Lionel Seinturier

Martin Monperrus, Simon Urli, Thomas Durieux et al.

Repairnator is a bot. It constantly monitors software bugs discovered during continuous integration of open-source software and tries to fix them automatically. If it succeeds in synthesizing a valid patch, Repairnator proposes the patch to the human developers, disguised under a fake human identity. To date, Repairnator has been able to producepatches that were accepted by the human developers and permanently merged into the code base. This is a milestone for human-competitiveness in software engineering research on automatic program repair.

Simon Urli, Zhongxing Yu, Lionel Seinturier et al.

Program repair research has made tremendous progress over the last few years, and software development bots are now being invented to help developers gain productivity. In this paper, we investigate the concept of a " program repair bot " and present Repairnator. The Repairnator bot is an autonomous agent that constantly monitors test failures, reproduces bugs, and runs program repair tools against each reproduced bug. If a patch is found, Repairnator bot reports it to the developers. At the time of writing, Repairnator uses three different program repair systems and has been operating since February 2017. In total, it has studied 11 317 test failures over 1 609 open-source software projects hosted on GitHub, and has generated patches for 17 different bugs. Over months, we hit a number of hard technical challenges and had to make various design and engineering decisions. This gives us a unique experience in this area. In this paper, we reflect upon Repairnator in order to share this knowledge with the automatic program repair community.

Martin Monperrus, Simon Urli, Thomas Durieux et al.

Repairnator is a bot. It constantly monitors software bugs discovered during continuous integration of open-source software and tries to fix them automatically. If it succeeds to synthesize a valid patch, Repairnator proposes the patch to the human developers, disguised under a fake human identity. To date, Repairnator has been able to produce 5 patches that were accepted by the human developers and permanently merged in the code base. This is a milestone for human-competitiveness in software engineering research on automatic program repair.

Zhongxing Yu, Chenggang Bai, Lionel Seinturier et al.

Annotations have been formally introduced into Java since Java 5. Since then, annotations have been widely used by the Java community for different purposes, such as compiler guidance and runtime processing. Despite the ever-growing use, there is still limited empirical knowledge about the actual usage of annotations in practice, the changes made to annotations during software evolution, and the potential impact of annotations on code quality. To fill this gap, we perform the first large-scale empirical study about Java annotations on 1,094 notable open-source projects hosted on GitHub. Our study systematically investigates annotation usage, annotation evolution, and annotation impact, and generates 10 novel and important findings. We also present the implications of our findings, which shed light for developers, researchers, tool builders, and language or library designers in order to improve all facets of Java annotation engineering.

Benoit Cornu, Earl T. Barr, Lionel Seinturier et al.

Fixing a software error requires understanding its root cause. In this paper, we introduce ''causality traces'', crafted execution traces augmented with the information needed to reconstruct the causal chain from the root cause of a bug to an execution error. We propose an approach and a tool, called Casper, for dynamically constructing causality traces for null dereference errors. The core idea of Casper is to inject special values, called ''ghosts'', into the execution stream to construct the causality trace at runtime. We evaluate our contribution by providing and assessing the causality traces of 14 real null dereference bugs collected over six large, popular open-source projects. Over this data set, Casper builds a causality trace in less than 5 seconds.

Sacha Brisset, Romain Rouvoy, Lionel Seinturier et al.

Web applications are constantly evolving to integrate new features and fix reported bugs. Even an imperceptible change can sometimes entail significant modifications of the Document Object Model (DOM), which is the underlying model used by browsers to render all the elements included in a web application. Scripts that interact with web applications (e.g. web test scripts, crawlers, or robotic process automation) rely on this continuously evolving DOM which means they are often particularly fragile. More precisely, the major cause of breakages observed in automation scripts are element locators, which are identifiers used by automation scripts to navigate across the DOM. When the DOM evolves, these identifiers tend to break, thus causing the related scripts to no longer locate the intended target elements. For this reason, several contributions explored the idea of automatically repairing broken locators on a page. These works attempt to repair a given broken locator by scanning all elements in the new DOM to find the most similar one. Unfortunately, this approach fails to scale when the complexity of web pages grows, leading either to long computation times or incorrect element repairs. This article, therefore, adopts a different perspective on this problem by introducing a new locator repair solution that leverages tree matching algorithms to relocate broken locators. This solution, named Erratum, implements a holistic approach to reduce the element search space, which greatly eases the locator repair task and drastically improves repair accuracy. We compare the robustness of Erratum on a large-scale benchmark composed of realistic and synthetic mutations applied to popular web applications currently deployed in production. Our empirical results demonstrate that Erratum outperforms the accuracy of WATER, a state-of-the-art solution, by 67%.

Sacha Brisset, Romain Rouvoy, Renaud Pawlak et al.

