{"title":"Using Lingvodoc platform for researching genetic and areal semantic shifts: the case of Ob-Ugric basic vocabulary","authors":"Julia Normanskaya","doi":"10.1109/ISPRAS57371.2022.10076867","DOIUrl":"https://doi.org/10.1109/ISPRAS57371.2022.10076867","url":null,"abstract":"Article analysis consists the list the significance of the main results that were obtained when analyzing the graph-phonetic features of the first Cyrillic books in the XIX century:1.The first Cyrillic books allow us to see how the classification of dialects changed.2.The first Cyrillic books allow you to date the time of phonetic changes.3.The first Cyrillic books make it possible to verify the accuracy of transcription of extinct dialects completed by different authors.4.The first Cyrillic books made it possible to identify phenomena that persist in modern dialects and existed in the XIX century, but previously did not attract the systematic attention of scientists.5.The first Cyrillic books make it possible to clarify the territory where speakers of some dialects had previously lived.6.The first Cyrillic books confirm the reconstruction of the proto-language.7.First books allow us to clarify the reconstruction of the proto-language.8.The first Cyrillic books allow us to establish who was the true creator of literary languages.","PeriodicalId":103880,"journal":{"name":"2022 Ivannikov Ispras Open Conference (ISPRAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129922941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research on automatic generation of fuzz-target for software library functions","authors":"Chi Thien Tran, D. Ponomarev, Andrey Kuznhesov","doi":"10.1109/ISPRAS57371.2022.10076871","DOIUrl":"https://doi.org/10.1109/ISPRAS57371.2022.10076871","url":null,"abstract":"To avoid re-development, software libraries are widely used. However, the automated testing of software libraries remains challenging. This article focuses on the use of fuzzing technology and automatic code generation for testing software libraries. Since late of 2020, the instrument Futag [1] – Fuzz-targets automatic generator for software libraries – has been developed in Ivannikov Institute for system programming of Russian academy of science. The instrument gathers data on the building process, generates the fuzz-targets for library functions, and performs static analysis to find entity dependencies in library source code. As result, Futag has found bugs in software libraries such as libpng, tinyxml2, libpq-standalone, etc.","PeriodicalId":103880,"journal":{"name":"2022 Ivannikov Ispras Open Conference (ISPRAS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124276996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Finetuning BERT on Partially Annotated NER Corpora","authors":"Viktor Scherbakov, V. Mayorov","doi":"10.1109/ISPRAS57371.2022.10076869","DOIUrl":"https://doi.org/10.1109/ISPRAS57371.2022.10076869","url":null,"abstract":"Most Named Entity Recognition (NER) models operate under the assumption that training datasets are fully labelled. While it is valid for established datasets like CoNLL 2003 and OntoNotes, sometimes it is not feasible to obtain the complete dataset annotation. These situations may occur, for instance, after selective annotation of entities for cost reduction. This work presents an approach to finetuning BERT on such partially labelled datasets using self-supervision and label preprocessing. Our approach outperforms the previous LSTM-based label preprocessing baseline, significantly improving the performance on poorly labelled datasets. We demonstrate that following our approach while finetuning RoBERTa on CoNLL 2003 dataset with only 10% of total entities labelled is enough to reach the performance of the baseline trained on the same dataset with 50% of the entities labelled.","PeriodicalId":103880,"journal":{"name":"2022 Ivannikov Ispras Open Conference (ISPRAS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130350138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Vishnyakov, D. Kuts, V. Logunova, Darya Parygina, Eli Kobrin, Georgy Savidov, A. Fedotov
{"title":"Sydr-Fuzz: Continuous Hybrid Fuzzing and Dynamic Analysis for Security Development Lifecycle","authors":"A. Vishnyakov, D. Kuts, V. Logunova, Darya Parygina, Eli Kobrin, Georgy Savidov, A. Fedotov","doi":"10.1109/ISPRAS57371.2022.10076861","DOIUrl":"https://doi.org/10.1109/ISPRAS57371.2022.10076861","url":null,"abstract":"Nowadays automated dynamic analysis frameworks for continuous testing are in high demand to ensure software safety and satisfy the security development lifecycle (SDL) requirements. The security bug hunting efficiency of cutting-edge hybrid fuzzing techniques outperforms widely utilized coverage-guided fuzzing. We propose an enhanced dynamic analysis pipeline to leverage productivity of automated bug detection based on hybrid fuzzing. We implement the proposed pipeline in the continuous fuzzing toolset Sydr-Fuzz which is powered by hybrid fuzzing orchestrator, integrating our DSE tool Sydr with libFuzzer and AFL++. Sydr-Fuzz also incorporates security predicate checkers, crash triaging tool Casr, and utilities for corpus minimization and coverage gathering. The benchmarking of our hybrid fuzzer against alternative state-of-the-art solutions demonstrates its superiority over coverage-guided fuzzers while remaining on the same level with advanced hybrid fuzzers. Furthermore, we approve the relevance of our approach by discovering 85 new real-world software flaws within the OSS-Sydr-Fuzz project. Finally, we open Casr source code to the community to facilitate examination of the existing crashes.","PeriodicalId":103880,"journal":{"name":"2022 Ivannikov Ispras Open Conference (ISPRAS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114180946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}