Abstract
Traceability links recovery (TLR) has been a topic of interest for many years. However, TLR approaches are based on the latent semantics of the software artifacts, and are not equipped to deal with software artifacts that lack those inherent semantics, such as BPMN models. The aim of this work is to enhance TLR approaches in BPMN models by incorporating the linguistic particularities of BPMN models into the TLR process. Our approach runs through a threefold contribution: (1) we identify the particularities of BPMN models; (2) we describe how to leverage the particularities; and (3) we build three variants of the best exploratory TLR approach which specifically cater to BPMN models. The approach is evaluated through both an academic case study and a real-world industrial case study. The results show that incorporating the particularities of BPMN into the TLR process leads the specific approach to improve the traceability results obtained by generalist approaches, maintaining precision levels and improving recall. The novel findings of this paper suggest that there is a benefit in researching and taking in account the particularities of the different kinds of models in order to optimize the results of TLR between requirements and models, instead of relying on generalist approaches.
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References
Brambilla M, Cabot J, Wimmer M (2012) Model-driven software engineering in practice. Synth Lectur Softw Eng 1(1):1–182
Macaulay LA (2012) Requirements engineering. Springer, New York
Winkler S, Pilgrim J (2010) A survey of traceability in requirements engineering and model-driven development. Softw Syst Model (SoSyM) 9(4):529–565
Loniewski G, Insfran E, Abrahão S (2010) A systematic review of the use of requirements engineering techniques in model-driven development. In: International conference on model driven engineering languages and systems. Springer, pp 213–227
Font J, Arcega L, Haugen Ø, Cetina C (2016) Feature Location in Models Through a Genetic Algorithm Driven by Information Retrieval Techniques. In: Proceedings of the ACM/IEEE 19th international conference on model driven engineering languages and systems. ACM, MODELS ’16
Martinez J, Ziadi T, Bissyande TF, Klein J, Le Traon Y (2015) Automating the extraction of model-based software product lines from model variants (t). In: 2015 30th IEEE/ACM international conference on automated software engineering (ASE). IEEE, pp 396–406
Martinez J, Ziadi T, Papadakis M, Bissyandé TF, Klein J, Le Traon Y (2018) Feature location benchmark for extractive software product line adoption research using realistic and synthetic eclipse variants. Inf Softw Technol 104:46–59
Krüger J, Mukelabai M, Gu W, Shen H, Hebig R, Berger T (2019) Where is my feature and what is it about? a case study on recovering feature facets. J Syst Softw 152:239–253
Chinosi M, Trombetta A (2012) BPMN: an introduction to the standard. Comput Stand Interfaces 34(1):124–134
Oliveto R, Gethers M, Poshyvanyk D, De Lucia A (2010) On the Equivalence of Information Retrieval Methods for Automated Traceability Link Recovery. In: 2010 IEEE 18th international conference on program comprehension. IEEE, pp 68–71
Watkins R, Neal M (1994) Why and how of requirements tracing. IEEE Softw 11(4):104–106
Ghazarian A (2010) A research agenda for software reliability. IEEE Reliability Society 2009 Annual Technology Report
Rempel P, Mäder P (2017) Preventing defects: the impact of requirements traceability completeness on software quality. IEEE Trans Softw Eng 43(8):777–797
Zhang Y, Witte R, Rilling J, Haarslev V (2008) Ontological approach for the semantic recovery of traceability links between software artefacts. IET Softw 2(3):185–203
Zowghi D, Jin Z (2011) Requirements engineering. Springer, New York
Gotel OC, Finkelstein C (1994) An analysis of the requirements traceability problem. In: Proceedings of the first international conference on requirements engineering. IEEE, pp 94–101
Spanoudakis G, Zisman A (2005) Software traceability: a roadmap. Handb Softw Eng Knowl Eng 3:395–428
Schlutter A, Vogelsang A (2020) Trace link recovery using semantic relation graphs and spreading activation. In: 2020 IEEE 28th international requirements engineering conference (RE). IEEE, pp 20–31
Madala K, Piparia S, Blanco E, Do H, Bryce R (2021) Model elements identification using neural networks: a comprehensive study. Requir Eng 26:67–96
