@INPROCEEDINGS{Rahman22-SE4RAI-ChallengesMLAIndustry,
   AUTHOR       = {Md Saidur Rahman and Foutse Khomh and Emilio Rivera and 
      Yann-Ga�l Gu�h�neuc and Bernd Lehnert},
   BOOKTITLE    = {Proceedings of the 1<sup>th</sup> ICSE International Workshop on Software Engineering for Responsible Artificial Intelligence (SE4RAI)},
   TITLE        = {Challenges in Machine Learning Application Development: 
      An Industrial Experience Report},
   YEAR         = {2022},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Qinghua Lu and Xiwei (Sherry) Xu and Liming Zhu and 
      John Grundy},
   MONTH        = {May},
   NOTE         = {8 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {21--28},
   PUBLISHER    = {ACM Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Program comprehension</b>, 
      Venue: <i>SE4RAI</i>},
   URL          = {http://www.ptidej.net/publications/documents/SE4RAI22.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/SE4RAI22.ppt.pdf},
   ABSTRACT     = {SAP is the market leader in enterprise application 
      software offering an end-to-end suite of applications and services to 
      enable their customers worldwide to operate their business. 
      Especially, retail customers of SAP deal with millions of sales 
      transactions for their day-to-day business. Transactions are created 
      during retail sales at the point of sale (POS) terminals and those 
      transactions are then sent to some central servers for validations 
      and other business operations. A considerable proportion of the 
      retail transactions may have inconsistencies or anomalies due to many 
      technical and human errors. SAP provides an automated process for 
      error detection but still requires a manual process by dedicated 
      employees using workbench software for correction. However, manual 
      corrections of these errors are time-consuming, labor-intensive, and 
      might be prone to further errors due to incorrect modifications. 
      Thus, automated detection and correction of transaction errors are 
      very important regarding their potential business values and the 
      improvement in the business workflow. In this paper, we report on our 
      experience from a project where we develop an AI-based system to 
      automatically detect transaction errors and propose corrections. We 
      identify and discuss the challenges that we faced during this 
      collaborative research and development project, from two distinct 
      perspectives: Software Engineering and Machine Learning. We report on 
      our experience and insights from the project with guidelines for the 
      identified challenges. We collect developers' feedback for 
      qualitative analysis of our findings. We believe that our findings 
      and recommendations can help other researchers and practitioners 
      embarking into similar endeavours.}
}

{"_id":"rxXwKPXEey5EDv6ze","bibbaseid":"rahman-khomh-rivera-guhneuc-lehnert-challengesinmachinelearningapplicationdevelopmentanindustrialexperiencereport-2022","author_short":["Rahman, M. S.","Khomh, F.","Rivera, E.","Gu�h�neuc, Y.","Lehnert, B."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Md","Saidur"],"propositions":[],"lastnames":["Rahman"],"suffixes":[]},{"firstnames":["Foutse"],"propositions":[],"lastnames":["Khomh"],"suffixes":[]},{"firstnames":["Emilio"],"propositions":[],"lastnames":["Rivera"],"suffixes":[]},{"firstnames":["Yann-Ga�l"],"propositions":[],"lastnames":["Gu�h�neuc"],"suffixes":[]},{"firstnames":["Bernd"],"propositions":[],"lastnames":["Lehnert"],"suffixes":[]}],"booktitle":"Proceedings of the 1^th ICSE International Workshop on Software Engineering for Responsible Artificial Intelligence (SE4RAI)","title":"Challenges in Machine Learning Application Development: An Industrial Experience Report","year":"2022","optaddress":"","optcrossref":"","editor":[{"firstnames":["Qinghua"],"propositions":[],"lastnames":["Lu"],"suffixes":[]},{"firstnames":["Xiwei","(Sherry)"],"propositions":[],"lastnames":["Xu"],"suffixes":[]},{"firstnames":["Liming"],"propositions":[],"lastnames":["Zhu"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Grundy"],"suffixes":[]}],"month":"May","note":"8 pages.","optnumber":"","optorganization":"","pages":"21–28","publisher":"ACM Press","optseries":"","optvolume":"","keywords":"Topic: <b>Program comprehension</b>, Venue: <i>SE4RAI</i>","url":"http://www.ptidej.net/publications/documents/SE4RAI22.doc.pdf","pdf":"http://www.ptidej.net/publications/documents/SE4RAI22.ppt.pdf","abstract":"SAP is the market leader in enterprise application software offering an end-to-end suite of applications and services to enable their customers worldwide to operate their business. Especially, retail customers of SAP deal with millions of sales transactions for their day-to-day business. Transactions are created during retail sales at the point of sale (POS) terminals and those transactions are then sent to some central servers for validations and other business operations. A considerable proportion of the retail transactions may have inconsistencies