Internal and external quality in the evolution of mobile software: An exploratory study in open-source market

Gezici, Bahar; Tarhan, Ayça; Chouseinoglou, Oumout

doi:10.1016/j.infsof.2019.04.002

Cited by 16 publications

(13 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As an example, Corral et al [5] proposed a study to determine whether there is a relationship between product quality and market success and they found that there is a signifcant impact between software quality and success. Another related study with this context belongs to Gezici et al [8], where the market success as a demonstration of external quality in the community-based dimension was evaluated from multiple perspectives. Based on their model that consists of six related metrics, a Success Index (SI) was formulated based on statistical correlations between the metrics.…”

Section: A Oss Quality and Successmentioning

confidence: 99%

“…It is measured by analyzing user reviews and ratings that are allowed in application markets to collect feedback from the users regarding various software releases. This feedback enables to assess and estimate the quality and success of an OSS in time [5,8].…”

Section: Introductionmentioning

confidence: 99%

“…We then apply the model on metric data of three mobile OSS applications from Google Play market, and evaluate its performance with respect to original user ratings of applications. Second, we use Success Index (SI) for the OSS applications in accordance to another study of two authors [8] and compare the correlations of SI with both the original and predicted user ratings in order to observe any variation on the relations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Neural Sentiment Analysis of User Reviews to Predict User Ratings

Gezici

Bölücü

Tarhan

et al. 2019

2019 4th International Conference on Computer Science and Engineering (UBMK)

Self Cite

View full text Add to dashboard Cite

The signifcance of user satisfaction is increasing in the competitive open source software (OSS) market. Application stores let users send their feedbacks for applications, which are in the form of user reviews or ratings. Developers are informed about bugs or any additional requirements with the help of this feedback and use it to increase the quality of the software. Moreover, potential users rely on this information as a success indicator to decide downloading the applications. Since it is usually costly to read all the reviews and evaluate their content, the ratings are taken as the base for the assessment. This makes the consistency of the contents with the ratings of the reviews important for healthy evaluation of the applications. In this study, we use recurrent neural networks to analyze the reviews automatically, and thereby predict the user ratings based on the reviews. We apply transfer learning from a huge volume, gold dataset of Amazon Customer Reviews. We evaluate the performance of our model on three mobile OSS applications in the Google Play Store and compare the predicted ratings and the original ratings of the users. Eventually, the predicted ratings have an accuracy of 87.61% compared to the original ratings of the users, which seems promising to obtain the ratings from the reviews especially if the former is absent or its consistency with the reviews is weak.

show abstract

Section: A Oss Quality and Successmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Neural Sentiment Analysis of User Reviews to Predict User Ratings

Gezici

Bölücü

Tarhan

et al. 2019

2019 4th International Conference on Computer Science and Engineering (UBMK)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The evolution of software, however, has been studied specifically, and there is a well‐established set of empirical observations about how individual software systems evolve 2 . Lehman's laws have been used and verified in multiple studies over different contexts; for instance, in recent years, Gezici et al 3 applied Lehman's framework to explore internal quality, external quality and the relation between these two in the evolution of mobile software. Braga de Vasconcelos et al 4 also adopted Lehman's stance on software evolution, arguing that the adoption of knowledge management practices in software engineering would improve both software construction and more particularly software maintenance.…”

Section: Introductionmentioning

confidence: 99%

Evolution and prospects of the Comprehensive R Archive Network (CRAN) package ecosystem

Mora‐Cantallops

Sicilia

García‐Barriocanal

et al. 2020

J Software Evolu Process

View full text Add to dashboard Cite

Free and open source software package ecosystems have existed for a long time, but such collaborative development practice has surged in recent years. One of the oldest and most popular package ecosystems is Comprehensive R Archive Network (CRAN), the repository of packages of the statistical language R, a popular statistical computing environment. CRAN stores a large number of packages that are updated regularly and depend on many other packages in a complex graph of relations. As the repository grows, its sustainability could be threatened by that complexity or nonuniform evolution of some packages. This paper provides an empirical analysis of the evolution of the CRAN repository in the last 20 years, considering the laws of software evolution and the effect of CRAN's policies on such development. Results show how the progress of CRAN is consistent with the laws of continuous growth and change and how there seems to be a relevant increase in complexity in recent years. Significant challenges are raising related to the scale and scope of software package managers and the services they provide; understanding how they change over time and what might endanger their sustainability are key factors for their future improvement, maintenance, policies, and, eventually, sustainability of the ecosystem.

show abstract

“…Validation Pengujian dilakukan dengan menggunakan pengujian kesuksesan sistem informasi menggunakan model DeLone and McLean [19]. Pengujian ini akan dilakukan kepada admin dan siswa perpustakaan.…”

unclassified

Penerapan Sistem Informasi Administrasi Perpustakaan Menggunakan Model Desain User Experience

Setiawansyah

Adrian

Devija

2021

JAMIKA

View full text Add to dashboard Cite

The library at SMP N 5 Bandarlampung is a junior high school library that has library management staff and the number of book collections according to library standards and has adequate library facilities and infrastructure. Students and students are required to become members of the school library to support the learning process. However, the process of borrowing and returning books currently carried out is still conventional, that is, all library administration data collection in borrowing and returning books is still written in the book, and when looking for the required data, you must open the book page. Application of library administration information systems using this user experience design, users can better understand and easily use applications that are made to maximize the performance of library staff, school principals, and students in managing library administration. The design of the library administration information system using the user experience design at SMP Negeri 5 Bandarlampung using the user centered design method has 5 stages namely, Empethized, Define Problem Statements, Indentation, and Prototype in accordance with the needs of users in the library administration information system based on the user experience design undertaken. The results of testing the criteria for the DeLone and McLean Model criteria for the success of the information system were 84.31% with the criteria being Very Good .

show abstract

Internal and external quality in the evolution of mobile software: An exploratory study in open-source market

Cited by 16 publications

References 39 publications

Neural Sentiment Analysis of User Reviews to Predict User Ratings

Neural Sentiment Analysis of User Reviews to Predict User Ratings

Evolution and prospects of the Comprehensive R Archive Network (CRAN) package ecosystem

Penerapan Sistem Informasi Administrasi Perpustakaan Menggunakan Model Desain User Experience

Contact Info

Product

Resources

About