[{"publication":"IEEE Transactions on Evolutionary Computation","type":"journal_article","status":"public","department":[{"_id":"819"}],"user_id":"15504","_id":"54548","language":[{"iso":"eng"}],"keyword":["Optimization","Evolutionary computation","Benchmark testing","Hyperparameter optimization","Portfolios","Extraterrestrial measurements","Dispersion","Exploratory landscape analysis","mixed-variable problem","mixed search spaces","automated algorithm selection"],"page":"1-1","citation":{"ama":"Prager RP, Trautmann H. Exploratory Landscape Analysis for Mixed-Variable Problems. <i>IEEE Transactions on Evolutionary Computation</i>. Published online 2024:1-1. doi:<a href=\"https://doi.org/10.1109/TEVC.2024.3399560\">10.1109/TEVC.2024.3399560</a>","chicago":"Prager, Raphael Patrick, and Heike Trautmann. “Exploratory Landscape Analysis for Mixed-Variable Problems.” <i>IEEE Transactions on Evolutionary Computation</i>, 2024, 1–1. <a href=\"https://doi.org/10.1109/TEVC.2024.3399560\">https://doi.org/10.1109/TEVC.2024.3399560</a>.","ieee":"R. P. Prager and H. Trautmann, “Exploratory Landscape Analysis for Mixed-Variable Problems,” <i>IEEE Transactions on Evolutionary Computation</i>, pp. 1–1, 2024, doi: <a href=\"https://doi.org/10.1109/TEVC.2024.3399560\">10.1109/TEVC.2024.3399560</a>.","apa":"Prager, R. P., &#38; Trautmann, H. (2024). Exploratory Landscape Analysis for Mixed-Variable Problems. <i>IEEE Transactions on Evolutionary Computation</i>, 1–1. <a href=\"https://doi.org/10.1109/TEVC.2024.3399560\">https://doi.org/10.1109/TEVC.2024.3399560</a>","bibtex":"@article{Prager_Trautmann_2024, title={Exploratory Landscape Analysis for Mixed-Variable Problems}, DOI={<a href=\"https://doi.org/10.1109/TEVC.2024.3399560\">10.1109/TEVC.2024.3399560</a>}, journal={IEEE Transactions on Evolutionary Computation}, author={Prager, Raphael Patrick and Trautmann, Heike}, year={2024}, pages={1–1} }","mla":"Prager, Raphael Patrick, and Heike Trautmann. “Exploratory Landscape Analysis for Mixed-Variable Problems.” <i>IEEE Transactions on Evolutionary Computation</i>, 2024, pp. 1–1, doi:<a href=\"https://doi.org/10.1109/TEVC.2024.3399560\">10.1109/TEVC.2024.3399560</a>.","short":"R.P. Prager, H. Trautmann, IEEE Transactions on Evolutionary Computation (2024) 1–1."},"year":"2024","author":[{"first_name":"Raphael Patrick","last_name":"Prager","full_name":"Prager, Raphael Patrick"},{"first_name":"Heike","full_name":"Trautmann, Heike","id":"100740","last_name":"Trautmann","orcid":"0000-0002-9788-8282"}],"date_created":"2024-06-03T06:16:33Z","date_updated":"2024-06-03T06:17:13Z","doi":"10.1109/TEVC.2024.3399560","title":"Exploratory Landscape Analysis for Mixed-Variable Problems"},{"title":"Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization","doi":"10.1109/TEVC.2024.3458855","date_updated":"2024-09-24T08:01:47Z","date_created":"2024-09-24T08:01:14Z","author":[{"first_name":"Angel E.","full_name":"Rodriguez-Fernandez, Angel E.","last_name":"Rodriguez-Fernandez"},{"full_name":"Schäpermeier, Lennart","last_name":"Schäpermeier","first_name":"Lennart"},{"last_name":"Hernández","full_name":"Hernández, Carlos","first_name":"Carlos"},{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"},{"full_name":"Trautmann, Heike","id":"100740","last_name":"Trautmann","orcid":"0000-0002-9788-8282","first_name":"Heike"},{"last_name":"Schütze","full_name":"Schütze, Oliver","first_name":"Oliver"}],"year":"2024","page":"1-1","citation":{"ama":"Rodriguez-Fernandez AE, Schäpermeier L, Hernández C, Kerschke P, Trautmann H, Schütze O. Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. <i>IEEE Transactions on Evolutionary Computation</i>. Published online 2024:1-1. doi:<a href=\"https://doi.org/10.1109/TEVC.2024.3458855\">10.1109/TEVC.2024.3458855</a>","ieee":"A. E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann, and O. Schütze, “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization,” <i>IEEE Transactions on Evolutionary Computation</i>, pp. 1–1, 2024, doi: <a href=\"https://doi.org/10.1109/TEVC.2024.3458855\">10.1109/TEVC.2024.3458855</a>.","chicago":"Rodriguez-Fernandez, Angel E., Lennart Schäpermeier, Carlos Hernández, Pascal Kerschke, Heike Trautmann, and Oliver Schütze. “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” <i>IEEE Transactions on Evolutionary Computation</i>, 2024, 1–1. <a href=\"https://doi.org/10.1109/TEVC.2024.3458855\">https://doi.org/10.1109/TEVC.2024.3458855</a>.","apa":"Rodriguez-Fernandez, A. E., Schäpermeier, L., Hernández, C., Kerschke, P., Trautmann, H., &#38; Schütze, O. (2024). Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. <i>IEEE Transactions on Evolutionary Computation</i>, 1–1. <a href=\"https://doi.org/10.1109/TEVC.2024.3458855\">https://doi.org/10.1109/TEVC.2024.3458855</a>","bibtex":"@article{Rodriguez-Fernandez_Schäpermeier_Hernández_Kerschke_Trautmann_Schütze_2024, title={Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization}, DOI={<a href=\"https://doi.org/10.1109/TEVC.2024.3458855\">10.1109/TEVC.2024.3458855</a>}, journal={IEEE Transactions on Evolutionary Computation}, author={Rodriguez-Fernandez, Angel E. and Schäpermeier, Lennart and Hernández, Carlos and Kerschke, Pascal and Trautmann, Heike and Schütze, Oliver}, year={2024}, pages={1–1} }","short":"A.E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2024) 1–1.","mla":"Rodriguez-Fernandez, Angel E., et al. “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” <i>IEEE Transactions on Evolutionary Computation</i>, 2024, pp. 1–1, doi:<a href=\"https://doi.org/10.1109/TEVC.2024.3458855\">10.1109/TEVC.2024.3458855</a>."},"keyword":["Optimization","Evolutionary computation","Approximation algorithms","Benchmark testing","Vectors","Surveys","Pareto optimization","multi-objective optimization","evolutionary computation","multimodal optimization","local solutions"],"language":[{"iso":"eng"}],"_id":"56221","user_id":"15504","status":"public","publication":"IEEE Transactions on Evolutionary Computation","type":"journal_article"},{"publication_status":"published","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783031702389","9783031702396"]},"related_material":{"link":[{"url":"https://link.springer.com/chapter/10.1007/978-3-031-70239-6_34","relation":"confirmation"}]},"place":"Cham","year":"2024","citation":{"chicago":"Gusmita, Ria Hari, Muhammad Faruq Amiral Abshar, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains.” In <i>Lecture Notes in Computer Science</i>. Cham: Springer Nature Switzerland, 2024. <a href=\"https://doi.org/10.1007/978-3-031-70239-6_34\">https://doi.org/10.1007/978-3-031-70239-6_34</a>.","ieee":"R. H. Gusmita, M. F. A. Abshar, D. Moussallem, and A.-C. Ngonga Ngomo, “IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains,” in <i>Lecture Notes in Computer Science</i>, Cham: Springer Nature Switzerland, 2024.","ama":"Gusmita RH, Abshar MFA, Moussallem D, Ngonga Ngomo A-C. IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains. In: <i>Lecture Notes in Computer Science</i>. Springer Nature Switzerland; 2024. doi:<a href=\"https://doi.org/10.1007/978-3-031-70239-6_34\">10.1007/978-3-031-70239-6_34</a>","apa":"Gusmita, R. H., Abshar, M. F. A., Moussallem, D., &#38; Ngonga Ngomo, A.-C. (2024). IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains. In <i>Lecture Notes in Computer Science</i>. The 29th Annual International Conference on Natural Language &#38; Information Systems (NLDB 2024), Turin, Italy. Springer Nature Switzerland. <a href=\"https://doi.org/10.1007/978-3-031-70239-6_34\">https://doi.org/10.1007/978-3-031-70239-6_34</a>","short":"R.H. Gusmita, M.F.A. Abshar, D. Moussallem, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2024.","bibtex":"@inbook{Gusmita_Abshar_Moussallem_Ngonga Ngomo_2024, place={Cham}, title={IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-70239-6_34\">10.1007/978-3-031-70239-6_34</a>}, booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland}, author={Gusmita, Ria Hari and Abshar, Muhammad Faruq Amiral and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2024} }","mla":"Gusmita, Ria Hari, et al. “IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains.” <i>Lecture Notes in Computer Science</i>, Springer Nature Switzerland, 2024, doi:<a href=\"https://doi.org/10.1007/978-3-031-70239-6_34\">10.1007/978-3-031-70239-6_34</a>."