Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
Expertise browser: a quantitative approach to identifying expertise
Proceedings of the 24th International Conference on Software Engineering
Inferring Change Effort from Configuration Management Databases
METRICS '98 Proceedings of the 5th International Symposium on Software Metrics
Bayesian Analysis of Software Cost and Quality Models
ICSM '01 Proceedings of the IEEE International Conference on Software Maintenance (ICSM'01)
Towards a taxonomy of approaches for mining of source code repositories
MSR '05 Proceedings of the 2005 international workshop on Mining software repositories
Development of a hybrid cost estimation model in an iterative manner
Proceedings of the 28th international conference on Software engineering
Mining version archives for co-changed lines
Proceedings of the 2006 international workshop on Mining software repositories
Fine-grained processing of CVS archives with APFEL
eclipse '06 Proceedings of the 2006 OOPSLA workshop on eclipse technology eXchange
How Long Will It Take to Fix This Bug?
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
An empirical analysis of software effort estimation with outlier elimination
Proceedings of the 4th international workshop on Predictor models in software engineering
Tracking Your Changes: A Language-Independent Approach
IEEE Software
Comparison and evaluation of code clone detection techniques and tools: A qualitative approach
Science of Computer Programming
Automated trendline generation for accurate software effort estimation
Proceedings of the 3rd annual conference on Systems, programming, and applications: software for humanity
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Timesheets are an important instrument used to track time spent by team members in a software project on the tasks assigned to them. In a typical project, developers fill timesheets manually on a periodic basis. This is often tedious, time consuming and error prone. Over or under reporting of time spent on tasks causes errors in billing development costs to customers and wrong estimation baselines for future work, which can have serious business consequences. In order to assist developers in filling their timesheets accurately, we present a tool called Timesheet Assistant (TA) that non-intrusively mines developer activities and uses statistical analysis on historical data to estimate the actual effort the developer may have spent on individual assigned tasks. TA further helps the developer or project manager by presenting the details of the activities along with effort data so that the effort may be seen in the context of the actual work performed. We report on an empirical study of TA in a software maintenance project at IBM that provides preliminary validation of its feasibility and usefulness. Some of the limitations of the TA approach and possible ways to address those are also discussed.