore linkages between feedback issues and source code files. Given a feedback issue, the linkages then allow engineers to identify source code files that are highly relevant to the issue. We have implemented Feedback2Code and evaluated it against ChangeAdvisor (a state-of-the-art approach) on 24 open source projects. The evaluation results clearly show the strength of Feedback2Code : for 103793 feedback issues, Feedback2Code successfully established 101190 feedback-code linkages and achieved a precision that is [Formula: see text] higher than that of ChangeAdvisor . Feedback2Code also achieved an MRR and an MAP that are [Formula: see text] and [Formula: see text] higher than those of ChangeAdvisor , respectively. Furthermore, we also found that a Feedback2Code -trained model can be easily transferred, allowing feedback-code linkages to be established in new projects with a little history data.

IMPLEMENTATION OF STEGANOGRAPHIC INFORMATION PROTECTION METHOD IN SOFTWARE DEVELOPMENT

2020 ◽  
Author(s):  
В.Е. Радынская
Keyword(s):  
Software Development ◽  
Source Code ◽  
Digital Watermark ◽  
Significant Loss ◽  
Information Protection ◽  
Software Products ◽  
Protection Method ◽  
Linguistic Steganography ◽  
A Priority ◽  
Reverse Development

Показано, что защита программных продуктов от несанкционированного использования является первостепенной задачей для разработчиков. Выделены три основные категории атак на программное обеспечение (ПО): нелегальное использование, обратная разработка, когда из ПО извлекаются наиболее ценные модули или части исходного кода, и модификация исходного кода, приводящая к существенным потерям для разработчиков, вплоть до потери авторских прав. Рассмотрен один из возможных способов защиты метод вложения цифрового водяного знака (ЦВЗ), основанный на использовании лингвистической стеганографии. It is shown that the protection of software products from unauthorized use is a priority for developers. There are three main categories of attacks on modern software: illegal use, reverse development, when the most valuable modules or parts of the source code are extracted from the software, and modification of the source code, which leads to significant loss of developers, up to the loss of copyright. One of the possible methods of protection is the method of embedding a digital watermark, based on the use of linguistic steganography.

scholarly journals MIAQuant, a novel system for automatic segmentation, measurement, and localization comparison of different biomarkers from serialized histological slices

2017 ◽  
Vol 61 (4) ◽  
Author(s):  
Elena Casiraghi ◽  
Mara Cossa ◽  
Veronica Huber ◽  
Licia Rivoltini ◽  
Matteo Tozzi ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Automatic Segmentation ◽  
Source Code ◽  
Automatic Method ◽  
Automatic Image Analysis ◽  
Tissue Slices ◽  
Software Products ◽  
Research Fields ◽  
Black Boxes ◽  
Histological Results

<p>In the clinical practice, automatic image analysis methods quickly quantizing histological results by objective and replicable methods are getting more and more necessary and widespread. Despite several commercial software products are available for this task, they are very little flexible, and provided as black boxes without modifiable source code. To overcome the aforementioned problems, we employed the commonly used MATLAB platform to develop an automatic method, MIAQuant, for the analysis of histochemical and immunohistochemical images, stained with various methods and acquired by different tools. It automatically extracts and quantifies markers characterized by various colors and shapes; furthermore, it aligns contiguous tissue slices stained by different markers and overlaps them with differing colors for visual comparison of their localization. Application of MIAQuant for clinical research fields, such as oncology and cardiovascular disease studies, has proven its efficacy, robustness and flexibility with respect to various problems; we highlight that, the flexibility of MIAQuant makes it an important tool to be exploited for basic researches where needs are constantly changing. MIAQuant software and its user manual are freely available for clinical studies, pathological research, and diagnosis.</p>

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