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Information needs for software development analytics

Raymond P. L. Buse, Thomas Zimmermann
2012 2012 34th International Conference on Software Engineering (ICSE)  
The survey responses lead us to propose several guidelines for analytics tools in software development including: Engineers do not necessarily have much expertise in data analysis; thus tools should be  ...  We asked about their decision making process, their needs for artifacts and indicators, and scenarios in which they would use analytics.  ...  in our study, meet with us, and provide their valuable insights and feedback.  ... 
doi:10.1109/icse.2012.6227122 dblp:conf/icse/BuseZ12 fatcat:sexjtintu5ay3pipxyfktl6cf4

Message from the RCoSE-DDrEE 2019 Workshop Organizers

2019 2019 IEEE/ACM Joint 4th International Workshop on Rapid Continuous Software Engineering and 1st International Workshop on Data-Driven Decisions, Experimentation and Evolution (RCoSE/DDrEE)  
for automated experimentation • Case studies on automated continuous experimentation practices in industry • Data-driven decision-making at runtime • Data-driven engineering The Joint RCoSE-DDrEE 2019  ...  Rapid continuous software engineering refers to the organizational capability to develop, release and learn from software in very short rapid cycles, typically hours, days or very small numbers of weeks  ...  for automated experimentation • Case studies on automated continuous experimentation practices in industry • Data-driven decision-making at runtime • Data-driven engineering The Joint RCoSE-DDrEE 2019  ... 
doi:10.1109/rcose/ddree.2019.00005 fatcat:w543gyxlafbubaboykogawkwmu

Analytics for software development

Raymond P.L. Buse, Thomas Zimmermann
2010 Proceedings of the FSE/SDP workshop on Future of software engineering research - FoSER '10  
We discuss how analytics works, why it's a good fit for software engineering, and the research problems that must be overcome in order to realize its promise.  ...  Despite large volumes of data and many types of metrics, software projects continue to be difficult to predict and risky to conduct.  ...  of analysis, data, and systematic reasoning to make decisions.  ... 
doi:10.1145/1882362.1882379 dblp:conf/sigsoft/BuseZ10 fatcat:qivu6uh7kndo7n6jhf2vl7swym

Software intelligence

Ahmed E. Hassan, Tao Xie
2010 Proceedings of the FSE/SDP workshop on Future of software engineering research - FoSER '10  
We coin the name SI as an inspiration from the Business Intelligence (BI) field, which offers concepts and techniques to improve business decision making by using fact-based support systems.  ...  Similarly, SI offers software practitioners (not just developers) up-to-date and pertinent information to support their daily decision-making processes.  ...  Hassan is the NSERC RIM Industrial Chair in Software Engineering.  ... 
doi:10.1145/1882362.1882397 dblp:conf/sigsoft/HassanX10 fatcat:jdqqen4pgbalvf7ltinj5mtwhi

Digital Sovereignty and Software Engineering for the IoT-laden, AI/ML-driven Era [article]

Christian Berger
2022 arXiv   pre-print
maintained, and evolved using cloud-powered dashboards and data analytics pipelines that process, aggregate, and analyze countless data points preferably in real-time.  ...  Today's software engineering already needs to deal with challenges originating from the multidisciplinarity that is required to realize IoT products: Many variants consist of sensor/actuator-powered systems  ...  for fair, inclusive, and equal data-driven decision making in both, products and engineering processes.  ... 
arXiv:2205.14137v1 fatcat:saksyv35hra7foez2xmcpcfucq

Evidence-based software production

James Kirby, David M. Weiss, Robyn R. Lutz
2010 Proceedings of the FSE/SDP workshop on Future of software engineering research - FoSER '10  
Achieving the deeper understanding needed to transform software production requires collecting and using evidence on a large scale. This paper proposes some steps toward that outcome.  ...  Software development remains a labor-intensive process in which delays and cost overruns are common, and responding to installed software's errors, anomalies, vulnerabilities, and lack of interoperability  ...  ACKNOWLEDGMENTS Thanks to Grady Campbell and Jon Bentley for helpful comments. We acknowledge NSF grants 0541163 and 0916275, and support from ONR and DDR&E/S&T/IS.  ... 
doi:10.1145/1882362.1882403 dblp:conf/sigsoft/KirbyWL10 fatcat:5gsqpaarwjhybkdjj75qds4fxu

A Survey of Bayesian Network Models for Decision Making System in Software Engineering

Nageswarao M., N. Geethanjali
2016 International Journal of Computer Applications  
A large number of software metrics are discovered and used for metric prediction in the literature.  ...  Bayesian network model is used to predict the defect correction at various levels of the software development.  ...  Data Analysis Data Normalization Structure Analysis And Decision Making in Bayesian networks.  ... 
doi:10.5120/ijca2016906330 fatcat:cq45rwqsubaadfwszki26bap6q

Multi-site Software Engineering Ontology Instantiations Management Using Reputation Based Decision Making [chapter]

