Jon Grov

• Jørgensen, Magne & Grov, Jon (2021). A field experiment on trialsourcing and the effect of contract types on outsourced software development. Information and Software Technology. ISSN 0950-5849. 134, p. 106559–106559. Full text in Research Archive Show summary

  Context: To ensure the success of software projects, it is essential to select skilled developers and to use suitable work contracts. Objective: This study tests two hypotheses: (i) the use of work-sample testing (trialsourcing) improves the selection of skilled software developers; and (ii) the use of contracts based on hourly payment leads to better software project outcomes than fixed-price contracts. Method: Fifty-seven software freelancers with relevant experience and good evaluation scores from previous clients were invited to complete a two-hour long trialsourcing task to qualify for a software development project. Thirty-six developers completed the trialsourcing task with acceptable performance, and, based on a stratified allocation process, were asked to give a proposal based on an hourly payment or a fixed-price contract. Eight hourly payment-based and eight fixed-priced proposals were accepted. The process and product characteristics of the completion of these 16 projects were collected and analysed. Results and Conclusion: Only partial support for our hypotheses was observed. While the use of trialsourcing may have prevented the selection of developers with insufficient skills, the performance on the trialsourcing task of the selected developers did not predict performance on the project. The use of hourly payments led to lower costs than fixed-price contracts, but not to improved processes or products. We plan to follow up these, to us unexpected, results with research on how to design more skill-predictive trialsourcing tasks, and when and why different project contexts give different contract consequences.

• Bobba, Rakesh; Grov, Jon; Gupta, Indranil; Liu, Si; Meseguer, Jose & Ölveczky, Peter Csaba [Show all 7 contributors for this article] (2018). Survivability: Design, Formal Modeling, and Validation of Cloud Storage Systems Using Maude, Assured Cloud Computing. Wiley-IEEE Computer Society Press. ISSN 9781119428633. p. 10–48. doi: 10.1002/9781119428497.ch2. Full text in Research Archive
• Grov, Jon & Ølveczky, Peter Csaba (2014). Increasing Consistency in Multi-site Data Stores: Megastore-CGC and Its Formal Analysis. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 8702, p. 159–174. doi: 10.1007/978-3-319-10431-7_12. Full text in Research Archive
• Grov, Jon & Ølveczky, Peter Csaba (2014). Formal modeling and analysis of Google's megastore in real-time maude. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 8373, p. 494–519. doi: 10.1007/978-3-642-54624-2_25. Full text in Research Archive
• Grov, Jon & Ølveczky, Peter Csaba (2013). Scalable and Fully Consistent Transactions in the Cloud through Hierarchical Validation. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 8059, p. 26–38. doi: 10.1007/978-3-642-40053-7_3. Full text in Research Archive
• Grov, Jon & Normann, Ragnar (2006). Technical note: Replication graphs revisited. Journal of computer and system sciences. ISSN 0022-0000. 72(8), p. 1251–1261. doi: 10.1016/j.jcss.2006.02.004. Full text in Research Archive
• Grov, Jon; Soares, Luís; Jr., Alfrânio Correia; Pereira, José; Oliveira, Rui & Pedone, Fernando (2006). A Pragmatic Protocol for Database Replication in Interconnected Clusters. In Jeske, Daniel; Ciardo, Gianfranco & Dai, Yuan-Shun (Ed.), Proceedings - 12th Pacific Rim International Symposium on Dependable Computing. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9780769527246. p. 230–237. Full text in Research Archive

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• Skrikerud, Anne Maria & Grov, Jon (2007). Privacy at Risk. Full text in Research Archive
• Skrikerud, Anne Maria & Grov, Jon (2006). The dubious uniqueness of the genetic information. Full text in Research Archive
• Grov, Jon; Soares, Luís; Jr., Alfrânio Correia; José, Pereira; Oliveira, Rui & Pedone, Fernando (2006). A Pragmatic Protocol for Database Replication in Interconnected Clusters. Full text in Research Archive
• Grov, Jon & Ölveczky, Peter Csaba (2014). Transactional Data Management for Multi-Site Systems: New Approaches and Formal Analysis. Universitetet i Oslo. Full text in Research Archive Show summary

  High-impact systems, notably systems used in health care, public infrastructure, traffic control, and finance, depend on a data management facility that can tolerate many types of failure. In addition, the prevalent adoption of cloud systems increase the demand for commodity services to provide consistent and efficient data storage services. For commodity services, strong fault tolerance and scalability are necessary. However, achieving the desired level of fault tolerance requires multi-site repli- cation: multiple copies of data are stored at geographically distant sites. Combining such data replication with the transactional consistency guarantees provided by a traditional database system is challenging, and users are usually required to choose between consistency, performance, and fault tolerance. Google's Megastore is among the most mature multi-site data stores providing transactions. However, one challenge with Megastore is that it requires data to be grouped into a set of relatively fine-grained partitions, and transactional consistency is only provided within one partition. In some usage scenarios, this represents a signifficant disadvantage. The main contributions of this thesis are: 1) three new approaches for transactional multi-site data management, including an extension of Megastore to provide cross-partition consistency; 2) a formal-methods-based analysis strategy using Real-Time Maude to assess both performance and correctness; and 3) a formal model of Megastore that provides the first reasonably detailed publicly available description of the Megastore approach to data management in multisite data stores.

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