Favorite publications
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These are my favourite papers of all times:
Data-Driven Extract Method Recommendations: A Study at ING
Proceedings of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '21), 2021
The sound identification of refactoring opportunities is still an open problem in software engineering. Recent studies have shown the effectiveness of machine learning models in recommending methods that should undergo different refactoring operations.
In this work, we experiment with such approaches to identify methods that should undergo an E...
How Developers Engineer Test Cases: An Observational Study
Transactions on Software Engineering (TSE), 2021
One of the main challenges that developers face when testing their systems lies in engineering test cases that are good enough to reveal bugs. And while our body of knowledge on software testing and automated test case generation is already quite significant, in practice, developers are still the ones responsible for engineering test cases manua...
An Exploratory Study of Log Placement Recommendation in an Enterprise System
Mining Software Repositories Conference (MSR), 2021
Logging is a development practice that plays an important role in the operations and monitoring of complex systems.
Developers place log statements in the source code and use log data to understand how the system behaves in production.
Unfortunately, anticipating where to log during development is challenging.
Previous studies show the feasibili...
The Effectiveness of Supervised Machine Learning Algorithms in Predicting Software Refactoring
Transactions on Software Engineering (TSE), 2020
Refactoring is the process of changing the internal structure of software to improve its quality without modifying its external behavior. Before carrying out refactoring activities, developers need to identify refactoring opportunities. Currently, refactoring opportunity identification heavily relies on developers’ expertise and intuition.
In t...
Monitoring-Aware IDEs
27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2019
Engineering modern large-scale software requires software developers to not solely focus on writing code, but also to continuously examine monitoring data to reason about the dynamic behavior of their systems. These additional monitoring responsibilities for developers have only emerged recently, in the light of DevOps culture. Interestingly, so...
When Testing Meets Code Review: Why and How Developers Review Tests
40th International Conference on Software Engineering (ICSE), 2018
Automated testing is considered an essential process for ensuring software quality. However, writing and maintaining high-quality test code is challenging and frequently considered of secondary importance. For production code, many open source and industrial software projects employ code review, a well-established software quality practice, but ...
Search-Based Test Data Generation for SQL Queries
40th International Conference on Software Engineering (ICSE), 2018
Database-centric systems strongly rely on SQL queries to manage and manipulate their data. These SQL commands can range from very simple selections to queries that involve several tables, subqueries, and grouping operations. And, as with any important piece of code, developers should properly test SQL queries. In order to completely test a SQL q...
The Adoption of JavaScript Linters in Practice: A Case Study on ESLint
Transactions on Software Engineering (TSE), 2018
A linter is a static analysis tool that warns software developers about possible code errors or violations to coding standards. By using such a tool, errors can be surfaced early in the development process when they are cheaper to fix. For a linter to be successful, it is important to understand the needs and challenges of developers when using ...
Code smells for Model-View-Controller architectures
Empirical Software Engineering Journal (EMSE), 2017
Previous studies have shown the negative effects that low-quality code can have on maintainability proxies, such as code change- and defect-proneness. One of the symptoms for low-quality code are code smells, defined as sub-optimal implementation choices. While this definition is quite general and seems to suggest a wide spectrum of smells that ...