article

Heuristic expansion of feature mappings in evolving program families

Authors:

Alessandro Garcia,

Jaejoon LeeAuthors Info & Claims

Software—Practice & Experience, Volume 44, Issue 11

Pages 1315 - 1349

https://doi.org/10.1002/spe.2200

Published: 01 November 2014 Publication History

Abstract

Establishing explicit mappings between features and their implementation elements in code is one of the critical factors to maintain and evolve software systems successfully. This is especially important when developers have to evolve program families, which have evolved from one single core system to similar but different systems to accommodate various requirements from customers. Many techniques and tools have emerged to assist developers in the feature mapping activity. However, existing techniques and tools for feature mapping are limited as they operate on a single program version individually. Additionally, existing approaches are limited to recover features on demand, that is, developers have to run the tools for each family member version individually. In this paper, we propose a cohesive suite of five mapping heuristics addressing those two limitations. These heuristics explore the evolution history of the family members in order to expand feature mappings in evolving program families. The expansion refers to the action of automatically generating the feature mappings for each family member version by systematically considering its previous change history. The mapping expansion starts from seed mappings and continually tracks the features of the program family, thus eliminating the need of on demand algorithms. Additionally, we present the MapHist tool that provides support to the application of the proposed heuristics. We evaluate the accuracy of our heuristics through two evolving program families from our industrial partners. Copyright ©2013 John Wiley & Sons, Ltd.

References

[1]

Chen K, Rajlich V. Case study of feature location using dependence graph. In Proceedings of the International Workshop on Program Comprehension, <bookSeriesTitle>IWPC</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 2000; pp.241-249.

[2]

Eisenbarth T, Koschke R, Simon D. Locating features in source code. IEEE Transactions on Software Engineering 2003; Volume 29: pp.210-224.

[3]

Rohatgi A, Hamou-Lhadj A, Rilling J. An approach for mapping features to code based on static and dynamic analysis. In Proceedings of the International Conference on Program Comprehension, <bookSeriesTitle>ICPC</bookSeriesTitle>. IEEE Computer Society: Los Alamitos, CA, USA, 2008; pp.236-241.

[4]

Wilde N, Scully M. Software reconnaissance: mapping program features to code. Journal of Software Maintenance 1995; Volume 7: pp.49-62.

[5]

Kang K, Cohen S, Hess J, Novak W, Peterson S. Feature-oriented domain analysis foda feasibility study. Technical Report, Carnegie-Mellon University Software Engineering Institute, 1990.

[6]

Figueiredo E, Cacho N, Sant'Anna C, Monteiro M, Kulesza U, Garcia A, Soares S, Ferrari F, Khan S, Filho FC, Dantas F. et al. Evolving software product lines with aspects: an empirical study on design stability. In Proceedings of the International Conference on Software Engineering, <bookSeriesTitle>ICSE</bookSeriesTitle>. ACM: NY, USA, 2008; pp.261-270.

[7]

Parnas D. On the design and development of program families. IEEE Transaction Software Engineering 1976; Volume 2: pp.1-9.

[8]

Novais R, Nunes C, Lima C, Cirilo E, Dantas F, Garcia A, Mendonca M. On the proactive and interactive visualization for feature evolution comprehension: an industrial investigation. In Proceedings of the International Conference on Software Engineering ICSE, Software Engineering in Practice. IEEE Computer Society: Washington, DC, USA, 2012; pp.1044-1053.

[9]

Kästner C, Kuhlemann M, Batory D. Automating feature-oriented refactoring of legacy applications. Workshop on Refactoring Tools in Conjunction With European Conference on Object-Oriented Programming, WRT, 2007; pp.62-63.

[10]

Ratzinger J, Sigmund T. Mining software evolution to predict refactoring. In Proceedings of the International Symposium on Empirical Software Engineering and Measurement, ESEM, 2007; pp.354-363.

[11]

Kang KC, Kim M, Lee J, Kim B. Feature-oriented re-engineering of legacy systems into product line assets - a case study. Proceedings of the International Software Product Line Conference, SPLC, 2005; pp.45-56.

[12]

Zhang G, Shen L, Peng X, Xing Z, Zhao W. Incremental and iterative reengineering towards software product line: an industrial case study. Proceedings of the International Conference on Software Maintenance, ICSM, 2011; pp.418-427.

[13]

Eixelsberger W, Ogris M, Gall H, Bellay B. Software architecture recovery of a program family. In Proceedings of the International Conference on Software Engineering, <bookSeriesTitle>ICSE</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 1998; pp.508-511.

