Context dependent maintenance effort estimation: Case study in a small software company

This paper presents an approach to software maintenance effort estimation based on the analysis of software maintenance requests available in issue tracking system in a very small local software company. Over 1900 requests, collected during 19 months in 2010 and 2011, were selected for analysis. The approach takes into account: the frequency of submitted user requests for particular periods of time important for organizing work in the company, the existence of maintenance service agreement for clients, the number of programmers assigned to the task associated to each request, and the number of working hours required for requests solving. The approach calculates correlation and establishes linear regression between frequencies of submitted user requests and the average time required for completing requests. This approach estimates an average number of working hours for processing user requests in periods of time that are important for internal company organization. In the paper are also discussed implications for practice and research, and provided recommendations for adapting this approach to other small software companies.

[1]  T.C. Lethbridge,et al.  Guide to the Software Engineering Body of Knowledge (SWEBOK) and the Software Engineering Education Knowledge (SEEK) - a preliminary mapping , 2001, 10th International Workshop on Software Technology and Engineering Practice.

[2]  Andrea De Lucia,et al.  Assessing effort estimation models for corrective maintenance through empirical studies , 2005, Inf. Softw. Technol..

[3]  Zeljko Stojanov,et al.  Discovering automation level of software change request process from qualitative empirical data , 2011, 2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI).

[4]  Ita Richardson,et al.  Guest Editors' Introduction: Why are Small Software Organizations Different? , 2007, IEEE Software.

[5]  Liguo Yu Indirectly predicting the maintenance effort of open-source software , 2006, J. Softw. Maintenance Res. Pract..

[6]  Leslie Kish,et al.  Statistical Design for Research: Kish/Statistical Design for Research , 2005 .

[7]  Alain Abran,et al.  A Software Maintenance Maturity Model (S3M): Measurement Practices at Maturity Levels 3 and 4 , 2009, SQM@CSMR.

[8]  Hareton K. N. Leung,et al.  Estimating Maintenance Effort by Analogy , 2002, Empirical Software Engineering.

[9]  Mario Piattini,et al.  A software maintenance methodology for small organizations: Agile_MANTEMA , 2012, J. Softw. Evol. Process..

[10]  Barry W. Boehm,et al.  Software Defect Reduction Top 10 List , 2001, Computer.

[11]  Magne Jørgensen,et al.  Experience With the Accuracy of Software Maintenance Task Effort Prediction Models , 1995, IEEE Trans. Software Eng..

[12]  Giuliano Antoniol,et al.  Trend Analysis and Issue Prediction in Large-Scale Open Source Systems , 2008, 2008 12th European Conference on Software Maintenance and Reengineering.

[13]  Janice Singer,et al.  Guide to Advanced Empirical Software Engineering , 2007 .

[14]  Sheldon H. Stein,et al.  Understanding Regression Analysis , 1990 .

[15]  Phongphun Kijsanayothin,et al.  On modeling software defect repair time , 2009, Empirical Software Engineering.

[16]  Gautam Shroff,et al.  Dynamics of software maintenance , 2004, SOEN.

[17]  Inge S. Helland,et al.  On the Interpretation and Use of R 2 in Regression Analysis , 1987 .

[19]  Barry Boehm,et al.  Top 10 list [software development] , 2001 .

[20]  Hans van Vliet,et al.  Two case studies in measuring software maintenance effort , 1998, Proceedings. International Conference on Software Maintenance (Cat. No. 98CB36272).

[21]  Keith H. Bennett,et al.  Software maintenance and evolution: a roadmap , 2000, ICSE '00.

[22]  C. Tompkins Using and Interpreting Linear Regression and Correlation Analyses: Some Cautions and Considerations , 1993 .

[23]  D. Dobrilovic,et al.  Identifying properties of software change request process: Qualitative investigation in very small software companies , 2011, 2011 IEEE 9th International Symposium on Intelligent Systems and Informatics.

[24]  Tore Dybå,et al.  Process Improvement in Practice: A Handbook for It Companies (The Kluwer International Series in Software Engineering, 9) , 2004 .