or anomalies due to many technical and human errors. SAP provides an automated process for error detection but still requires a manual process by dedicated employees using workbench software for correction. However, manual corrections of these errors are time-consuming, labor-intensive, and might be prone to further errors due to incorrect modifications. Thus, automated detection and correction of transaction errors are very important regarding their potential business values and the improvement in the business workflow. In this paper, we report on our experience from a project where we develop an AI-based system to automatically detect transaction errors and propose corrections. We identify and discuss the challenges that we faced during this collaborative research and development project, from two distinct perspectives: Software Engineering and Machine Learning. We report on our experience and insights from the project with guidelines for the identified challenges. We collect developers' feedback for qualitative analysis of our findings. We believe that our findings and recommendations can help other researchers and practitioners embarking into similar endeavours.","bibtex":"@INPROCEEDINGS{Rahman22-SE4RAI-ChallengesMLAIndustry,\r\n AUTHOR = {Md Saidur Rahman and Foutse Khomh and Emilio Rivera and \r\n Yann-Ga�l Gu�h�neuc and Bernd Lehnert},\r\n BOOKTITLE = {Proceedings of the 1^th ICSE International Workshop on Software Engineering for Responsible Artificial Intelligence (SE4RAI)},\r\n TITLE = {Challenges in Machine Learning Application Development: \r\n An Industrial Experience Report},\r\n YEAR = {2022},\r\n OPTADDRESS = {},\r\n OPTCROSSREF = {},\r\n EDITOR = {Qinghua Lu and Xiwei (Sherry) Xu and Liming Zhu and \r\n John Grundy},\r\n MONTH = {May},\r\n NOTE = {8 pages.},\r\n OPTNUMBER = {},\r\n OPTORGANIZATION = {},\r\n PAGES = {21--28},\r\n PUBLISHER = {ACM Press},\r\n OPTSERIES = {},\r\n OPTVOLUME = {},\r\n KEYWORDS = {Topic: <b>Program comprehension</b>, \r\n Venue: <i>SE4RAI</i>},\r\n URL = {http://www.ptidej.net/publications/documents/SE4RAI22.doc.pdf},\r\n PDF = {http://www.ptidej.net/publications/documents/SE4RAI22.ppt.pdf},\r\n ABSTRACT = {SAP is the market leader in enterprise application \r\n software offering an end-to-end suite of applications and services to \r\n enable their customers worldwide to operate their business. \r\n Especially, retail customers of SAP deal with millions of sales \r\n transactions for their day-to-day business. Transactions are created \r\n during retail sales at the point of sale (POS) terminals and those \r\n transactions are then sent to some central servers for validations \r\n and other business operations. A considerable proportion of the \r\n retail transactions may have inconsistencies or anomalies due to many \r\n technical and human errors. SAP provides an automated process for \r\n error detection but still requires a manual process by dedicated \r\n employees using workbench software for correction. However, manual \r\n corrections of these errors are time-consuming, labor-intensive, and \r\n might be prone to further errors due to incorrect modifications. \r\n Thus, automated detection and correction of transaction errors are \r\n very important regarding their potential business values and the \r\n improvement in the business workflow. In this paper, we report on our \r\n experience from a project where we develop an AI-based system to \r\n automatically detect transaction errors and propose corrections. We \r\n identify and discuss the challenges that we faced during this \r\n collaborative research and development project, from two distinct \r\n perspectives: Software Engineering and Machine Learning. We report on \r\n our experience and insights from the project with guidelines for the \r\n identified challenges. We collect developers' feedback for \r\n qualitative analysis of our findings. We believe that our findings \r\n and recommendations can help other researchers and practitioners \r\n embarking into similar endeavours.}\r\n}\r\n\r\n","author_short":["Rahman, M. S.","Khomh, F.","Rivera, E.","Gu�h�neuc, Y.","Lehnert, B."],"editor_short":["Lu, Q.","Xu, X. (.","Zhu, L.","Grundy, J."],"key":"Rahman22-SE4RAI-ChallengesMLAIndustry","id":"Rahman22-SE4RAI-ChallengesMLAIndustry","bibbaseid":"rahman-khomh-rivera-guhneuc-lehnert-challengesinmachinelearningapplicationdevelopmentanindustrialexperiencereport-2022","role":"author","urls":{"Paper":"http://www.ptidej.net/publications/documents/SE4RAI22.doc.pdf"},"keyword":["Topic: <b>Program comprehension</b>","Venue: <i>SE4RAI</i>"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"http://www.yann-gael.gueheneuc.net/Work/Publications/Biblio/complete-bibliography.bib","dataSources":["8vn5MSGYWB4fAx9Z4"],"keywords":["topic: <b>program comprehension</b>","venue: <i>se4rai</i>"],"search_terms":["challenges","machine","learning","application","development","industrial","experience","report","rahman","khomh","rivera","gu�h�neuc","lehnert"],"title":"Challenges in Machine Learning Application Development: An Industrial Experience Report","year":2022}