[14]

Quilty G, Cinnéide M. Experiences with software product line development in risk management software. In Proceedings of the Software Product Line Conference SPLC, <bookSeriesTitle>SPLC</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 2011; pp.251-260.

[15]

Antoniol G, Guéhéneuc YG. Feature identification: a novel approach and a case study. In Proceedings of the International Conference on Software Maintenance, <bookSeriesTitle>ICSM</bookSeriesTitle>. IEEE Computer Society: Los Alamitos, USA, 2005; pp.357-366.

[16]

Biggerstaff T, Mitbander B, Webster D. Program understanding and the concept assignment problem. Communications of the ACM 1994; Volume 37: pp.72-82.

[17]

Eisenberg A, Volder KD. Dynamic feature traces: finding features in unfamiliar code. In Proceedings of the International Conference on Software Maintenance, <bookSeriesTitle>ICSM</bookSeriesTitle>. IEEE Computer Society: Washington, USA, 2005; pp.337-346.

[18]

Kellens A, Mens K, Tonella P. Transactions on aspect-oriented software development iv, 2007; pp.143-162.

[19]

Poshyvanyk D, Gueheneuc YG, Marcus A, Antoniol G, Rajlich V. Feature location using probabilistic ranking of methods based on execution scenarios and information retrieval. IEEE Transactions on Software Engineering 2007; Volume 33: pp.420-432.

[20]

Robillard M. An empirical study of the concept assignment problem. Technical Report, SOCS-TR-2007.3, School of Computer Science, McGill University, 2007.

[21]

Savage T, Revelle M, Poshyvanyk D. Flat3: feature location and textual tracing tool. In Proceedings of the International Conference on Software Engineering, Vol.Volume 2, <bookSeriesTitle>ICSE</bookSeriesTitle>. ACM: NY, USA, 2010; pp.255-258.

[22]

Nunes C, Garcia A, Figueiredo E, Lucena C. Revealing mistakes in concern mapping tasks: an experimental evaluation. In Proceedings of the European Conference on Software Maintenance and Reengineering, <bookSeriesTitle>CSMR</bookSeriesTitle>. IEEE Computer Society: Los Alamitos, USA, 2011; pp.101-110.

[23]

Robillard M, Murphy G. Representing concerns in source code. ACM Transactions on Software Engineering and Methodology TOSEM 2007; Volume 16.

[24]

Robillard M, Weigand-Warr F. Concernmapper: simple view-based separation of scattered concerns. In Proceedings of the OOPSLA Workshop on Eclipse Technology Exchange, <bookSeriesTitle>Eclipse</bookSeriesTitle>. ACM: NY, USA, 2005; pp.65-69.

[25]

Adams B, Jiang Z, Hassan A. Identifying crosscutting concerns using historical code changes. In Proceedings of the International Conference on Software Engineering, vol.Volume 1, <bookSeriesTitle>ICSE</bookSeriesTitle>. ACM: NY, USA, 2010; pp.305-314.

Digital Library

[26]

Nguyen T, Nguyen H, Nguyen H, Nguyen T. Aspect recommendation for evolving software. In Proceeding of the International Conference on Software Engineering, <bookSeriesTitle>ICSE</bookSeriesTitle>. ACM: NY, USA, 2011; pp.361-370.

[27]

Doar M. Jdiff - an html report of api differences, 2007. Available from: "http://www.jdiff.org/"[Accessed in September].

[28]

Kawrykow D, Robillard M. Non-essential changes in version histories. In Proceedings of the International Conference on Software Engineering, <bookSeriesTitle>ICSE '11</bookSeriesTitle>. ACM: New York, NY, USA, 2011; pp.351-360.

[29]

Dit B, Revelle M, Gethers M, Poshyvanyk D. Feature location in source code: a taxonomy and survey. Journal of Software Maintenance and Evolution: Research and Practice - JSME to appear 2011.

[30]

Cornelissen B, Zaidman A, <familyNamePrefix>van</familyNamePrefix>Deursen A, Moonen L, Koschke R. A systematic survey of program comprehension through dynamic analysis. IEEE Transactions on Software Engineering 2009; Volume 35: pp.684-702.

[31]

Koschke R, Quante J. On dynamic feature location. In Proceedings of the International Conference on Automated Software Engineering, <bookSeriesTitle>ASE</bookSeriesTitle>. ACM: NY, USA, 2005; pp.86-95.

[32]

Wong E, Horgan J, Gokhale S, Trivedi K. Locating program features using execution slices. In Proceedings of the Symposium on Application - Specific Systems and Software Engineering and Technology, <bookSeriesTitle>ASSET</bookSeriesTitle>. IEEE Computer Society: Washington, USA, 1999; pp.194-203.

