Impact of Installation Counts on Perceived Quality: A Case Study on Debian
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Debian has a large ecosystem of 16,000 software packages maintained by thousands of developers. The Debian project tracks installation and usage data, and receives around 500 bug reports per month. The document discusses analyzing popularity, usage patterns, bug reports, and other data for software packages in the Debian ecosystem.
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ECMAScript 2015 (ES6)
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C# Production Debugging Made Easy
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Ropython-windbg-python-extensions
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WinDbg showcase.
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Extended information on PyKd.
Honeynet Project Workshop 2014 - Thug: a low-interaction honeyclient
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PyCon AU 2012 - Debugging Live Python Web Applications
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Learn Electron for Web Developers
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Similar to Impact of Installation Counts on Perceived Quality: A Case Study on Debian (20)
Honeynet Project Workshop 2014 - Thug: a low-interaction honeyclient
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PyCon AU 2012 - Debugging Live Python Web Applications
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In-app advertisements have become a major revenue for app developers in the mobile app economy. Ad libraries play an integral part in this ecosystem as app
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Studying the Dialogue Between Users and Developers of Free Apps in the Google...
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Studying online distribution platforms for games through the mining of data f...
Our studies of Steam platform data provided insights into online game distribution:
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This study analyzed factors that impact the speed of questions receiving accepted answers on four popular Stack Exchange websites: Stack Overflow, Mathematics, Ask Ubuntu, and Super User. The researchers examined question, answerer, asker, and answer factors from over 150,000 questions. They built classification models and found that key factors for fast answers included the past speed of answerers, length of the question, and past speed of answers for the question's tags. The models achieved AUCs of 0.85-0.95. Fast answers relied heavily on answerers, especially frequent answerers. The study suggests improving incentives for non-frequent and more difficult questions to attract diverse answerers.
Investigating the Challenges in Selenium Usage and Improving the Testing Effi...
Selenium is a popular tool for browser-based automation testing. The author analyzes challenges in using Selenium by mining Selenium questions on Stack Overflow. Programming language-related questions, especially for Java and Python, are most common and growing fastest. Less than half of questions receive accepted answers, and questions about browsers and components take longest. In the second part, the author develops an approach to improve efficiency of Selenium-based load testing by sharing browsers among user instances. This increases the number of error-free users by 20-22% while reducing memory usage.
Mining Development Knowledge to Understand and Support Software Logging Pract...
This document summarizes Heng Li's PhD thesis on mining development knowledge to understand and support software logging practices. It discusses how logging code is used to record runtime information but can be difficult for developers to maintain. The thesis aims to understand current logging practices and develop tools by mining change history, source code, issue reports, and other development knowledge. It presents research that analyzes logging-related issues to identify developers' logging concerns, uses code topics and structure to predict where logging statements should be added, leverages code changes to suggest when logging code needs updating, and applies machine learning models to recommend appropriate log levels.
Which Log Level Should Developers Choose For a New Logging Statement?
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Towards Just-in-Time Suggestions for Log Changes
The document presents a study on providing just-in-time suggestions for log changes when developers make code changes. The researchers analyzed over 32,000 log changes from 4 systems. They found 20 reasons for log changes that fall into 4 categories: block changes, log improvements, dependence-driven changes, and logging issues. A random forest classifier using 25 software metrics related to code changes, history, and complexity achieved 0.84-0.91 AUC in predicting whether a log change is needed. Change metrics and product metrics were the most influential factors. The study aims to help developers make better logging decisions for failure diagnosis.
The Impact of Task Granularity on Co-evolution Analyses
The document discusses how task granularity at different levels (e.g. commits, pull requests, work items) can impact analyses of co-evolution in software projects. It finds that analyzing at the commit-level can overlook relationships between tasks that span multiple commits. Work item level analysis is recommended to provide a more complete view of co-evolution, as median of 29% of work items consist of multiple commits, and analyzing at the commit level would miss 24% of co-changed files and inability to group 83% of related commits.
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How are Discussions Associated with Bug Reworking? An Empirical Study on Open...
1) Initial bug fix discussions with more comments and more developers participating are more likely to experience later bug reworking through re-opening or re-patching of the bug.