},"date_updated":"2024-10-14T19:22:16Z","publisher":"Springer Nature Switzerland","author":[{"first_name":"Ria Hari","id":"71039","full_name":"Gusmita, Ria Hari","last_name":"Gusmita"},{"last_name":"Abshar","full_name":"Abshar, Muhammad Faruq Amiral","first_name":"Muhammad Faruq Amiral"},{"first_name":"Diego","last_name":"Moussallem","full_name":"Moussallem, Diego","id":"71635"},{"first_name":"Axel-Cyrille","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo"}],"date_created":"2024-10-10T14:29:08Z","title":"IndEL: Indonesian Entity Linking Benchmark Dataset for General and Specific Domains","doi":"10.1007/978-3-031-70239-6_34","conference":{"location":"Turin, Italy","end_date":"2024-06-27","start_date":"2024-06-25","name":"The 29th Annual International Conference on Natural Language & Information Systems (NLDB 2024)"},"type":"book_chapter","publication":"Lecture Notes in Computer Science","abstract":[{"text":"In recent years, there has been a surge in natural language processing research focused on low-resource languages (LrLs), underscoring the growing recognition that LrLs deserve the same attention as high-resource languages (HrLs). This shift is crucial for ensuring linguistic diversity and inclusivity in the digital age. Despite Indonesian ranking as the 11th most spoken language globally, it remains under-resourced in terms of computational tools and datasets. Within the semantic web domain, Entity Linking (EL) is pivotal, linking textual entity mentions to their corresponding entries in knowledge bases. This process is foundational for advanced information extraction tasks, including relation extraction and event detection. To bolster EL research in Indonesian, we introduce IndEL, the first benchmark dataset tailored for both general and specific domains. IndEL was manually curated using Wikidata, adhering to a rigorous set of annotation guidelines. We used two Named Entity Recognition (NER) benchmark datasets for entity extraction: NER UI for the general domain and IndQNER for the specific domain. IndQNER focused on entities from the Indonesian translation of the Quran. IndEL comprises 4765 entities in the general domain and 2453 in the specific domain. Using the GERBIL framework, we use IndEL to evaluate the performance of various EL systems, such as Babelfy, DBpedia Spotlight, MAG, OpenTapioca, and WAT. Our further investigation reveals that within Wikidata, a significant number of NIL entities remain unlinked due to the limited number of Indonesian labels and the use of acronyms. Especially in the specific domain, transliteration and translation processes performed to create the Indonesian translation of the Quran contribute to the presence of entities in a descriptive form and as synonyms.","lang":"eng"}],"status":"public","_id":"56581","user_id":"71039","keyword":["entity linking benchmark dataset","Indonesian","general and specific domains"],"language":[{"iso":"eng"}]},{"department":[{"_id":"34"},{"_id":"574"}],"user_id":"71039","_id":"46572","status":"public","type":"book_chapter","doi":"10.1007/978-3-031-35320-8_12","conference":{"name":"International Conference on Applications of Natural Language to Information Systems (NLDB) 2023","start_date":"2023-06-21","end_date":"2023-06-23","location":"Derby, UK"},"author":[{"last_name":"Gusmita","id":"71039","full_name":"Gusmita, Ria Hari","first_name":"Ria Hari"},{"last_name":"Firmansyah","id":"76787","full_name":"Firmansyah, Asep Fajar","first_name":"Asep Fajar"},{"first_name":"Diego","last_name":"Moussallem","id":"71635","full_name":"Moussallem, Diego"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"date_updated":"2024-11-19T15:41:34Z","citation":{"apa":"Gusmita, R. H., Firmansyah, A. F., Moussallem, D., &#38; Ngonga Ngomo, A.-C. (2023). IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran. In <i>Natural Language Processing and Information Systems</i>. International Conference on Applications of Natural Language to Information Systems (NLDB) 2023, Derby, UK. Springer Nature Switzerland. <a href=\"https://doi.org/10.1007/978-3-031-35320-8_12\">https://doi.org/10.1007/978-3-031-35320-8_12</a>","short":"R.H. Gusmita, A.F. Firmansyah, D. Moussallem, A.-C. Ngonga Ngomo, in: Natural Language Processing and Information Systems, Springer Nature Switzerland, Cham, 2023.","mla":"Gusmita, Ria Hari, et al. “IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran.” <i>Natural Language Processing and Information Systems</i>, Springer Nature Switzerland, 2023, doi:<a href=\"https://doi.org/10.1007/978-3-031-35320-8_12\">10.1007/978-3-031-35320-8_12</a>.","bibtex":"@inbook{Gusmita_Firmansyah_Moussallem_Ngonga Ngomo_2023, place={Cham}, title={IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-35320-8_12\">10.1007/978-3-031-35320-8_12</a>}, booktitle={Natural Language Processing and Information Systems}, publisher={Springer Nature Switzerland}, author={Gusmita, Ria Hari and Firmansyah, Asep Fajar and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2023} }","ama":"Gusmita RH, Firmansyah AF, Moussallem D, Ngonga Ngomo A-C. IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran. In: <i>Natural Language Processing and Information Systems</i>. Springer Nature Switzerland; 2023. doi:<a href=\"https://doi.org/10.1007/978-3-031-35320-8_12\">10.1007/978-3-031-35320-8_12</a>","ieee":"R. H. Gusmita, A. F. Firmansyah, D. Moussallem, and A.