Pornpit Wongthongtham, Farookh Khadeer Hussain, Elizabeth Chang, Tharam S. Dillon
2008 Lecture Notes in Computer Science  
Software engineering ontology instantiations signify project information which is shared and has evolved to reflect project development, changes in the software requirements or in the design process, to  ...  In multi-site distributed environment, team members in the software engineering projects have naturally an interaction with each other and share lots of project data/agreement amongst themselves.  ...  The ability to make use of the software engineering knowledge, described in the software engineering ontology, enables applications in the systems to have capabilities in managing instance knowledge in  ... 
doi:10.1007/978-3-540-89784-2_7 fatcat:dl2kgbknk5flrccnaxam57s4ce

Ontology-based multi-site software development methodology and tools

P. Wongthongtham, E. Chang, T.S. Dillon, I. Sommerville
2006 Journal of systems architecture  
, to raise issues, to make decisions and to find answers in a multi-site distributed environment can become very large.  ...  follow the project plan, and how to carry out a discussion over a multi-site distributed environment and to make a just-in-time decision are the challenge.  ...  The decision maker agent has its own database to store data for decision making occurring in the system.  ... 
doi:10.1016/j.sysarc.2006.06.008 fatcat:wvcp5ueapvadbffaho3kayg6te

Towards evidence‐based decision‐making for identification and usage of assets in composite software: A research roadmap

Claes Wohlin, Efi Papatheocharous, Jan Carlson, Kai Petersen, Emil Alégroth, Jakob Axelsson, Deepika Badampudi, Markus Borg, Antonio Cicchetti, Federicio Ciccozzi, Thomas Olsson, Séverine Sentilles (+3 others)
2021 Journal of Software: Evolution and Process  
Software engineering is decision intensive. Evidence-based software engineering is suggested for decision-making concerning the use of methods and technologies when developing software.  ...  Software development often includes the reuse of software assets, for example, open-source components. Which components to use have  ...  software engineering and their decision-making to be informed by evidence.  ... 
doi:10.1002/smr.2345 fatcat:lcrb3azt55akdpyvnu6iy42hku

Data mining for software engineering and humans in the loop

Leandro L. Minku, Emilia Mendes, Burak Turhan
2016 Progress in Artificial Intelligence  
This field is concerned with the use of data mining to provide useful insights into how to improve software engineering processes and software itself, supporting decision-making.  ...  This makes adoption of data mining by software engineering practitioners difficult.  ...  Software data have the potential to provide useful insights into how to improve software engineering processes and software itself, supporting decision-making.  ... 
doi:10.1007/s13748-016-0092-2 fatcat:ngh5mlpj7rgfteg4kwsbzm63hi

The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development [article]

Richard Berntsson Svensson, Robert Feldt, Richard Torkar
2019 arXiv   pre-print
With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions.  ...  In this paper we investigated the experiences of using DDDM, and how data can improve decision making.  ...  -RQ2: To what extent is data used for decision making and requirements engineering in agile software developing companies?  ... 
arXiv:1904.03948v1 fatcat:cbsjgidlrfajrcfmyl6evfnyvi

The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development [chapter]

Richard Berntsson Svensson, Robert Feldt, Richard Torkar
2019 Lecture Notes in Business Information Processing  
With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions.  ...  In this paper we investigated the experiences of using DDDM, and how data can improve decision making.  ...  -RQ2: To what extent is data used for decision making and requirements engineering in agile software developing companies?  ... 
doi:10.1007/978-3-030-19034-7_5 fatcat:whi46lik4vaq3pl3ux4vn4lj2a

Bridging the marketing theory–practice gap with marketing engineering

Gary L Lilien, Arvind Rangaswamy, Gerrit H van Bruggen, Berend Wierenga
2002 Journal of Business Research  
We describe how marketing engineering harnesses marketing data and knowledge to facilitate decision making.  ...  In this paper, we describe the concept of marketing engineering -an approach to solving marketing decision problems -popularized by Lilien and Rangaswamy [Lilien GL,Rangaswamy A.  ...  A new area of marketing is emerging which helps to combine data, knowledge, managerial judgment, and computer software to facilitate decision making, which we call marketing engineering.  ... 
doi:10.1016/s0148-2963(00)00146-6 fatcat:6zhcwhyh45elhlioikxxdnvsce

Evidence Engineering

Audris Mockus
2015 Proceedings of the 8th India Software Engineering Conference on XXX - ISEC '15  
As computing becomes a commodity, software is omnipresent in all parts of life and, therefore, it either helps end users make decisions or it makes decisions for them.  ...  Moreover, the software has to ensure that the resulting data reflects the intended quantities, and that the quality of that data is sufficient to make important decisions either automatically of with human  ... 
doi:10.1145/2723742.2723767 dblp:conf/indiaSE/Mockus15 fatcat:nfra3tvm4ba3nnz3uxxrrbcz2a
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