The possibility of introduction of a change in software cannot be denied as the request for upgrades and improved functionality keeps coming on. Implementing these changes require a systematic Change Impact Analysis (CIA) which is a step by step process under software maintenance. However, the most difficult phase in this systematic CIA process is the identification of an initial location of initiating the proposed change. Various techniques have been proposed to identify this initial location which comes under Feature Location Techniques. These techniques are aimed at finding areas in the software code and other software artifacts that implement a feature. The paper attempts to organize and structure existing work in the field of feature location by presenting a literature survey of recent feature location techniques whereby the techniques have been categorized according to the methodology followed, the tools proposed and their impact. The paper also discusses open issues and defines future directions in the field of feature location.

change impact analysis, feature location, software maintenance,concept location

[1] W.Li, S.Henry, “Maintenance support for object-oriented programs” Vol 7, No 2, pp. 131–147, 1995.
[2] S Bohner, R. Arnold, “Software Change Impact Analysis”, IEEE Computer Society Press: Los Alamitos, CA, USA, 1996.
[3] S.L. Pfleeger, S.A.Bohner, “A framework for software maintenance metrics”, In the Proceedings of the International Conference on Software Maintenance, Washington, DC, pp. 320–327, 1990.
[4] E. Horowitz, R.C. Williamson,”SODOS: a software documentation support environment—its definition”, IEEE Transactions on Software Engineering, Vol 12, No 8, pp. 849–859. 1986.
[5] N.Wilde, M.Scully,”Software Reconnaissance: Mapping Program Features to Code”, Software Maintenance: Research and Practice, vol. 7, pp. 49-62, 1995.
[6] V. Rajlich and P. Gosavi,), "Incremental Change in Object-Oriented Programming", IEEE Software, pp. 2-9. 2004.
[7] A.Dhamija, S.Sikka, “Software Change Management: A Quantified Perspective”, International Journal of Engineering & Technology-UAE, Vol 7, Issue 3.12, pp. 963-967. 2018.
[8] B.Dit, M.Revelle, M.Gethers, D.Poshyvanyk, “Feature location in source code: a taxonomy and survey”, Journal of Software Maintenance and Evolution: Research and Practice, 2011.
[9] M. Revelle and D. Poshyvanyk, “An Exploratory Study on Assessing Feature Location Techniques”, In Proceedings of 17th IEEE International Conference on Program Comprehension (ICPC`09), Vancouver, British Columbia, Canada, May 17-19, pp. 218-222, 2009.
[10] J. Rubin and M. Chechik, “A survey of feature location techniques,” Domain Engineering: Product Lines, Conceptual Models, and Languages. Springer, pp. 29–58, 2013.
[11] N. Alhindawi, J. Alsakran, A. Rodan, H. Faris, “A Survey of Concepts Location Enhancement for Program Comprehension and Maintenance”, Journal of Software Engineering and Applications, Vol 7, pp. 413-421, 2014.
[12] E. Hill, B. Sisman, A.C. Kak, “On the use of positional proximity in IR-based feature location”, CSMR-WCRE,pp. 318–322, 2014.
[13] F. Beck, B. Dit, J. Velasco-Madden, D. Weiskopf, and D. Poshyvanyk. Rethinking user interfaces for feature location. In Proceedings of the 23rd IEEE International Conference on Program Comprehension, ICPC, pages 151–162. IEEE, 2015
[14] C.S. Corley, K.L. Kashuda, N.A. Kraft, "Modeling changeset topics for feature location" , ICSME, Germany, IEEE., pp. 71-80, 2015.
[15] C.S. Corley, K Damevski and N.A. Kraft, Exploring the Use of Deep Learning for Feature Location, , ICSME, Germany, IEEE, 2015.
[16] M. Chochlov, M. English and J. Buckley, “Using Changeset Descriptions as a Data Source to Assist Feature Location”,IEEE SCAM, Breman Germany, 2015.
[17] G Liang, Y Dang, H Chen, L Mei, S Li, Y M Chee, “What Code Implements Such Service? A Behavior Model Based Feature Location Approach”, IEEE International Conference on Services Computing, 2016.
[18] B.Dit, L.Guerrouj, D.Poshyvanyk and G.Antoniol,"Can Better Identifier Splitting Techniques Help Feature Location?" In Proceedings. of 19th IEEE International Conference on Program Comprehension (ICPC`11), Kingston, Ontario, Canada, June 22-24 pp. 11-20, 2011.
[19] J.T. Burke, “Utilizing Feature Location Techniques for Feature Addition and Feature Enhancement”, In Proceedings of the 29th ACM/IEEE international conference on Automated software engineering pp. 879-882, 2014.
[20] T. Eisenbarth, R. Koschke and D. Simon, "Locating Features in Source Code" , IEEE Transactions on Software Engineering vol. 29 no. 3, pp. 210 – 224, 2003.
[21] X.Peng, X.Zhenchang, T.Xi, Yijun and Zhao, Wenyun). “Improving feature location using structural similarity and iterative graph mapping”, Journal of Systems and Software, 86(3) pp. 664–676, 2013.
[22] M.D.A.Maia, R.F. Lafetá, “On the impact of trace-based feature location in the performance of software maintainers”, Journal of Systems and Software, v.86 n.4, p.1023-1037, April, 2013.
[23] S. Zamani, S.P. Lee, R.Shokripour, J.Anvik J, “A noun-based approach to feature location using time-aware term-weighting”. Inf Softw Technol, Vol 56, No 8, pp. 991-1011, 2014.
[24] G.Scanniello, A. Marcus, D. Pascale, “Link analysis algorithms for static concept location: an empirical assessment”. Empirical Softw Eng, pp. 1–55, 2014.
[25] K. Damevski D. Shepherd L. Pollock "A field study of how developers locate features in source code" Empirical Software Engineering, pp. 1-24, 2015.
[26] Aanchal, S. kumar, "Metrics for Software Components in Object Oriented Environments: A Survey", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.2, pp.25-29, 2013.
[27] Anandi Mahajan, Pankaj Sharma, "Object Oriented Requirement management Tools for maintaining of status of requirements", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.6, pp.27-30, 2018