Ranking & Metrics
Impact Score is a novel metric devised to rank conferences based on the number of contributing top scientists in addition to the h-index estimated from the scientific papers published by top scientists. See more details on our methodology page.
Research Impact Score:5.12
Contributing Top Scientist:32
Papers published by Top Scientists47
Research Ranking (Computer Science)98
Conference Call for Papers
Authors are invited to submit research papers describing original contributions in testing or analysis of computer software. Papers describing original theoretical or empirical research, new techniques, methods for emerging systems, in-depth case studies, infrastructures of testing and analysis, or tools are welcome.
Authors are invited to submit experience papers describing a significant experience in applying software testing and analysis methods or tools and should carefully identify and discuss important lessons learned so that other researchers and/or practitioners can benefit from the experience. Of special interest are experience papers that report on industrial applications of software testing and analysis methods or tools.
ISSTA would like to encourage researchers to reproduce results from previous papers. A reproducibility study must go beyond simply re-implementing an algorithm and/or re-running the artifacts provided by the original paper. It should at the very least apply the approach to new, significantly broadened inputs. Particularly, reproducibility studies are encouraged to target techniques that previously were evaluated only on proprietary subject programs or inputs. A reproducibility study should clearly report on results that the authors were able to reproduce as well as on aspects of the work that were irreproducible. In the latter case, authors are encouraged to make an effort to communicate or collaborate with the original paper’s authors to determine the cause for any observed discrepancies and, if possible, address them (e.g., through minor implementation changes). We explicitly encourage authors to not focus on a single paper/artifact only, but instead to perform a comparative experiment of multiple related approaches. In particular, reproducibility studies should follow the ACM guidelines on reproducibility (different team, different experimental setup): The measurement can be obtained with stated precision by a different team, a different measuring system, in a different location on multiple trials. For computational experiments, this means that an independent group can obtain the same result using artifacts which they develop completely independently. This means that it is also insufficient to focus on repeatability (i.e., same experiment) alone. Reproducibility Studies will be evaluated according to the following standards:
Depth and breadth of experiments
Clarity of writing
Appropriateness of conclusions
Amount of useful, actionable insights
Availability of artifacts
We expect reproducibility studies to clearly point out the artifacts the study is built on, and to submit those artifacts to artifact evaluation (see below). Artifacts evaluated positively will be eligible to obtain the highly prestigious badges Results Replicated or Results Reproduced.