[33]

Eaddy M, Zimmermann T, Sherwood KD, Garg V, Murphy GC, Nagappan N, Aho AV. Do crosscutting concerns cause defects?. IEEE Transactions on Software Engineering July 2008; Volume 34 Issue 4: pp.497-515.

[34]

Buckner J, Buchta J, Petrenko M, Rajlich V. Jripples: a tool for program comprehension during incremental change. In Proceedings of the International Workshop on Program Comprehension, <bookSeriesTitle>IWPC</bookSeriesTitle>. IEEE Computer Society: Washington, USA, 2005; pp.149-152.

[35]

Dit B, Revelle M, Poshyvanyk D. Integrating information retrieval, execution and link analysis algorithms to improve feature location in software. Empirical Software Engineering 2012: pp.1-33.

[36]

Eaddy M, Aho A, Antoniol G, Gueheneuc YG. Cerberus: tracing requirements to source code using information retrieval, dynamic analysis, and program analysis. In Proceedings of the International Conference on Program Comprehension, <bookSeriesTitle>ICPC</bookSeriesTitle>. IEEE Computer Society: Los Alamitos, USA, 2008; pp.53-62.

[37]

Poshyvanyk D, Marcus A. Combining formal concept analysis with information retrieval for concept location in source code. In Proceedings of the IEEE International Conference on Program Comprehension, <bookSeriesTitle>ICPC</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 2007; pp.37-48.

[38]

Revelle M, Gethers M, Poshyvanyk D. Using structural and textual information to capture feature coupling in object-oriented software. Empirical Software Engineering December 2011; Volume 16 Issue 6: pp.773-811.

[39]

Antoniol G, Canfora G, Casazza G, Lucia AD, Merlo E. Recovering traceability links between code and documentation. IEEE Transactions on Software Engineering 2002; Volume 28 Issue 10: pp.970-983.

[40]

Marcus A, Maletic JI. Recovering documentation-to-source-code traceability links using latent semantic indexing. In Proceedings of the International Conference on Software Engineering, <bookSeriesTitle>ICSE</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 2003; pp.125-135.

[41]

Breu S, Zimmermann T. Mining aspects from version history. In Proceedings of the International Conference on Automated Software Engineering, <bookSeriesTitle>ASE</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 2006; pp.221-230.

[42]

Bruntink M, <familyNamePrefix>van</familyNamePrefix>Deursen A, Tourwe T, <familyNamePrefix>van</familyNamePrefix>Engelen R. An evaluation of clone detection techniques for identifying crosscutting concerns. In Proceedings of the IEEE International Conference on Software Maintenance, <bookSeriesTitle>ICSM</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 2004; pp.200-209.

[43]

Bruntink M, <familyNamePrefix>van</familyNamePrefix>Deursen A, <familyNamePrefix>van</familyNamePrefix>Engelen R, Tourwe T. On the use of clone detection for identifying crosscutting concern code. IEEE Transactions on Software Engineering October 2005; Volume 31 Issue 10: pp.804-818.

[44]

Nunes C, Garcia A, Lucena C. History-sensitive recovery of product line features. In Proceedings of the International Conference on Software Maintenance - Doc. Symp., <bookSeriesTitle>ICSM</bookSeriesTitle>. IEEE Computer Society, 2010; pp.1-2.

[45]

Kim M, Sazawal V, Notkin D, Murphy G. An empirical study of code clone genealogies. In Proceedings of the International Symposium on Foundations of Software Engineering, <bookSeriesTitle>ESEC/FSE</bookSeriesTitle>. ACM: NY, USA, 2005; pp.187-196.

[46]

Carneiro G, Silva M, Mara L, Figueiredo E, Sant'Anna C, Garcia A, Mendonca M. Identifying code smells with multiple concern views. Proceedings of the Brazilian Symposium on Software Engineering, 2010; pp.128-137.

[47]

Fowler M. Refactoring: Improving the design of existing code. Addison-Wesley: Boston, MA, USA, 1999.

[48]

Nguyen T, Nguyen H, Pham N, Al-Kofahi J, Nguyen T. Clemanx: incremental clone detection tool for evolving software. In Proceedings of the International Conference on Software Engineering, <bookSeriesTitle>ICSE</bookSeriesTitle>. IEEE: Vancouver, BC, 2009; pp.437-438.

[49]

Hrbacek K, Jech T. Introduction to Set Theory, Monographs and Textbooks in Pure and Applied Mathematics. Marcel Dekker AG: New York, NY, 1944.

[50]

Figueiredo E, Carreiro B, Sant'Anna C, Garcia A, Whittle J, Nunes D. Crosscutting patterns and design stability: an exploratory analysis. Proceeding of the International Conference on Program Comprehension, ICPC, 2009; pp.138-147.

