International audienceWith commits and releases, hundreds of tests are run on varying conditions (e.g., over different hardware and workloads) that can help to understand evolution and ensure non-regression of software performance. We hypothesize that performance is not only sensitive to evolution of software, but also to different variability layers of its execution environment, spanning the hardware, the operating system, the build, or the workload processed by the software. Leveraging the MongoDB dataset, our results show that changes in hardware and workload can drastically impact performance evolution and thus should be taken into account when reasoning about evolution. An open problem resulting from this study is how to manage the var...
The importance of ensemble computing is well established. However, executing ensembles at scale intr...
Empirical performance measurements of computer systems almost always exhibit variability and anomali...
The development cycle of large software is necessarily prone to introducing software errors that are...
International audienceWith commits and releases, hundreds of tests are run on varying conditions (e....
International audienceConfiguring software is a powerful means to reach functional and performance g...
Software performance faults have severe consequences for users, developers, and companies. One way t...
This paper presents a scenario-based approach for the evaluation of the quality attribute of perform...
Highly-configurable software systems often leverage variability modeling to achieve systematical reu...
This is the pre-print for the paper presented at the Data Showcase Track in: The 14th International ...
International audienceUnderstanding the root of a performance drop or improvement requires analyzing...
International audienceGenerative software development has paved the way for the creation of multiple...
Software systems are heavily configurable, in the sense that users can adapt them according to their...
Shrinking of device dimensions has undoubtedly enabled the very large scale integration of transisto...
International audienceBiology, medicine, physics, astrophysics, chemistry: all these scientific doma...
The society expects software to deliver the right functionality, in a short amount of time and with ...
The importance of ensemble computing is well established. However, executing ensembles at scale intr...
Empirical performance measurements of computer systems almost always exhibit variability and anomali...
The development cycle of large software is necessarily prone to introducing software errors that are...
International audienceWith commits and releases, hundreds of tests are run on varying conditions (e....
International audienceConfiguring software is a powerful means to reach functional and performance g...
Software performance faults have severe consequences for users, developers, and companies. One way t...
This paper presents a scenario-based approach for the evaluation of the quality attribute of perform...
Highly-configurable software systems often leverage variability modeling to achieve systematical reu...
This is the pre-print for the paper presented at the Data Showcase Track in: The 14th International ...
International audienceUnderstanding the root of a performance drop or improvement requires analyzing...
International audienceGenerative software development has paved the way for the creation of multiple...
Software systems are heavily configurable, in the sense that users can adapt them according to their...
Shrinking of device dimensions has undoubtedly enabled the very large scale integration of transisto...
International audienceBiology, medicine, physics, astrophysics, chemistry: all these scientific doma...
The society expects software to deliver the right functionality, in a short amount of time and with ...
The importance of ensemble computing is well established. However, executing ensembles at scale intr...
Empirical performance measurements of computer systems almost always exhibit variability and anomali...
The development cycle of large software is necessarily prone to introducing software errors that are...