Maintenance Web Based Applications Using Feature Location


Achmad Arwan, Denny Sagita Rusdianto


Maintenance web applications are a complex set of efforts. The FilkomApps are the web application used by the Faculty of Computer Science of Universitas Brawijaya to arrange the academic, theses of students, assignment of faculty, inventory, presence, honorarium. It has about 6K number of files(HTML, PHP, JS, CSS). The feature location was able to help the maintenance of the web applications by locating specific features on the files. The process comprises of preprocessing (tokenizing, web language syntax removal, splitting, stopword and stemming), indexing (VSM Lucene), and evaluations (precision and recall). The experiments were done by querying the keywords originate from previous maintenance modification effort and feature of a system. The results of precision were 86% and recall were 47%. The precision was better 374% than the conventional method (using the IDE search feature)

Full Text:



Pérez F, Lapeña R, Font J, Cetina C (2018) Fragment retrieval on models for model maintenance : Applying a multi- objective perspective to an industrial case study. Inf Softw Technol 103:188–201 . doi: 10.1016/j.infsof.2018.06.017

Moslehi P, Adams B (2018) Feature Location using Crowd-based Screencasts Feature Location using Crowd-based Screencasts

Damevski K, Shepherd D, Pollock L (2016) A field study of how developers locate features in source code. 724–747 . doi: 10.1007/s10664-015-9373-9

Martinez J (2018) Feature location benchmark for extractive software product line adoption research using realistic and synthetic Eclipse variants. 104:46–59 . doi: 10.1016/j.infsof.2018.07.005

Kraft NA, Gray J (2018) Impact of structural weighting on a latent Dirichlet allocation – based feature location technique. 1–25 . doi: 10.1002/smr.1892

Biggers LR, Bocovich C, Capshaw R, Eddy BP, Etzkorn LH, Kraft NA (2014) Configuring latent Dirichlet allocation based feature location

Razzaq A, Le A, Chris G, Jim E (2019) An empirical assessment of baseline feature location techniques (2020) Usage statistics of server-side programming languages for websites. (2020)

Arwan A, Rochimah S, Akbar RJ (2015) Source Code Retrieval on StackOverflow Using LDA. 2015 3rd Int Conf Inf Commun Technol 295–299 . doi: 10.1109/ICoICT.2015.7231439

Zhang W, Yoshida T, Tang X (2011) A comparative study of TF*IDF, LSI and multi-words for text classification. Expert Syst Appl 38:2758–2765 . doi: 10.1016/j.eswa.2010.08.066

Tobergte DR, Curtis S (2013) Apache Solr Search Patterns

Manning, Christopher D., Prabhakar Raghavan and HS (2008) Introduction to information retrieval. Vol. 1. No. 1