Parizi RM, Lee SP, Dabbagh M (2014) Achievements and challenges in state-of-the-art software traceability between test and code artifacts. IEEE Trans Reliab 63(4):913–926
Rubin J, Chechik M (2013) A survey of feature location techniques. In: Domain engineering. Springer, pp 29–58
Lapeña R, Font J, Cetina C, Pastor Ó (2018) Exploring new directions in traceability link recovery in models: the process models case. In: International conference on advanced information systems engineering. Springer, pp 359–373
Lapeña R, Pérez F, Cetina C, Pastor Ó (2019) Improving traceability links recovery in process models through an ontological expansion of requirements. In: International conference on advanced information systems engineering. Springer, pp 261–275
Pérez F, Font J, Arcega L, Cetina C (2019) Collaborative feature location in models through automatic query expansion. Autom Softw Eng 26(1):161–202
Eaddy M, Aho AV, Antoniol G, Guéhéneuc YG (2008) Cerberus: tracing requirements to source code using information retrieval, dynamic analysis, and program analysis. In: ICPC 2008 conference. IEEE
Eaddy M, Aho A, Murphy GC (2007) Identifying, assigning, and quantifying crosscutting concerns. In: Proceedings of the first international workshop on assessment of contemporary modularization techniques, p 2
Marcus A, Maletic JI (2003) Recovering documentation-to-source-code traceability links using latent semantic indexing. In: Proceedings of the 25th international conference on software engineering. IEEE
Antoniol G, Canfora G, Casazza G, De Lucia A, Merlo E (2002) Recovering traceability links between code and documentation. IEEE Trans Softw Eng 28(10):970–983
Zisman A, Spanoudakis G, Pérez-Miñana E, Krause P (2003) Tracing software requirements artifacts. In: Software engineering research and practice, pp 448–455
De Lucia A, Fasano F, Oliveto R, Tortora G (2004) Enhancing an artefact management system with traceability recovery features. In: Proceedings of the 20th IEEE international conference on software maintenance. IEEE, pp 306–315
Eder S, Femmer H, Hauptmann B, Junker M (2015) Configuring latent semantic indexing for requirements tracing. In: Proceedings of the 2nd international workshop on requirements engineering and testing
Marcén AC, Lapeña R, Pastor Ó, Cetina C (2020) Traceability link recovery between requirements and models using an evolutionary algorithm guided by a learning to rank algorithm: Train control and management case. J Syst Softw 163:110519
Sultanov H, Hayes JH (2010) Application of swarm techniques to requirements engineering: requirements tracing. In: 18th IEEE international requirements engineering conference
Duan C, Cleland-Huang J (2007) Clustering support for automated tracing. In: Proceedings of the 22nd IEEE/ACM international conference on automated software engineering
Falessi D, Cantone G, Canfora G (2013) Empirical principles and an industrial case study in retrieving equivalent requirements via natural language processing techniques. IEEE Trans Softw Eng 39(1):18–44
Arora C, Sabetzadeh M, Goknil A, Briand LC, Zimmer F (2015) Change impact analysis for natural language requirements: an NLP approach. In: IEEE 23rd international requirements engineering conference
Pudlitz F, Brokhausen F, Vogelsang A (2019) Extraction of system states from natural language requirements. In: 2019 IEEE 27th international requirements engineering conference (RE). IEEE, pp 211–222
Deshpande G, Motger Q, Palomares C, Kamra I, Biesialska K, Franch X, Ruhe G, Ho J (2020) Requirements dependency extraction by integrating active learning with ontology-based retrieval. In: 2020 IEEE 28th international requirements engineering conference (RE). IEEE, pp 78–89
Seqerloo AY, Amiri MJ, Parsa S, Koupaee M (2019) Automatic test cases generation from business process models. Requir Eng 24(1):119–132
Moitra A, Siu K, Crapo AW, Durling M, Li M, Manolios P, Meiners M, McMillan C (2019) Automating requirements analysis and test case generation. Requir Eng 24(3):341–364
Reinhartz-Berger I, Kemelman M (2020) Extracting core requirements for software product lines. Requir Eng 25(1):47–65
Qian C, Wen L, Kumar A, Lin L, Lin L, Zong Z, Wang J, et al. (2020) An approach for process model extraction by multi-grained text classification. In: International conference on advanced information systems engineering. Springer, pp 268–282
