| 鐘ヶ江 由佳 | M, 2回目発表 | ソフトウェア設計学 | 飯田 元, 松本 健一, 市川 昊平, 高橋 慧智 |
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title: Investigation of the Effects of Changes in OSS Projects by Changing CI Tools
abstract: Continuous integration (CI) is a common practice in software development projects to develop software efficiently by finding defects in the early stage. CI tool provides automatically build such as compilation and testing to each source code change. There are many CI tools with different features. Therefore, in software development projects, they select better CI tools according to the attributes of the project. As the project evolves, the use environment of the CI tool also changes. Therefore, to develop software efficiently, it is sometimes necessary to introduce a new CI tool. However, the developers cannot measure an effect of the new CI tool in advance and it takes time to select and change the CI tool. For this reason, it is difficult to decide which CI tools should be adopted. Thus, the objective of this research is to support the judgment of the CI tool change. To accomplish this objective, we will analyze the benefits by changing CI tools and attributes of OSS projects which CI tools were changed. language of the presentation: Japanese | |||
| 辻 光顕 | M, 2回目発表 | ソフトウェア設計学 | 飯田 元☆, 松本 健一, 高橋 慧智, 片平 真史（客員）, 石濱 直樹（客員） |
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title: Quantative Analysis of Hazards Based on Systems Theory Using Statistical Model Checking
abstract: Safety-critical systems, such as railway systems and space systems, are required to be safe and reliable. It is necessary to identify hazards that could lead to accident in advance by performing safety analysis. To increase safety of the system design efficiently, it is required to decide which hazards should be dealt with most urgently, and then derive safety requirements to prevent hazards. However, the ability of hazard analysis is dependent on human ability. Therefore, the objective of this study is to propose a method to support identifying important hazardous scenarios based on systems theory, which is a new accident causality model, regardless of human ability. In particular, this study aims to determine how to model systematically hazardous scenarios based on systems theory and perform quantative evaluation by using statistical model checking. language of the presentation: Japanese 発表題目: システム理論に基づくハザードの統計的モデル検査法による定量的評価 発表概要: 鉄道システムやロケットなどの宇宙機には高い安全性が要求される。 このようなシステムを設計するためには、事前に安全分析を行うことによってハザードを識別し対策することが重要である。 システムの安全性を効率的に高めるためには、分析されたハザードから重要なものを識別して、ハザードに至るシナリオに対する対策を検討する必要がある。 しかしながら、ハザード分析能力は人によって異なるため、分析を行う人によってはその判断が難しいという課題がある。 そこで、本研究では、システム理論に基づくハザードに対して、人の分析能力によらず重要なハザードシナリオを系統的に識別するための支援を行う手法の提案を目標とする。 特に、従来までの故障によるハザードではなく、機能間における認識の齟齬によるハザードシナリオを系統的にモデル化する手法を提案し、統計的モデル検査法によって定量的評価を行うことを目指す。 | |||
| HOSSAIN SHAIKH FARHAD | D, 中間発表 | 計算システムズ生物学 | 金谷 重彦, 松本 健一, 小野 直亮, MD.ALTAF-UL-AMIN, 黄 銘 |
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title: Inter Disease Relations Based on Human Biomarkers by Network Analysis
abstract: A biomarker (short for biological marker) is a medical sign of a disease or condition which indicates a normal or abnormal state of a body. The biomarker is a key factor in the analysis of diseases and also for analyzing inter disease relations. We designed and developed a human biomarker (metabolites and proteins) database and the database is currently available online. This biomarkers database will provide information on different diseases, protein, biochemical, metabolite that cover 5000 above diseases and biomarkers association. Information is gathered from multiple sources which include NBCI, published patents, Clinical Trials, Data from the scientific conference, PMA database, FDA, EMEA, PMDA approved documents, google scholar, PubMed and regulatory-approved documents. From our developed database, we collected human biomarkers and their respective diseases. Then we determined the similarity among NCBI disease classes based on associated biomarker fingerprints. For this purpose, we collected biomarker PubChem IDs and using them downloaded the SDF files in a batch, then with those molecular description files determined their atom pair fingerprints using ChemmineR package. We constructed a network of biomarkers based on Tanimoto similarity between their fingerprints and applied DPclusO algorithm to find clusters consisting of biomarkers with similar chemical structures. We also conducted hierarchical clustering of the biomarkers. We categorized all the diseases in our data into 18 NCBI disease classes. Combining all information, we finally determined inter disease relations based on structural similarity between biomarkers. language of the presentation: English | |||