events

Software development is more and more reliant on external code. This external code is developed, bundled into packages and shared using package repositories like crates.io or npm. Reusing shared code bundles greatly improves development speed but without proper care and knowledge of included external code it can cause issues as well. Over-reliance on simple trivial packages that can be easily implemented locally can cause severe consequences like not being able to build if the package is no longer available.

ABSTRACT: Cloud computing services play an important role in today’s modern society. They enable daily operation and advances in key application domains, from banking to e-commerce, from science to gaming, from governance to education. Combining technology developed since the 1960s (e.g., modes of resource sharing) with new paradigms that could only have emerged in the 2010s (e.g., FaaS), they promise to enable unprecedented efficiency and seamless access to services for many.

TbD

Agile originated as a method to be used by a small number of co-located teams. When the amount of teams and the distance between the teams becomes bigger, issues will start to arise. With the rise of the computer and internet, programming-related work environments have become very large and globally distributed, implying a friction when using agile in these environments. This study aims to explore what challenges occur when using agile in very-large globally distributed environments and explore for practices that can be used to deal with them.

Large scale production distributed systems are difficult to design and test. Correctness must be ensured when processes run asynchronously, at arbitrary rates relative to each other, and in the presence of failures, e.g., process crashes or message losses. These conditions create a huge space of executions that is difficult to explore in a principled way. Current testing techniques focus on systematic or randomized exploration of all executions of an implementation while treating the implemented algorithms as black boxes.

Software maintenance is an important and time consuming task during the software development cycle. Readability of test code is a crucial element for performing programming tasks, such as testing, bug fixing and maintaining code. Hence poorly written tests are difficult to maintain and lose their value to developers. In order to overcome this problem, we need to understand how programmers read test code. Therefore in this paper we conducted an empirical study to analyse the various reading patterns in novices and professionals using a sophisticated eye tracking device.

Dear all, Join us on November the 6th, 13:00 - 14:00 on Zoom for the next SERG Reading Club 📖📚!: “Sampling in Software Engineering Research: A Critical Review and Guidelines” by Sebastian Baltes and Paul Ralph https://empirical-software.engineering/assets/pdf/tosem20-sampling.pdf Wanna join & you are not part of our Mattermost? Send an email to c.e.brandt /at/ tudelft.nl to get the Zoom link 😊

In this presentation, I’ll discuss the three MSc thesis defenses we have had at Adyen: The thesis of Henk Grent, who worked on automatically inferring constraints in large-scale APIs The thesis of Hendrig Sellik, who worked on a deep learning model that identifies off-by-one mistakes The thesis of Casper Schröder, who worked on a search-based algorithm to improve the modularization of Adyen’s large codebase. I’ll also discuss what our next works will be about.

Dear all, For this Friday we want to dive deeper into industry-academia collaborations. What is the state of collaborations? Do the partners benefit from the joint projects? how could we increase the process of collaborations between academia and industry? Join us on October the 30th, 13:00 - 14:00 on Zoom for the next SERG Reading Club 📖📚!: “Characterizing industry-academia collaborations in software engineering: evidence from 101 projects” by Garousi et al.

Abstract: In 2014, a Microsoft study investigated the sort of questions that data science applied to software engineering should answer. This resulted in 145 questions that developers considered relevant for data scientists to answer, thus providing a research agenda to the community. Fast forward to five years, no further studies investigated whether the questions from the software engineers at Microsoft hold for other software companies, including software-intensive companies with different primary focus (to which we refer as software-defined enterprises).