2) Manual analysis found that defective initial fixes and failure to reach consensus in discussions contributed to later reworking.
3) For re-opened bugs, initial discussions focused on addressing a particular problem through a burst of comments, while re-patched bugs lacked thorough code review and testing during the initial fix period.
A Study of the Relation of Mobile Device Attributes with the User-Perceived Q...
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A Large-Scale Study of the Impact of Feature Selection Techniques on Defect C...
This document presents the results of a large-scale study on the impact of feature selection techniques on defect classification models. The study used expanded scopes including multiple datasets from NASA and PROMISE with different feature types, more classification techniques from different paradigms, and additional feature selection techniques. The results show that correlation-based feature subset selection techniques like FS1 and FS2 consistently appear in the top ranks across most of the datasets, projects within the datasets, and classification techniques. The document concludes that future defect classification studies should consider applying correlation-based feature selection techniques.
Studying the Dialogue Between Users and Developers of Free Apps in the Google...
The study analyzes user-developer interactions through reviews and responses on the Google Play Store. It finds that responding to reviews has a significant positive impact, with 84% of rating increases due to the developer addressing the issue or providing guidance. Three common response patterns were identified: only negative reviews, negative or longer reviews, and reviews shortly after an update. Developers most often thank the user, ask for details, provide guidance, or ask for an endorsement. Guidance responses can address common issues through FAQs. The analysis considered over 2,000 apps, 355,000 review changes, 128,000 responses, and 4 million reviews.
What Do Programmers Know about Software Energy Consumption?
This document summarizes the results of a survey of 122 programmers about their knowledge of software energy consumption. The survey found that programmers have limited awareness of energy consumption and how to reduce it. They were unaware of the main causes of high energy usage. Programmers lacked knowledge about how to properly rank the energy consumption of different hardware components and were unfamiliar with strategies to improve efficiency, such as minimizing I/O and avoiding polling. The study concludes that programmers would benefit from more education on software energy usage and its causes.
Threshold for Size and Complexity Metrics: A Case Study from the Perspective ...
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Revisiting the Experimental Design Choices for Approaches for the Automated R...
Prior research on automated duplicate issue report retrieval focused on improving performance metrics like recall rate. The author revisits experimental design choices from four perspectives: needed effort, data changes, data filtration, and evaluation process.
The thesis contributions are: 1) Showing the importance of considering needed effort in performance measurement. 2) Proposing a "realistic evaluation" approach and analyzing prior findings with it. 3) Developing a genetic algorithm to filter old issue reports and improve performance. 4) Highlighting the impact of "just-in-time" features on evaluation. The findings help better understand benefits and limitations of prior work in this area.
Measuring Program Comprehension: A Large-Scale Field Study with Professionals
The document summarizes a large-scale field study that tracked the program comprehension activities of 78 professional developers over 3,148 hours. The study found that:
1) Program comprehension accounted for approximately 58% of developers' time on average, with navigation and editing making up the remaining portions.
2) Developers frequently used web browsers and document editors to aid comprehension beyond just IDEs.
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- 3. Debian has an eco-system of 16,000 packages Thousands of involved developers ~500 reported bugs per month Installation and usage are tracked
- 4. GCC CVS Mozilla CVS Firefox Browser Thunderbird Email GCC C Compiler GCC CVS
- 5. Popularity: total install counts Recent Use (Recent 30 days) Old Use (Beyond 30 days)
- 6. Source Packages mypkg libmypkg mypkg libmypkg-dev mypkg-common Type (Game, Dev, Editor) Priority (Essential , Optional) Bugs (fixed, reported, forwarded) Reporter (email) Binary Packages
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- 15. “With many eyes, all bugs become shallow” Eric Raymond
- 19. Try this at home http://purl.org/net/who/iht/wcre2011
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- http://mat.caminos.upm.es/~iht/tmp/insts_fixed_logofxy.png http://mat.caminos.upm.es/~iht/tmp/insts_fixed_nodots_logofxy.png http://mat.caminos.upm.es/~iht/tmp/insts_fixed_hexbin.png
- Eric Raymond said,