Rebmann A, van der Aa H (2021) Extracting semantic process information from the natural language in event logs. In: International conference on advanced information systems engineering. Springer, pp 57–74
Sànchez-Ferreres J, van der Aa H, Carmona J, Padró L (2018) Aligning textual and model-based process descriptions. Data Knowl Eng 118:25–40
Mendling J, Leopold H, Thom LH, van der Aa H (2019) Natural language processing with process models (NLP4RE report paper). In: REFSQ workshops, CEUR-WS.org, CEUR Workshop Proceedings, vol 2376
Klinkmüller C, Weber I, Mendling J, Leopold H, Ludwig A (2013) Increasing recall of process model matching by improved activity label matching. In: Business process management. Springer, pp 211–218
Leopold H, Mendling J, Polyvyanyy A (2014) Supporting process model validation through natural language generation. IEEE Trans Softw Eng 40(8):818–840
Spanoudakis G, Zisman A, Pérez-Minana E, Krause P (2004) Rule-based generation of requirements traceability relations. J Syst Softw 72(2):105–127
Leech G, Garside R, Bryant M (1994) CLAWS4: the tagging of the british national corpus. In: Proceedings of the 15th conference on computational linguistics, vol 1. Association for Computational Linguistics
Hulth A (2003) Improved automatic keyword extraction given more linguistic knowledge. In: Proceedings of the 2003 conference on empirical methods in natural language processing. Association for Computational Linguistics, pp 216–223
Plisson J, Lavrac N, Mladenic D, et al. (2004) A rule based approach to word lemmatization. In: Proceedings of the 7th international multi-conference information society, Citeseer, vol 1, pp 83–86
Landauer TK, Foltz PW, Laham D (1998) An introduction to latent semantic analysis. Discourse Process 25(2–3):259–284
Marcus A, Sergeyev A, Rajlich V, Maletic J (2004) An information retrieval approach to concept location in source code. In: Proceedings of the 11th working conference on reverse engineering, pp 214–223. https://doi.org/10.1109/WCRE.2004.10
Salman HE, Seriai A, Dony C (2014) Feature location in a collection of product variants: combining information retrieval and hierarchical clustering. In: The 26th international conference on software engineering and knowledge engineering, pp 426–430
Wohlin C, Runeson P, Höst M, Ohlsson MC, Regnell B, Wesslén A (2012) Experimentation in software engineering. Springer, New York
Salton G, McGill MJ (1986) Introduction to modern information retrieval. McGraw-Hill Inc, New York
Arcuri A, Briand L (2014) A Hitchhiker’s guide to statistical tests for assessing randomized algorithms in software engineering. Softw Test Verif Reliab 24(3):219–250
García S, Fernández A, Luengo J, Herrera F (2010) Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power. Inf Sci 180(10):2044–2064
Conover WJ (1998) Practical nonparametric statistics, vol 350. Wiley, New York
Vargha A, Delaney HD (2000) A Critique and Improvement of the CL common language effect size statistics of McGraw and Wong. J Educ Behav Stat
Krueger RA, Casey MA (2014) Focus groups: a practical guide for applied research. Sage Publications, Thousand Oaks
van der Aa H, Di Ciccio C, Leopold H, Reijers HA (2019) Extracting declarative process models from natural language. In: International conference on advanced information systems engineering. Springer, pp 365–382
Friedrich F, Mendling J, Puhlmann F (2011) Process model generation from natural language text. In: International conference on advanced information systems engineering. Springer, pp 482–496
Font J, Arcega L, Haugen Ø, Cetina C (2016) Feature location in model-based software product lines through a genetic algorithm. In: Proceedings of the 15th international conference on software reuse: bridging with social-awareness, ICSR 2016, Limassol, Cyprus
Affenzeller M, Winkler SM, Wagner S, Beham A (2009) Genetic algorithms and genetic programmin—modern concepts and practical applications. CRC Press, London
Acknowledgements
This work has been partially supported by the Ministry of Economy and Competitiveness (MINECO) through the Spanish National R+D+i Plan and ERDF funds under the project ALPS (RTI2018-096411-B-I00).
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Lapeña, R., Pérez, F., Cetina, C. et al. Leveraging BPMN particularities to improve traceability links recovery among requirements and BPMN models. Requirements Eng 27, 135–160 (2022). https://doi.org/10.1007/s00766-021-00365-1
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DOI: https://doi.org/10.1007/s00766-021-00365-1