-C. Ngonga Ngomo, “IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran,” in <i>Natural Language Processing and Information Systems</i>, Cham: Springer Nature Switzerland, 2023.","chicago":"Gusmita, Ria Hari, Asep Fajar Firmansyah, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran.” In <i>Natural Language Processing and Information Systems</i>. Cham: Springer Nature Switzerland, 2023. <a href=\"https://doi.org/10.1007/978-3-031-35320-8_12\">https://doi.org/10.1007/978-3-031-35320-8_12</a>."},"place":"Cham","related_material":{"link":[{"url":"https://link.springer.com/chapter/10.1007/978-3-031-35320-8_12","relation":"confirmation"}]},"publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783031353192","9783031353208"]},"publication_status":"published","language":[{"iso":"eng"}],"keyword":["NER benchmark dataset","Indonesian","specific domain"],"abstract":[{"text":"Indonesian is classified as underrepresented in the Natural Language Processing (NLP) field, despite being the tenth most spoken language in the world with 198 million speakers. The paucity of datasets is recognized as the main reason for the slow advancements in NLP research for underrepresented languages. Significant attempts were made in 2020 to address this drawback for Indonesian. The Indonesian Natural Language Understanding (IndoNLU) benchmark was introduced alongside IndoBERT pre-trained language model. The second benchmark, Indonesian Language Evaluation Montage (IndoLEM), was presented in the same year. These benchmarks support several tasks, including Named Entity Recognition (NER). However, all NER datasets are in the public domain and do not contain domain-specific datasets. To alleviate this drawback, we introduce IndQNER, a manually annotated NER benchmark dataset in the religious domain that adheres to a meticulously designed annotation guideline. Since Indonesia has the world’s largest Muslim population, we build the dataset from the Indonesian translation of the Quran. The dataset includes 2475 named entities representing 18 different classes. To assess the annotation quality of IndQNER, we perform experiments with BiLSTM and CRF-based NER, as well as IndoBERT fine-tuning. The results reveal that the first model outperforms the second model achieving 0.98 F1 points. This outcome indicates that IndQNER may be an acceptable evaluation metric for Indonesian NER tasks in the aforementioned domain, widening the research’s domain range.","lang":"eng"}],"publication":"Natural Language Processing and Information Systems","title":"IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran","date_created":"2023-08-17T12:41:45Z","publisher":"Springer Nature Switzerland","year":"2023"},{"abstract":[{"text":"Context: Cryptographic APIs are often misused in real-world applications. Therefore, many cryptographic API misuse detection tools have been introduced. However, there exists no established reference benchmark for a fair and comprehensive comparison and evaluation of these tools. While there are benchmarks, they often only address a subset of the domain or were only used to evaluate a subset of existing misuse detection tools. Objective: To fairly compare cryptographic API misuse detection tools and to drive future development in this domain, we will devise such a benchmark. Openness and transparency in the generation process are key factors to fairly generate and establish the needed benchmark. Method: We propose an approach where we derive the benchmark generation methodology from the literature which consists of general best practices in benchmarking and domain-specific benchmark generation. A part of this methodology is transparency and openness of the generation process, which is achieved by pre-registering this work. Based on our methodology we design CamBench, a fair \"Cryptographic API Misuse Detection Tool Benchmark Suite\". We will implement the first version of CamBench limiting the domain to Java, the JCA, and static analyses. Finally, we will use CamBench to compare current misuse detection tools and compare CamBench to related benchmarks of its domain.","lang":"eng"}],"status":"public","type":"misc","keyword":["cryptography","benchmark","API misuse","static analysis"],"language":[{"iso":"eng"}],"_id":"32409","department":[{"_id":"76"}],"user_id":"32312","year":"2022","citation":{"apa":"Schlichtig, M., Wickert, A.-K., Krüger, S., Bodden, E., &#38; Mezini, M. (2022). <i>CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite</i>. <a href=\"https://doi.org/10.48550/ARXIV.2204.06447\">https://doi.org/10.48550/ARXIV.2204.06447</a>","mla":"Schlichtig, Michael, et al. <i>CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite</i>. 2022, doi:<a href=\"https://doi.org/10.48550/ARXIV.2204.06447\">10.48550/ARXIV.2204.06447</a>.","bibtex":"@book{Schlichtig_Wickert_Krüger_Bodden_Mezini_2022, title={CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite}, DOI={<a href=\"https://doi.org/10.48550/ARXIV.2204.06447\">10.48550/ARXIV.2204.06447</a>}, author={Schlichtig, Michael and Wickert, Anna-Katharina and Krüger, Stefan and Bodden, Eric and Mezini, Mira}, year={2022} }","short":"M. Schlichtig, A.-K. Wickert, S. Krüger, E. Bodden, M. Mezini, CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite, 2022.","ama":"Schlichtig M, Wickert A-K, Krüger S, Bodden E, Mezini M. <i>CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite</i>.; 2022. doi:<a href=\"https://doi.org/10.48550/ARXIV.2204.06447\">10.48550/ARXIV.2204.06447</a>","chicago":"Schlichtig, Michael, Anna-Katharina Wickert, Stefan Krüger, Eric Bodden, and Mira Mezini. <i>CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite</i>, 2022. <a href=\"https://doi.org/10.48550/ARXIV.2204.06447\">https://doi.org/10.48550/ARXIV.2204.06447</a>.","ieee":"M. Schlichtig, A.-K. Wickert, S. Krüger, E. Bodden, and M. Mezini, <i>CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite</i>. 2022."},"related_material":{"link":[{"relation":"confirmation","url":"https://arxiv.org/abs/2204.06447"}]},"title":"CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite","doi":"10.48550/ARXIV.2204.06447","date_updated":"2022-07-25T10:23:44Z","date_created":"2022-07-25T07:56:59Z","author":[{"first_name":"Michael","id":"32312","full_name":"Schlichtig, Michael","orcid":"0000-0001-6600-6171","last_name":"Schlichtig"},{"last_name":"Wickert","full_name":"Wickert, Anna-Katharina","first_name":"Anna-Katharina"},{"first_name":"Stefan","full_name":"Krüger, Stefan","last_name":"Krüger"},{"first_name":"Eric","id":"59256","full_name":"Bodden, Eric","orcid":"0000-0003-3470-3647","last_name":"Bodden"},{"first_name":"Mira","full_name":"Mezini, Mira","last_name":"Mezini"}]},{"doi":"10.1109/asew.2019.00019","date_updated":"2022-01-06T06:52:38Z","author":[{"last_name":"Pauck","id":"22398","full_name":"Pauck, Felix","first_name":"Felix"},{"first_name":"Shikun","last_name":"Zhang","full_name":"Zhang, Shikun"}],"citation":{"ama":"Pauck F, Zhang S. Android App Merging for Benchmark Speed-Up and Analysis Lift-Up. In: <i>2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)</i>. ; 2019. doi:<a href=\"https://doi.org/10.1109/asew.2019.00019\">10.1109/asew.2019.00019</a>","chicago":"Pauck, Felix, and Shikun Zhang. “Android App Merging for Benchmark Speed-Up and Analysis Lift-Up.” In <i>2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)</i>, 2019. <a href=\"https://doi.org/10.1109/asew.2019.00019\">https://doi.org/10.1109/asew.2019.00019</a>.","ieee":"F. Pauck and S. Zhang, “Android App Merging for Benchmark Speed-Up and Analysis Lift-Up,” in <i>2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)</i>, 2019.","short":"F. Pauck, S. Zhang, in: 2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW), 2019.","bibtex":"@inproceedings{Pauck_Zhang_2019, title={Android App Merging for Benchmark Speed-Up and Analysis Lift-Up}, DOI={<a href=\"https://doi.org/10.1109/asew.2019.00019\">10.1109/asew.2019.00019</a>}, booktitle={2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)}, author={Pauck, Felix and Zhang, Shikun}, year={2019} }","mla":"Pauck, Felix, and Shikun Zhang. “Android App Merging for Benchmark Speed-Up and Analysis Lift-Up.” <i>2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)</i>, 2019, doi:<a href=\"https://doi.org/10.1109/asew.2019.00019\">10.1109/asew.2019.00019</a>.","apa":"Pauck, F., &#38; Zhang, S. (2019). Android App Merging for Benchmark Speed-Up