Release Planning of Mobile Apps Based on User Reviews

被引：191

作者：

Villarroel, Lorenzo ^{[1
]}

Bavota, Gabriele ^{[1
]}

Russo, Barbara ^{[1
]}

Oliveto, Rocco ^{[2
]}

Di Penta, Massimiliano ^{[3
]}

机构：

[1] Free Univ Bozen Bolzano, Bolzano, Italy

[2] Univ Molise, Pesche, IS, Italy

[3] Univ Sannio, Benevento, Italy

来源：

2016 IEEE/ACM 38TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE) | 2016年

关键词：

Release Planning; Mobile Apps; Mining Software Repositories;

D O I：

10.1145/2884781.2884818

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Developers have to to constantly improve their apps by fixing critical bugs and implementing the most desired features in order to gain shares in the continuously increasing and competitive market of mobile apps. A precious source of information to plan such activities is represented by reviews left by users on the app store. However, in order to exploit such information developers need to manually analyze such reviews. This is something not doable if, as frequently happens, the app receives hundreds of reviews per day. In this paper we introduce CLAP (Crowd Listener for releAse Planning), a thorough solution to (i) categorize user reviews based on the information they carry out (e.g., bug reporting), (ii) cluster together related reviews (e.g., all reviews reporting the same bug), and (iii) automatically prioritize the clusters of reviews to be implemented when planning the subsequent app release. We evaluated all the steps behind CLAP, showing its high accuracy in categorizing and clustering reviews and the meaningfulness of the recommended prioritizations. Also, given the availability of CLAP as a working tool, we assessed its practical applicability in industrial environments.

引用

页码：14 / 24

页数：11

共 21 条

[1]

[Anonymous], 2013, ACL 2013

[2]

Baeza-Yates R, 1999, MODERN INFORM RETRIE, V463

[3] The Impact of API Change- and Fault-Proneness on the User Ratings of Android Apps [J].

Bavota, Gabriele ;

Linares-Vasquez, Mario ;

Bernal-Cardenas, Carlos Eduardo ;

Di Penta, Massimiliano ;

Oliveto, Rocco ;

Poshyvanyk, Denys .

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2015, 41 (04) :384-407

[4]

Breiman L., 2001, Machine Learning, V45, P5

[5]

Carreño LVG, 2013, PROCEEDINGS OF THE 35TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2013), P582, DOI 10.1109/ICSE.2013.6606604

[6] AR-Miner: Mining Informative Reviews for Developers from Mobile App Marketplace [J].

Chen, Ning ;

Lin, Jialiu ;

Hoi, Steven C. H. ;

Xiao, Xiaokui ;

Zhang, Boshen .

36TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2014), 2014, :767-778

[7] SimApp: A Framework for Detecting Similar Mobile Applications by Online Kernel Learning [J].

Chen, Ning ;

Hoi, Steven C. H. ;

Li, Shaohua ;

Xiao, Xiaokui .

WSDM'15: PROCEEDINGS OF THE EIGHTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING, 2015, :305-314

[8]

Dumitru H, 2011, 2011 33RD INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE), P181, DOI 10.1145/1985793.1985819

[9]

Ester M., 1996, KDD-96 Proceedings. Second International Conference on Knowledge Discovery and Data Mining, P226

[10]

Fu B, 2013, 19TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (KDD'13), P1276

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