Helping Developers Help Themselves: Automatic Decomposition of Code Review Changes

Helping Developers Help Themselves: Automatic Decomposition of Code Review Changes - Barnett et al. 2015 Earlier this week we saw that pull requests with well organised commits are strongly preferred by integrators. Unfortunately, developers often make changes that incorporate multiple bug fixes, feature additions, refactorings, etc.. These result in changes that are both large and … Continue reading Helping Developers Help Themselves: Automatic Decomposition of Code Review Changes

The Art of Testing Less Without Sacrificing Quality

The Art of Testing Less Without Sacrificing Quality - Herzig et al. 2015 Why on earth would anyone want to test less? Maybe if you could guarantee the same eventually quality, and save a couple of million dollars along the way... By nature, system and compliance tests are complex and time-consuming although they rarely find … Continue reading The Art of Testing Less Without Sacrificing Quality

Work Practices and Challenges in Pull-Based Development

Work Practices and Challenges in Pull-based Development - Gousios et al. 2015 In the recent years, we are witnessing that collaborative, lightweight code review is increasingly becoming the default mechanism for integrating changes, in both collocated and distributed development. Effectively, the pull request (in various forms) is becoming the atomic unit of software change. How … Continue reading Work Practices and Challenges in Pull-Based Development

How Much Up-Front? A Grounded Theory of Agile Architecture

How Much Up-Front? A Grounded Theory of Agile Architecture - Waterman et al. 2015 It's time for something a little bit different, so this week I thought I'd bring you a selection of papers from the recently held ICSE'15 conference (International Conference on Software Engineering). To kick things off, today's choice looks at the question … Continue reading How Much Up-Front? A Grounded Theory of Agile Architecture

Discretized Streams: Fault Tolerant Stream Computing at Scale

Discretized Streams: Fault Tolerant Stream Computing at Scale - Zaharia et al. 2013 This is the Spark Streaming paper, and it sets out very clearly the problem that Discretized Streams were designed to solve: dealing effectively with faults and stragglers when processing streams in large clusters. This is hard to do in the traditional continuous … Continue reading Discretized Streams: Fault Tolerant Stream Computing at Scale