and Analysis Lift-Up. In <i>2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)</i>. <a href=\"https://doi.org/10.1109/asew.2019.00019\">https://doi.org/10.1109/asew.2019.00019</a>"},"publication_status":"published","has_accepted_license":"1","publication_identifier":{"isbn":["9781728141367"]},"file_date_updated":"2020-02-06T17:09:45Z","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - Subproject B4","_id":"12"}],"_id":"15838","user_id":"477","department":[{"_id":"77"}],"status":"public","type":"conference","title":"Android App Merging for Benchmark Speed-Up and Analysis Lift-Up","date_created":"2020-02-06T17:06:51Z","year":"2019","ddc":["004"],"keyword":["Program Analysis","Android App Analysis","Taint Analysis","App Merging","Benchmark"],"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"In the field of software analysis a trade-off between scalability and accuracy always exists. In this respect, Android app analysis is no exception, in particular, analyzing large or many apps can be challenging. Dealing with many small apps is a typical challenge when facing micro-benchmarks such as DROIDBENCH or ICC-BENCH. These particular benchmarks are not only used for the evaluation of novel tools but also in continuous integration pipelines of existing mature tools to maintain and guarantee a certain quality-level. Considering this latter usage it becomes very important to be able to achieve benchmark results as fast as possible. Hence, benchmarks have to be optimized for this purpose. One approach to do so is app merging. We implemented the Android Merge Tool (AMT) following this approach and show that its novel aspects can be used to produce scaled up and accurate benchmarks. For such benchmarks Android app analysis tools do not suffer from the scalability-accuracy trade-off anymore. We show this throughout detailed experiments on DROIDBENCH employing three different analysis tools (AMANDROID, ICCTA, FLOWDROID). Benchmark execution times are largely reduced without losing benchmark accuracy. Moreover, we argue why AMT is an advantageous successor of the state-of-the-art app merging tool (APKCOMBINER) in analysis lift-up scenarios."}],"file":[{"relation":"main_file","content_type":"application/pdf","access_level":"closed","file_id":"15839","file_name":"AMT_final.pdf","file_size":644517,"date_created":"2020-02-06T17:09:45Z","creator":"fpauck","date_updated":"2020-02-06T17:09:45Z"}],"publication":"2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)"},{"language":[{"iso":"eng"}],"ddc":["004"],"keyword":["Benchmark","Question answering","Knowledge base"],"file":[{"date_created":"2024-11-19T15:28:45Z","creator":"gusmita","date_updated":"2024-11-19T15:28:45Z","file_name":"Gusmita_et_al-2019-Semantic_Systems._The_Power_of_AI_and_Knowledge_Graphs,_15th_International....pdf","access_level":"closed","file_id":"57244","file_size":1179910,"content_type":"application/pdf","relation":"main_file","success":1}],"abstract":[{"text":"Question answering engines have become one of the most popular type of applications driven by Semantic Web technologies. Consequently, the provision of means to quantify the performance of current question answering approaches on current datasets has become ever more important. However, a large percentage of the queries found in popular question answering benchmarks cannot be executed on current versions of their reference dataset. There is a consequently a clear need to curate question answering benchmarks periodically. However, the manual alteration of question answering benchmarks is often error-prone. We alleviate this problem by presenting QUANT, a novel framework for the creation and curation of question answering benchmarks. QUANT sup-ports the curation of benchmarks by generating smart edit suggestions for question-query pair and for the corresponding metadata. In addition, our framework supports the creation of new benchmark entries by pro-viding predefined quality checks for queries. We evaluate QUANT on 653questions obtained from QALD-1 to QALD-8 with 10 users. Our results show that our framework generates reliable suggestions and can reduce the curation effort for QA benchmarks by up to 91%.","lang":"eng"}],"publication":"Semantic Systems. The Power of AI and Knowledge Graphs","title":"QUANT - Question Answering Benchmark Curator","date_created":"2024-10-10T14:25:00Z","publisher":"Springer International