Marc-André Laverdière, Bernhard J. Berger, E. Merlo
{"title":"Taint analysis of manual service compositions using Cross-Application Call Graphs","authors":"Marc-André Laverdière, Bernhard J. Berger, E. Merlo","doi":"10.1109/SANER.2015.7081882","DOIUrl":null,"url":null,"abstract":"We propose an extension over the traditional call graph to incorporate edges representing control flow between web services, named the Cross-Application Call Graph (CACG). We introduce a construction algorithm for applications built on the Jax-WS standard and validate its effectiveness on sample applications from Apache CXF and JBossWS. Then, we demonstrate its applicability for taint analysis over a sample application of our making. Our CACG construction algorithm accurately identifies service call targets 81.07% of the time on average. Our taint analysis obtains a F-Measure of 95.60% over a benchmark. The use of a CACG, compared to a naive approach, improves the F-Measure of a taint analysis from 66.67% to 100.00% for our sample application.","PeriodicalId":355949,"journal":{"name":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SANER.2015.7081882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We propose an extension over the traditional call graph to incorporate edges representing control flow between web services, named the Cross-Application Call Graph (CACG). We introduce a construction algorithm for applications built on the Jax-WS standard and validate its effectiveness on sample applications from Apache CXF and JBossWS. Then, we demonstrate its applicability for taint analysis over a sample application of our making. Our CACG construction algorithm accurately identifies service call targets 81.07% of the time on average. Our taint analysis obtains a F-Measure of 95.60% over a benchmark. The use of a CACG, compared to a naive approach, improves the F-Measure of a taint analysis from 66.67% to 100.00% for our sample application.