ESEIW 2022
Sun 18 - Fri 23 September 2022 Helsinki, Finland
Thu 22 Sep 2022 14:05 - 14:25 at Sonck - Session 2B - Technical Debt & Effort Estimation Chair(s): Carolyn Seaman

Background: Bug-fixing is the crux of software maintenance. It entails tending to heaps of bug reports using limited resources. Using historical data, we can ask questions that contribute to better-informed allocation heuristics. The caveat here is that often there is not enough data to provide a sound response. This issue is especially prominent for young projects. Also, answers may vary from project to project. Consequently, it is impossible to generalize results without assuming a notion of relatedness between projects.

Aims: Evaluate the independent impact of three report features in the bug-fixing time (BFT), generalizing results from many projects: bug priority, code-churn size in bug fixing commits, and existence of links to other reports (e.g., depends on or blocks other bug reports).

Method: We analyze 55 projects from the Apache ecosystem using Bayesian statistics. Similar to standard random effects methodology, we assume each project’s average BFT is a dispersed version of a global average BFT that we want to assess. We split the data based on feature values/range (e.g., with or without links). For each split, we compute a posterior distribution over its respective global BFT. Finally, we compare the posteriors to establish the feature’s effect on the BFT. We run independent analyses for each feature.

Results: Our results show that the existence of links and higher code-churn values lead to BFTs that are at least twice as long. On the other hand, considering three levels of priority (low, medium, and high), we observe no difference in the BFT.

Conclusion: To the best of our knowledge, this is the first study using hierarchical Bayes to extrapolate results from multiple projects and assess the global effect of different attributes on the BFT. We use this methodology to gain insight on how links, priority, and code-churn size impact the BFT. On top of that, our posteriors can be used as a prior to analyze novel projects, potentially young and scarce on data. We also believe our methodology can be reused for other generalization studies in empirical software engineering.


Thu 22 Sep

Displayed time zone: Athens change

13:30 - 15:00
Session 2B - Technical Debt & Effort EstimationESEM Industry Forum / ESEM Emerging Results and Vision Papers / ESEM Technical Papers at Sonck
Chair(s): Carolyn Seaman University of Maryland Baltimore County
13:30
20m
Full-paper
Asking about Technical Debt: Characteristics and Automatic Identification of Technical Debt Questions on Stack Overflow
ESEM Technical Papers
Nicholas Kozanidis Vrije Universiteit Amsterdam, Roberto Verdecchia Vrije Universiteit Amsterdam, Emitzá Guzmán Vrije Universiteit Amsterdam
Pre-print
13:50
15m
Vision and Emerging Results
An Experience Report on Technical Debt in Pull Requests: Challenges and Lessons Learned
ESEM Emerging Results and Vision Papers
Shubhashis Karmakar University of Saskatchewan, Zadia Codabux University of Saskatchewan, Melina Vidoni Australian National University
DOI
14:05
20m
Full-paper
Bayesian Analysis of Bug-Fixing Time using Report Data
ESEM Technical Papers
Renan Vieira Federal University of Ceará, Diego Mesquita Getulio Vargas Foundation, César Lincoln Mattos Federal University of Ceará, Ricardo Britto Ericsson / Blekinge Institute of Technology, Lincoln Souza Rocha Federal University of Ceará, João Gomes Federal University of Ceará
14:25
15m
Talk
Investigating a NASA Cyclomatic Complexity Policy on Maintenance of a Critical System
ESEM Industry Forum
Daniel Port University of Hawai‘i at Mānoa, Bill Taber Jet Propulsion Laboratory
14:40
15m
Vision and Emerging Results
An Empirical Study on the Occurrences of Code Smells in Open Source and Industrial Projects
ESEM Emerging Results and Vision Papers
Md. Masudur Rahman Institute of Information Technology (IIT), University of Dhaka, Abdus Satter University of Dhaka, Mahbubul Alam Joarder Institute of Information Technology (IIT), University of Dhaka, Kazi Sakib Institute of Information Technology, University of Dhaka