@Article{Saborido2018,
author="Saborido, Rub{\'e}n
and Morales, Rodrigo
and Khomh, Foutse
and Gu{\'e}h{\'e}neuc, Yann-Ga{\"e}l
and Antoniol, Giuliano",
title="Getting the most from map data structures in Android",
journal="Empirical Software Engineering",
year="2018",
volume={23}, 
number={5}, 
pages={2829-2864}, 
abstract="A map is a data structure that is commonly used to store data as key--value pairs and retrieve data as keys, values, or key--value pairs. Although Java offers different map implementation classes, Android SDK offers other implementations supposed to be more efficient than HashMap: ArrayMap and SparseArray variants (SparseArray, LongSparseArray, SparseIntArray, SparseLongArray, and SparseBooleanArray). Yet, the performance of these implementations in terms of CPU time, memory usage, and energy consumption is lacking in the official Android documentation; although saving CPU, memory, and energy is a major concern of users wanting to increase battery life. Consequently, we study the use of map implementations by Android developers in two ways. First, we perform an observational study of 5713 Android apps in GitHub. Second, we conduct a survey to assess developers' perspective on Java and Android map implementations. Then, we perform an experimental study comparing HashMap, ArrayMap, and SparseArray variants map implementations in terms of CPU time, memory usage, and energy consumption. We conclude with guidelines for choosing among the map implementations: HashMap is preferable over ArrayMap to improve energy efficiency of apps, and SparseArray variants should be used instead of HashMap and ArrayMap when keys are primitive types.",
issn={1573-7616},
doi={"10.1007/s10664-018-9607-8},
url_Paper = {map-data-structures.pdf},
url={https://doi.org/10.1007/s10664-018-9607-8}
}

{"_id":"DRXnfspJgz7aE6QB9","bibbaseid":"saborido-morales-khomh-guhneuc-antoniol-gettingthemostfrommapdatastructuresinandroid-2018","downloads":0,"creationDate":"2018-03-10T03:16:37.633Z","title":"Getting the most from map data structures in Android","author_short":["Saborido, R.","Morales, R.","Khomh, F.","Guéhéneuc, Y.","Antoniol, G."],"year":2018,"bibtype":"article","biburl":"https://moar82.github.io/myPapers/moralesBib.bib","bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Saborido"],"firstnames":["Rubén"],"suffixes":[]},{"propositions":[],"lastnames":["Morales"],"firstnames":["Rodrigo"],"suffixes":[]},{"propositions":[],"lastnames":["Khomh"],"firstnames":["Foutse"],"suffixes":[]},{"propositions":[],"lastnames":["Guéhéneuc"],"firstnames":["Yann-Gaël"],"suffixes":[]},{"propositions":[],"lastnames":["Antoniol"],"firstnames":["Giuliano"],"suffixes":[]}],"title":"Getting the most from map data structures in Android","journal":"Empirical Software Engineering","year":"2018","volume":"23","number":"5","pages":"2829-2864","abstract":"A map is a data structure that is commonly used to store data as key–value pairs and retrieve data as keys, values, or key–value pairs. Although Java offers different map implementation classes, Android SDK offers other implementations supposed to be more efficient than HashMap: ArrayMap and SparseArray variants (SparseArray, LongSparseArray, SparseIntArray, SparseLongArray, and SparseBooleanArray). Yet, the performance of these implementations in terms of CPU time, memory usage, and energy consumption is lacking in the official Android documentation; although saving CPU, memory, and energy is a major concern of users wanting to increase battery life. Consequently, we study the use of map implementations by Android developers in two ways. First, we perform an observational study of 5713 Android apps in GitHub. Second, we conduct a survey to assess developers' perspective on Java and Android map implementations. Then, we perform an experimental study comparing HashMap, ArrayMap, and SparseArray variants map implementations in terms of CPU time, memory usage, and energy consumption. We conclude with guidelines for choosing among the map implementations: HashMap is preferable over ArrayMap to improve energy efficiency of apps, and SparseArray variants should be used instead of HashMap and ArrayMap when keys are primitive types.","issn":"1573-7616","doi":"\"10.1007/s10664-018-9607-8","url_paper":"map-data-structures.pdf","url":"https://doi.org/10.1007/s10664-018-9607-8","bibtex":"@Article{Saborido2018,\r\nauthor=\"Saborido, Rub{\\'e}n\r\nand Morales, Rodrigo\r\nand Khomh, Foutse\r\nand Gu{\\'e}h{\\'e}neuc, Yann-Ga{\\\"e}l\r\nand Antoniol, Giuliano\",\r\ntitle=\"Getting the most from map data structures in Android\",\r\njournal=\"Empirical Software Engineering\",\r\nyear=\"2018\",\r\nvolume={23}, \r\nnumber={5}, \r\npages={2829-2864}, \r\nabstract=\"A map is a data structure that is commonly used to store data as key--value pairs and retrieve data as keys, values, or key--value pairs. Although Java offers different map implementation classes, Android SDK offers other implementations supposed to be more efficient than HashMap: ArrayMap and SparseArray variants (SparseArray, LongSparseArray, SparseIntArray, SparseLongArray, and SparseBooleanArray). Yet, the performance of these implementations in terms of CPU time, memory usage, and energy consumption is lacking in the official Android documentation; although saving CPU, memory, and energy is a major concern of users wanting to increase battery life. Consequently, we study the use of map implementations by Android developers in two ways. First, we perform an observational study of 5713 Android apps in GitHub. Second, we conduct a survey to assess developers' perspective on Java and Android map implementations. Then, we perform an experimental study comparing HashMap, ArrayMap, and SparseArray variants map implementations in terms of CPU time, memory usage, and energy consumption. We conclude with guidelines for choosing among the map implementations: HashMap is preferable over ArrayMap to improve energy efficiency of apps, and SparseArray variants should be used instead of HashMap and ArrayMap when keys are primitive types.\",\r\nissn={1573-7616},\r\ndoi={\"10.1007/s10664-018-9607-8},\r\nurl_Paper = {map-data-structures.pdf},\r\nurl={https://doi.org/10.1007/s10664-018-9607-8}\r\n}\r\n\r\n","author_short":["Saborido, R.","Morales, R.","Khomh, F.","Guéhéneuc, Y.","Antoniol, G."],"key":"Saborido2018","id":"Saborido2018","bibbaseid":"saborido-morales-khomh-guhneuc-antoniol-gettingthemostfrommapdatastructuresinandroid-2018","role":"author","urls":{" paper":"https://moar82.github.io/myPapers/map-data-structures.pdf","Paper":"https://doi.org/10.1007/s10664-018-9607-8"},"metadata":{"authorlinks":{"gu�h�neuc, y":"https://bibbase.org/show?bib=http%3A%2F%2Fwww.yann-gael.gueheneuc.net%2FWork%2FPublications%2FBiblio%2Fcomplete-bibliography.bib&msg=embed","morales, r":"https://www.ptidej.net/members/moralesr"}},"downloads":0},"search_terms":["getting","map","data","structures","android","saborido","morales","khomh","guéhéneuc","antoniol"],"keywords":[],"authorIDs":["AfJhKcg96muyPdu7S","FyQSF5CQAcHMSbkXr"],"dataSources":["SnNYgSkXkvyAsckPN","8vn5MSGYWB4fAx9Z4","p4Z23KnwhEH5amzu8"]}