Tree matching techniques have been investigated in many fields, including web data mining and extraction, as a key component to analyze the content of web documents, existing tree matching approaches, like Tree-Edit Distance (TED) or Flexible Tree Matching (FTM), fail to scale beyond a few hundreds of nodes, which is far below the average complexity of existing web online documents and applications. In this paper, we therefore propose a novel Similarity-based Flexible Tree Matching algorithm (SFTM), which is the first algorithm to enable tree matching on real-life web documents with practical computation times. In particular, we approach tree matching as an optimisation problem and we leverage node labels and local topology similarity in order to avoid any combinatorial explosion. Our practical evaluation demonstrates that our approach compares to the reference implementation of TED qualitatively, while improving the computation times by two orders of magnitude.

Thomas Durieux, Benoit Cornu, Lionel Seinturier et al.

Null pointer exceptions (NPE) are the number one cause of uncaught crashing exceptions in production. In this paper, we aim at exploring the search space of possible patches for null pointer exceptions with metaprogramming. Our idea is to transform the program under repair with automated code transformation, so as to obtain a metaprogram. This metaprogram contains automatically injected hooks, that can be activated to emulate a null pointer exception patch. This enables us to perform a fine-grain analysis of the runtime context of null pointer exceptions. We set up an experiment with 16 real null pointer exceptions that have happened in the field. We compare the effectiveness of our metaprogramming approach against simple templates for repairing null pointer exceptions.

Benoit Cornu, Thomas Durieux, Lionel Seinturier et al.

Null pointer exceptions, also known as null dereferences are the number one exceptions in the field. In this paper, we propose 9 alternative execution semantics when a null pointer exception is about to happen. We implement those alternative execution strategies using code transformation in a tool called NPEfix. We evaluate our prototype implementation on 11 field null dereference bugs and 519 seeded failures and show that NPEfix is able to repair at runtime 10/11 and 318/519 failures.

Jifeng Xuan, Benoit Cornu, Matias Martinez et al.

Context: Developers design test suites to automatically verify that software meets its expected behaviors. Many dynamic analysis techniques are performed on the exploitation of execution traces from test cases. However, in practice, there is only one trace that results from the execution of one manually-written test case. Objective: In this paper, we propose a new technique of test suite refactoring, called B-Refactoring. The idea behind B-Refactoring is to split a test case into small test fragments, which cover a simpler part of the control flow to provide better support for dynamic analysis. Method: For a given dynamic analysis technique, our test suite refactoring approach monitors the execution of test cases and identifies small test cases without loss of the test ability. We apply B-Refactoring to assist two existing analysis tasks: automatic repair of if-statements bugs and automatic analysis of exception contracts. Results: Experimental results show that test suite refactoring can effectively simplify the execution traces of the test suite. Three real-world bugs that could previously not be fixed with the original test suite are fixed after applying B-Refactoring; meanwhile, exception contracts are better verified via applying B-Refactoring to original test suites. Conclusions: We conclude that applying B-Refactoring can effectively improve the purity of test cases. Existing dynamic analysis tasks can be enhanced by test suite refactoring.

Fawaz Paraiso, Philippe Merle, Lionel Seinturier

Multi-cloud computing is a promising paradigm to support very large scale world wide distributed applications. Multi-cloud computing is the usage of multiple, independent cloud environments, which assumed no priori agreement between cloud providers or third party. However, multi-cloud computing has to face several key challenges such as portability, provisioning, elasticity, and high availability. Developers will not only have to deploy applications to a specific cloud, but will also have to consider application portability from one cloud to another, and to deploy distributed applications spanning multiple clouds. This article presents soCloud a service-oriented component-based Platform as a Service (PaaS) for managing portability, elasticity, provisioning, and high availability across multiple clouds. soCloud is based on the OASIS Service Component Architecture (SCA) standard in order to address portability. soCloud provides services for managing provisioning, elasticity, and high availability across multiple clouds. soCloud has been deployed and evaluated on top of ten existing cloud providers: Windows Azure, DELL KACE, Amazon EC2, CloudBees, OpenShift, dotCloud, Jelastic, Heroku, Appfog, and an Eucalyptus private cloud.

Benoit Cornu, Lionel Seinturier, Martin Monperrus

In software, there are the errors anticipated at specification and design time, those encountered at development and testing time, and those that happen in production mode yet never anticipated. In this paper, we aim at reasoning on the ability of software to correctly handle unanticipated exceptions. We propose an algorithm, called short-circuit testing, which injects exceptions during test suite execution so as to simulate unanticipated errors. This algorithm collects data that is used as input for verifying two formal exception contracts that capture two resilience properties. Our evaluation on 9 test suites, with 78% line coverage in average, analyzes 241 executed catch blocks, shows that 101 of them expose resilience properties and that 84 can be transformed to be more resilient.