CcNav: Understanding Compiler Optimizations in Binary Code

Program developers spend significant time on optimizing and tuning programs. During this iterative process, they apply optimizations, analyze the resulting code, and modify the compilation until they are satisfied. Understanding what the compiler did with the code is crucial to this process but is very time-consuming and labor-intensive. Users need to navigate through thousands of lines of binary code and correlate it to source code concepts to understand the results of the compilation and to identify optimizations. We present a design study in collaboration with program developers and performance analysts. Our collaborators work with various artifacts related to the program such as binary code, source code, control flow graphs, and call graphs. Through interviews, feedback, and pair-analytics sessions, we analyzed their tasks and workflow. Based on this task analysis and through a human-centric design process, we designed a visual analytics system Compilation Navigator (CcNav) to aid exploration of the effects of compiler optimizations on the program. CcNav provides a streamlined workflow and a unified context that integrates disparate artifacts. CcNav supports consistent interactions across all the artifacts making it easy to correlate binary code with source code concepts. CcNav enables users to navigate and filter large binary code to identify and summarize optimizations such as inlining, vectorization, loop unrolling, and code hoisting. We evaluate CcNav through guided sessions and semi-structured interviews. We reflect on our design process, particularly the immersive elements, and on the transferability of design studies through our experience with a previous design study on program analysis.Comment: IEEE VIS VAST 202

Interactive visualisation tools for supporting taxonomists working practice.

The necessity for scientists and others to use consistent terminology has recently beenregarded as fundamental to advancing scientific research, particularly where data fromdisparate sources must be shared, compared or integrated. One area where there aresignificant difficulties with the quality of collected data is the field of taxonomicdescription. Taxonomic description lies at the heart of the classification of organismsand communication of ideas of biodiversity. As part of their working practice,taxonomists need to gather descriptive data about a number of specimens on aconsistent basis for individual projects. Collecting semantically well-defined structureddata could improve the clarity and comparability of such data. No tools howevercurrently exist to allow taxonomists to do so within their working practice.Ontologies are increasingly used to describe and define complex domain data. As a partof related research an ontology of descriptive terminology for controlling the storageand use of flowering plant description data was developed.This work has applied and extended model-based user interface developmentenvironments to utilise such an ontology for the automatic generation of appropriatedata entry interfaces that support semantically well defined and structured descriptivedata. The approach taken maps the ontology to a system domain model, which ataxonomist can then specialise using their domain expertise, for their data entry needs asrequired for individual projects. Based on this specialised domain knowledge, thesystem automatically generates appropriate data entry interfaces that capture dataconsistent with the original ontology. Compared with traditional model-based userautomatic interface development environments, this approach also has the potential toreduce the labour requirements for the expert developer.The approach has also been successfully tested to generate data entry interfaces basedon an XML schema for the exchange of biodiversity datasets

Interactive visualisation tools for supporting taxonomists working practice.

The necessity for scientists and others to use consistent terminology has recently beenregarded as fundamental to advancing scientific research, particularly where data fromdisparate sources must be shared, compared or integrated. One area where there aresignificant difficulties with the quality of collected data is the field of taxonomicdescription. Taxonomic description lies at the heart of the classification of organismsand communication of ideas of biodiversity. As part of their working practice,taxonomists need to gather descriptive data about a number of specimens on aconsistent basis for individual projects. Collecting semantically well-defined structureddata could improve the clarity and comparability of such data. No tools howevercurrently exist to allow taxonomists to do so within their working practice.Ontologies are increasingly used to describe and define complex domain data. As a partof related research an ontology of descriptive terminology for controlling the storageand use of flowering plant description data was developed.This work has applied and extended model-based user interface developmentenvironments to utilise such an ontology for the automatic generation of appropriatedata entry interfaces that support semantically well defined and structured descriptivedata. The approach taken maps the ontology to a system domain model, which ataxonomist can then specialise using their domain expertise, for their data entry needs asrequired for individual projects. Based on this specialised domain knowledge, thesystem automatically generates appropriate data entry interfaces that capture dataconsistent with the original ontology. Compared with traditional model-based userautomatic interface development environments, this approach also has the potential toreduce the labour requirements for the expert developer.The approach has also been successfully tested to generate data entry interfaces basedon an XML schema for the exchange of biodiversity datasets