[51]

Nguyen T, Nguyen H, Pham N, Al-Kofahi J, Nguyen T. Clone-aware configuration management. In Proceedings of the International Conference on Automated Software Engineering, <bookSeriesTitle>ASE</bookSeriesTitle>. IEEE Computer Society: Washington, DC, USA, 2009; pp.123-134.

[52]

Robillard M, Murphy G. Concern graphs: finding and describing concerns using structural program dependencies. In Proceedings of the International Conference on Software Engineering, <bookSeriesTitle>ICSE</bookSeriesTitle>. ACM: NY, USA, 2002; pp.406-416.

[53]

Marin M, Deursen A, Moonen L. Identifying crosscutting concerns using fan-in analysis. ACM Transactions on Software Engineering and Methodology TOSEM 2007; Volume 17: pp.3:1-3:37.

[54]

Zhang D, Guo Y, Chen X. Automated aspect recommendation through clustering-based fan-in analysis. In Proceedings of the International Conference on Automated Software Engineering, <bookSeriesTitle>ASE</bookSeriesTitle>. IEEE Computer Society: Washington, USA, 2008; pp.278-287.

[55]

Gamma E, Helm R, Johnson R, Vlissides J. Design patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley: USA, 1994.

[56]

Nunes C, Garcia A, Lucena C, Lee J. History-sensitive heuristics for recovery of features in code of evolving program families. In Proceedings of the International Software Product Line Conference, <bookSeriesTitle>SPLC</bookSeriesTitle>. ACM: Savaldor, Brazil, 2012; pp.136-145.

[57]

Bennett K, Rajlich V. Software maintenance and evolution: a roadmap. In Proceedings of the Conference on the Future of Software Engineering, <bookSeriesTitle>ICSE</bookSeriesTitle>. ACM: New York, NY, USA, 2000; pp.73-87.

[58]

Figueiredo E, Garcia A, Maia M, Ferreira G, Nunes C, Whittle J. On the impact of crosscutting concern projection on code measurement. In Proceedings of the International Conference on Aspect-Oriented Software Development, <bookSeriesTitle>AOSD</bookSeriesTitle>. ACM: NY, USA, 2011; pp.81-92.

[59]

Wohlin C, Runeson P, Hösta M, Ohlsson M, Regnell B, Wesslén A. Experimentation in Software Engineering: An Introduction. Kluwer Academic Publishers: Norwell, MA, USA, 2000.

Digital Library

Cited By

Guimarães EGarcia ACai YFrance RGhosh SLeavens G(2015)Architecture-sensitive heuristics for prioritizing critical code anomaliesProceedings of the 14th International Conference on Modularity10.1145/2724525.2724567(68-80)Online publication date: 16-Mar-2015
https://dl.acm.org/doi/10.1145/2724525.2724567

Index Terms

Heuristic expansion of feature mappings in evolving program families
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

Index terms have been assigned to the content through auto-classification.

Recommendations

History-sensitive heuristics for recovery of features in code of evolving program families
SPLC '12: Proceedings of the 16th International Software Product Line Conference - Volume 1

A program family might degenerate due to unplanned changes in its implementation, thus hindering the maintenance of family members. This degeneration is often induced by feature code that is changed individually in each member without considering other ...
A Hyper-Heuristic Using GRASP with Path-Relinking: A Case Study of the Nurse Rostering Problem

The goal of hyper-heuristics is to design and choose heuristics to solve complex problems. The primary motivation behind the hyper-heuristics is to generalize the solving ability of the heuristics. In this paper, the authors propose a Hyper-heuristic ...
A Set-Covering-Based Heuristic Approach for Bin-Packing Problems

Several combinatorial optimization problems can be formulated as large set-covering problems. In this work, we use the set-covering formulation to obtain a general heuristic algorithm for this type of problem, and describe our implementation of the ...

Comments

Information & Contributors

Information

Published In

cover image Software—Practice & Experience

Software—Practice & Experience Volume 44, Issue 11

November 2014

128 pages

ISSN:0038-0644

Issue’s Table of Contents

Publisher

John Wiley & Sons, Inc.

United States

Publication History

Published: 01 November 2014

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 06 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Guimarães EGarcia ACai YFrance RGhosh SLeavens G(2015)Architecture-sensitive heuristics for prioritizing critical code anomaliesProceedings of the 14th International Conference on Modularity10.1145/2724525.2724567(68-80)Online publication date: 16-Mar-2015
https://dl.acm.org/doi/10.1145/2724525.2724567

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents