An Exploratory Study on the Occurrence of Self-Admitted Technical Debt in Android Apps
Technical debt describes situations where developers write less-than-optimal code to meet project milestones. However, this debt accumulation often results in future developer effort to live with or fix these quality issues. To better manage this debt, developers may document their sub-optimal code as comments in the code (i.e., self-admitted technical debt or SATD). While prior research has investigated the occurrence and characteristics of SATD, this research has primarily focused on non-mobile systems. With millions of mobile applications (apps) in multiple genres available for end-users, there is a lack of research on sub-optimal code developers intentionally implement in mobile apps. In this study, we examine the occurrence and characteristics of SATD in 15,614 open-source Android apps. Our findings show that even though such apps contain occurrences of SATD, the volume per app (a median of 4) is lower than in non-mobile systems, with most debt categorized as Code Debt. Additionally, we identify typical elements in an app that are prone to intentional sub-optimal implementations. We envision our findings supporting researchers and tool vendors with building tools and techniques to support app developers with app maintenance.
Sun 14 MayDisplayed time zone: Hobart change
11:00 - 12:30 | |||
11:00 25mResearch paper | An Exploratory Study on the Occurrence of Self-Admitted Technical Debt in Android Apps Technical Papers Gregory Wilder II University of Hawai‘i at Mānoa, Riley Miyamoto University of Hawai‘i at Mānoa, Samuel Watson University of Hawai‘i at Mānoa, Rick Kazman University of Hawai‘i at Mānoa, Anthony Peruma University of Hawai‘i at Mānoa Pre-print | ||
11:25 25mResearch paper | Automatically Identifying Relations Between Self-Admitted Technical Debt Across Different Sources Technical Papers Yikun Li University of Groningen, Mohamed Soliman University of Groningen, Paris Avgeriou Univ. of Gronningen | ||
11:50 15mShort-paper | Automated Self-Admitted Technical Debt Tracking at Commit-Level: A Language-independent Approach Short Papers Mohammad Sadegh Sheikhaei School of Computing, Queen's University, Yuan Tian Queens University, Kingston, Canada Pre-print | ||
12:05 15mShort-paper | Measuring Improvement of F1-Scores in Detection of Self-Admitted Technical Debt Short Papers William Aiken University of Ottawa, Paul K. Mvula University of Ottawa, Paula Branco University of Ottawa, Guy Jourdan University of Ottawa, Mehrdad Sabetzadeh University of Ottawa, Herna Viktor University of Ottawa Pre-print | ||
12:20 10mLive Q&A | Open Q&A Plenary |