An Empirical Study on the Impacts of Autonomy of Components on Qualities of Software Systems

2011 ◽  
Author(s):  
Tingxun Shi ◽  
Jianzhu Ma ◽  
Wenpin Jiao ◽  
Fanjing Meng
Keyword(s):  
Empirical Study ◽  
Software Systems

An Empirical Study on the Architecture Instability of Software Projects

2019 ◽  
Vol 29 (04) ◽  
pp. 515-545 ◽  
Author(s):  
Lerina Aversano ◽  
Daniela Guardabascio ◽  
Maria Tortorella
Keyword(s):  
Empirical Study ◽  
Programming Languages ◽  
Quantitative Information ◽  
Software Systems ◽  
Software Project ◽  
Software System ◽  
Software Projects ◽  
System Maturity ◽  
Multiple Releases ◽  
Initial Concept

Software architecture is an artifact that expresses how the initial concept of a software system has actually been implemented. However, changes to the requirement imply continuous modification of the software system and may affect its architecture. It is expected that when a software system reaches the mature state, the requirements for evolution decrease and its architecture becomes more stable. The paper analyzes how the architecture of a software system evolves during its life cycle, with the aim of obtaining quantitative information on its possible instability after it has been declared mature. The goal is to verify if the architectural instability decreases with the increase of the software system maturity and to identify the software components that are more unstable among multiple releases. The paper proposes metrics that measure the instability of the architecture of a software system and its components through different releases. Open source software projects classified as mature and active and related historical data are analyzed. The results of the empirical study point out that the instability of software projects continues to evolve even after they are declared mature. The proposed metrics give a useful support for investigating the instability of a software project, even if further factors can be analyzed. Furthermore, the study can be replicated on other software systems belonging to different domains and developed using different programming languages.

An Empirical Study of Technical Debt in Open-Source Software Systems

2017 ◽  
pp. 113-125 ◽  
Author(s):  
Reem Alfayez ◽  
Celia Chen ◽  
Pooyan Behnamghader ◽  
Kamonphop Srisopha ◽  
Barry Boehm
Keyword(s):  
Empirical Study ◽  
Open Source ◽  
Open Source Software ◽  
Software Systems ◽  
Technical Debt

Use of software systems development methods An empirical study in Brunei Darussalam

1998 ◽  
Vol 39 (14-15) ◽  
pp. 949-963 ◽  
Author(s):  
Md.Mahbubur Rahim ◽  
Afzaal H. Seyal ◽  
Mohd.Noah Abd. Rahman
Keyword(s):  
Empirical Study ◽  
Systems Development ◽  
Software Systems ◽  
Brunei Darussalam ◽  
Development Methods

METRIC SELECTION FOR SOFTWARE DEFECT PREDICTION

2011 ◽  
Vol 21 (02) ◽  
pp. 237-257 ◽  
Author(s):  
HUANJING WANG ◽  
TAGHI M. KHOSHGOFTAAR ◽  
JASON VAN HULSE ◽  
KEHAN GAO
Keyword(s):  
Empirical Study ◽  
Prediction Models ◽  
Characteristic Curve ◽  
Life Cycles ◽  
Defect Prediction ◽  
Software Systems ◽  
Software Projects ◽  
Ensemble Technique ◽  
Defect Prediction Models ◽  
Software Practitioners

Real-world software systems are becoming larger, more complex, and much more unpredictable. Software systems face many risks in their life cycles. Software practitioners strive to improve software quality by constructing defect prediction models using metric (feature) selection techniques. Finding faulty components in a software system can lead to a more reliable final system and reduce development and maintenance costs. This paper presents an empirical study of six commonly used filter-based software metric rankers and our proposed ensemble technique using rank ordering of the features (mean or median), applied to three large software projects using five commonly used learners. The classification accuracy was evaluated in terms of the AUC (Area Under the ROC (Receiver Operating Characteristic) Curve) performance metric. Results demonstrate that the ensemble technique performed better overall than any individual ranker and also possessed better robustness. The empirical study also shows that variations among rankers, learners and software projects significantly impacted the classification outcomes, and that the ensemble method can smooth out performance.

scholarly journals Challenges in migrating legacy software systems to the cloud — an empirical study

2017 ◽  
Vol 67 ◽  
pp. 100-113 ◽  
Author(s):  
Mahdi Fahmideh Gholami ◽  
Farhad Daneshgar ◽  
Ghassan Beydoun ◽  
Fethi Rabhi
Keyword(s):  
Empirical Study ◽  
Software Systems ◽  
Legacy Software
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