Publishing","year":"2019","file_date_updated":"2024-11-19T15:28:45Z","user_id":"71039","_id":"56579","status":"public","editor":[{"first_name":"Maribel","full_name":"Acosta, Maribel","last_name":"Acosta"},{"first_name":"Philippe","full_name":"Cudr{\\'e}-Mauroux, Philippe","last_name":"Cudr{\\'e}-Mauroux"},{"first_name":"Maria","last_name":"Maleshkova","full_name":"Maleshkova, Maria"},{"last_name":"Pellegrini","full_name":"Pellegrini, Tassilo","first_name":"Tassilo"},{"first_name":"Harald","last_name":"Sack","full_name":"Sack, Harald"},{"last_name":"Sure-Vetter","full_name":"Sure-Vetter, York","first_name":"York"}],"type":"book_chapter","main_file_link":[{"url":"https://rdcu.be/d0KJc","open_access":"1"}],"conference":{"name":"SEMANTiCS 2019","start_date":"2019-09-09","end_date":"2019-09-12","location":"Karlsruhe, Germany"},"doi":"10.1007/978-3-030-33220-4_25","author":[{"last_name":"Gusmita","full_name":"Gusmita, Ria Hari","id":"71039","first_name":"Ria Hari"},{"full_name":"Jalota, Rricha","last_name":"Jalota","first_name":"Rricha"},{"first_name":"Daniel","full_name":"Vollmers, Daniel","last_name":"Vollmers"},{"full_name":"Reineke, Jan","last_name":"Reineke","first_name":"Jan"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"},{"first_name":"Ricardo","last_name":"Usbeck","full_name":"Usbeck, Ricardo"}],"oa":"1","date_updated":"2024-11-19T15:34:24Z","citation":{"bibtex":"@inbook{Gusmita_Jalota_Vollmers_Reineke_Ngonga Ngomo_Usbeck_2019, place={Cham}, title={QUANT - Question Answering Benchmark Curator}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-33220-4_25\">10.1007/978-3-030-33220-4_25</a>}, booktitle={Semantic Systems. The Power of AI and Knowledge Graphs}, publisher={Springer International Publishing}, author={Gusmita, Ria Hari and Jalota, Rricha and Vollmers, Daniel and Reineke, Jan and Ngonga Ngomo, Axel-Cyrille and Usbeck, Ricardo}, editor={Acosta, Maribel and Cudr{\\’e}-Mauroux, Philippe and Maleshkova, Maria and Pellegrini, Tassilo and Sack, Harald and Sure-Vetter, York}, year={2019}, pages={343--358} }","short":"R.H. Gusmita, R. Jalota, D. Vollmers, J. Reineke, A.-C. Ngonga Ngomo, R. Usbeck, in: M. Acosta, P. Cudr{\\’e}-Mauroux, M. Maleshkova, T. Pellegrini, H. Sack, Y. Sure-Vetter (Eds.), Semantic Systems. The Power of AI and Knowledge Graphs, Springer International Publishing, Cham, 2019, pp. 343--358.","mla":"Gusmita, Ria Hari, et al. “QUANT - Question Answering Benchmark Curator.” <i>Semantic Systems. The Power of AI and Knowledge Graphs</i>, edited by Maribel Acosta et al., Springer International Publishing, 2019, pp. 343--358, doi:<a href=\"https://doi.org/10.1007/978-3-030-33220-4_25\">10.1007/978-3-030-33220-4_25</a>.","apa":"Gusmita, R. H., Jalota, R., Vollmers, D., Reineke, J., Ngonga Ngomo, A.-C., &#38; Usbeck, R. (2019). QUANT - Question Answering Benchmark Curator. In M. Acosta, P. Cudr{\\’e}-Mauroux, M. Maleshkova, T. Pellegrini, H. Sack, &#38; Y. Sure-Vetter (Eds.), <i>Semantic Systems. The Power of AI and Knowledge Graphs</i> (pp. 343--358). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-030-33220-4_25\">https://doi.org/10.1007/978-3-030-33220-4_25</a>","ieee":"R. H. Gusmita, R. Jalota, D. Vollmers, J. Reineke, A.-C. Ngonga Ngomo, and R. Usbeck, “QUANT - Question Answering Benchmark Curator,” in <i>Semantic Systems. The Power of AI and Knowledge Graphs</i>, M. Acosta, P. Cudr{\\’e}-Mauroux, M. Maleshkova, T. Pellegrini, H. Sack, and Y. Sure-Vetter, Eds. Cham: Springer International Publishing, 2019, pp. 343--358.","chicago":"Gusmita, Ria Hari, Rricha Jalota, Daniel Vollmers, Jan Reineke, Axel-Cyrille Ngonga Ngomo, and Ricardo Usbeck. “QUANT - Question Answering Benchmark Curator.” In <i>Semantic Systems. The Power of AI and Knowledge Graphs</i>, edited by Maribel Acosta, Philippe Cudr{\\’e}-Mauroux, Maria Maleshkova, Tassilo Pellegrini, Harald Sack, and York Sure-Vetter, 343--358. Cham: Springer International Publishing, 2019. <a href=\"https://doi.org/10.1007/978-3-030-33220-4_25\">https://doi.org/10.1007/978-3-030-33220-4_25</a>.","ama":"Gusmita RH, Jalota R, Vollmers D, Reineke J, Ngonga Ngomo A-C, Usbeck R. QUANT - Question Answering Benchmark Curator. In: Acosta M, Cudr{\\’e}-Mauroux P, Maleshkova M, Pellegrini T, Sack H, Sure-Vetter Y, eds. <i>Semantic Systems. The Power of AI and Knowledge Graphs</i>. Springer International Publishing; 2019:343--358. doi:<a