{"title":"在堆栈溢出问题中报告的问题可以重现吗?一项探索性研究","authors":"Saikat Mondal, M. M. Rahman, C. Roy","doi":"10.1109/MSR.2019.00074","DOIUrl":null,"url":null,"abstract":"Software developers often look for solutions to their code level problems at Stack Overflow. Hence, they frequently submit their questions with sample code segments and issue descriptions. Unfortunately, it is not always possible to reproduce their reported issues from such code segments. This phenomenon might prevent their questions from getting prompt and appropriate solutions. In this paper, we report an exploratory study on the reproducibility of the issues discussed in 400 questions of Stack Overflow. In particular, we parse, compile, execute and even carefully examine the code segments from these questions, spent a total of 200 man hours, and then attempt to reproduce their programming issues. The outcomes of our study are two-fold. First, we find that 68% of the code segments require minor and major modifications in order to reproduce the issues reported by the developers. On the contrary, 22% code segments completely fail to reproduce the issues. We also carefully investigate why these issues could not be reproduced and then provide evidence-based guidelines for writing effective code examples for Stack Overflow questions. Second, we investigate the correlation between issue reproducibility status (of questions) and corresponding answer meta-data such as the presence of an accepted answer. According to our analysis, a question with reproducible issues has at least three times higher chance of receiving an accepted answer than the question with irreproducible issues.","PeriodicalId":6706,"journal":{"name":"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)","volume":"6 1","pages":"479-489"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Can Issues Reported at Stack Overflow Questions be Reproduced? An Exploratory Study\",\"authors\":\"Saikat Mondal, M. M. Rahman, C. Roy\",\"doi\":\"10.1109/MSR.2019.00074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software developers often look for solutions to their code level problems at Stack Overflow. Hence, they frequently submit their questions with sample code segments and issue descriptions. Unfortunately, it is not always possible to reproduce their reported issues from such code segments. This phenomenon might prevent their questions from getting prompt and appropriate solutions. In this paper, we report an exploratory study on the reproducibility of the issues discussed in 400 questions of Stack Overflow. In particular, we parse, compile, execute and even carefully examine the code segments from these questions, spent a total of 200 man hours, and then attempt to reproduce their programming issues. The outcomes of our study are two-fold. First, we find that 68% of the code segments require minor and major modifications in order to reproduce the issues reported by the developers. On the contrary, 22% code segments completely fail to reproduce the issues. We also carefully investigate why these issues could not be reproduced and then provide evidence-based guidelines for writing effective code examples for Stack Overflow questions. Second, we investigate the correlation between issue reproducibility status (of questions) and corresponding answer meta-data such as the presence of an accepted answer. According to our analysis, a question with reproducible issues has at least three times higher chance of receiving an accepted answer than the question with irreproducible issues.\",\"PeriodicalId\":6706,\"journal\":{\"name\":\"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)\",\"volume\":\"6 1\",\"pages\":\"479-489\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSR.2019.00074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSR.2019.00074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Can Issues Reported at Stack Overflow Questions be Reproduced? An Exploratory Study
Software developers often look for solutions to their code level problems at Stack Overflow. Hence, they frequently submit their questions with sample code segments and issue descriptions. Unfortunately, it is not always possible to reproduce their reported issues from such code segments. This phenomenon might prevent their questions from getting prompt and appropriate solutions. In this paper, we report an exploratory study on the reproducibility of the issues discussed in 400 questions of Stack Overflow. In particular, we parse, compile, execute and even carefully examine the code segments from these questions, spent a total of 200 man hours, and then attempt to reproduce their programming issues. The outcomes of our study are two-fold. First, we find that 68% of the code segments require minor and major modifications in order to reproduce the issues reported by the developers. On the contrary, 22% code segments completely fail to reproduce the issues. We also carefully investigate why these issues could not be reproduced and then provide evidence-based guidelines for writing effective code examples for Stack Overflow questions. Second, we investigate the correlation between issue reproducibility status (of questions) and corresponding answer meta-data such as the presence of an accepted answer. According to our analysis, a question with reproducible issues has at least three times higher chance of receiving an accepted answer than the question with irreproducible issues.