href=\"https://doi.org/10.1007/978-3-030-33220-4_25\">10.1007/978-3-030-33220-4_25</a>"},"page":"343--358","place":"Cham","publication_status":"published","publication_identifier":{"eisbn":["978-3-030-33220-4"],"isbn":["978-3-030-33219-8"],"issn":["0302-9743","1611-3349"]},"has_accepted_license":"1"},{"title":"Reconfigurable Processors for Handhelds and Wearables: Application Analysis","doi":"10.1117/12.434376","date_updated":"2022-01-06T06:56:17Z","volume":4525,"date_created":"2018-04-17T15:51:39Z","author":[{"first_name":"Rolf","full_name":"Enzler, Rolf","last_name":"Enzler"},{"first_name":"Marco","last_name":"Platzner","id":"398","full_name":"Platzner, Marco"},{"orcid":"0000-0001-5728-9982","last_name":"Plessl","full_name":"Plessl, Christian","id":"16153","first_name":"Christian"},{"first_name":"Lothar","last_name":"Thiele","full_name":"Thiele, Lothar"},{"full_name":"Tröster, Gerhard","last_name":"Tröster","first_name":"Gerhard"}],"year":"2001","page":"135-146","intvolume":"      4525","citation":{"ama":"Enzler R, Platzner M, Plessl C, Thiele L, Tröster G. Reconfigurable Processors for Handhelds and Wearables: Application Analysis. In: <i>Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III</i>. Vol 4525. Proc. SPIE. ; 2001:135-146. doi:<a href=\"https://doi.org/10.1117/12.434376\">10.1117/12.434376</a>","chicago":"Enzler, Rolf, Marco Platzner, Christian Plessl, Lothar Thiele, and Gerhard Tröster. “Reconfigurable Processors for Handhelds and Wearables: Application Analysis.” In <i>Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III</i>, 4525:135–46. Proc. SPIE, 2001. <a href=\"https://doi.org/10.1117/12.434376\">https://doi.org/10.1117/12.434376</a>.","ieee":"R. Enzler, M. Platzner, C. Plessl, L. Thiele, and G. Tröster, “Reconfigurable Processors for Handhelds and Wearables: Application Analysis,” in <i>Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III</i>, 2001, vol. 4525, pp. 135–146.","apa":"Enzler, R., Platzner, M., Plessl, C., Thiele, L., &#38; Tröster, G. (2001). Reconfigurable Processors for Handhelds and Wearables: Application Analysis. In <i>Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III</i> (Vol. 4525, pp. 135–146). <a href=\"https://doi.org/10.1117/12.434376\">https://doi.org/10.1117/12.434376</a>","bibtex":"@inproceedings{Enzler_Platzner_Plessl_Thiele_Tröster_2001, series={Proc. SPIE}, title={Reconfigurable Processors for Handhelds and Wearables: Application Analysis}, volume={4525}, DOI={<a href=\"https://doi.org/10.1117/12.434376\">10.1117/12.434376</a>}, booktitle={Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III}, author={Enzler, Rolf and Platzner, Marco and Plessl, Christian and Thiele, Lothar and Tröster, Gerhard}, year={2001}, pages={135–146}, collection={Proc. SPIE} }","mla":"Enzler, Rolf, et al. “Reconfigurable Processors for Handhelds and Wearables: Application Analysis.” <i>Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III</i>, vol. 4525, 2001, pp. 135–46, doi:<a href=\"https://doi.org/10.1117/12.434376\">10.1117/12.434376</a>.","short":"R. Enzler, M. Platzner, C. Plessl, L. Thiele, G. Tröster, in: Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III, 2001, pp. 135–146."},"keyword":["benchmark"],"_id":"2432","department":[{"_id":"518"},{"_id":"78"}],"user_id":"24135","series_title":"Proc. SPIE","abstract":[{"text":"In this paper, we present the analysis of applications from the domain of handheld and wearable computing. This analysis is the first step to derive and evaluate design parameters for dynamically reconfigurable processors. We discuss the selection of representative benchmarks for handhelds and wearables and group the applications into multimedia, communications, and cryptography programs. We simulate the applications on a cycle-accurate processor simulator and gather statistical data such as instruction mix, cache hit rates and memory requirements for an embedded processor model. A breakdown of the executed cycles into different functions identifies the most compute-intensive code sections - the kernels. Then, we analyze the applications and discuss parameters that strongly influence the design of dynamically reconfigurable processors. Finally, we outline the construction of a parameterizable simulation model for a reconfigurable unit that is attached to a processor core.","lang":"eng"}],"status":"public","publication":"Reconfigurable Technology: FPGAs and Reconfigurable Processors for Computing and Communications III","type":"conference"}]