short-paper

TDTool: threshold derivation tool

Authors:

Eduardo Fernandes,

Eduardo FigueiredoAuthors Info & Claims

EASE '16: Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering

Article No.: 24, Pages 1 - 5

https://doi.org/10.1145/2915970.2916014

Published: 01 June 2016 Publication History

Abstract

Software metrics provide basic means to quantify quality of software systems. However, the effectiveness of the measurement process is directly dependent on the definition of reliable thresholds. If thresholds are not properly defined, it is difficult to know, for instance, whether a given metric value indicates a potential problem in a class implementation. There are several methods proposed in literature to derive thresholds for software metrics. However, most of these methods (i) do not respect the skewed distribution of software metrics and (ii) do not provide a supporting tool. Aiming to fill the second gap, we propose a tool, called TDTool, to derive metric thresholds. TDTool is open source and supports four different methods for threshold derivation. This paper presents TDTool architecture and illustrates how to use it. It also presents the thresholds derived using each method based on a benchmark of 33 software product lines.

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Cited By

Filó TBigonha MFerreira K(2024)Evaluating Thresholds for Object-Oriented Software MetricsJournal of the Brazilian Computer Society10.5753/jbcs.2024.337330:1(313-346)Online publication date: 25-Sep-2024
https://doi.org/10.5753/jbcs.2024.3373
Alqmase MAlshayeb MGhouti L(2022)Quality assessment framework to rank software projectsAutomated Software Engineering10.1007/s10515-022-00342-029:2Online publication date: 18-May-2022
https://doi.org/10.1007/s10515-022-00342-0
Mishra AShatnawi RCatal CAkbulut A(2021)Techniques for Calculating Software Product Metrics Threshold Values: A Systematic Mapping StudyApplied Sciences10.3390/app11231137711:23(11377)Online publication date: 1-Dec-2021
https://doi.org/10.3390/app112311377
Show More Cited By

Index Terms

TDTool: threshold derivation tool
1. Software and its engineering

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cover image ACM Other conferences

EASE '16: Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering

June 2016

310 pages

ISBN:9781450336918

DOI:10.1145/2915970

Conference Chair:
Sarah Beecham,
Program Chairs:
Barbara Kitchenham,
Stephen G. MacDonell

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 June 2016

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EASE '16

EASE '16: 20th International Conference on Evaluation and Assessment in Software Engineering

June 1 - 3, 2016

Limerick, Ireland

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Overall Acceptance Rate 71 of 232 submissions, 31%

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Cited By

Filó TBigonha MFerreira K(2024)Evaluating Thresholds for Object-Oriented Software MetricsJournal of the Brazilian Computer Society10.5753/jbcs.2024.337330:1(313-346)Online publication date: 25-Sep-2024
https://doi.org/10.5753/jbcs.2024.3373
Alqmase MAlshayeb MGhouti L(2022)Quality assessment framework to rank software projectsAutomated Software Engineering10.1007/s10515-022-00342-029:2Online publication date: 18-May-2022
https://doi.org/10.1007/s10515-022-00342-0
Mishra AShatnawi RCatal CAkbulut A(2021)Techniques for Calculating Software Product Metrics Threshold Values: A Systematic Mapping StudyApplied Sciences10.3390/app11231137711:23(11377)Online publication date: 1-Dec-2021
https://doi.org/10.3390/app112311377
Amanatidis TMittas NMoschou AChatzigeorgiou AAmpatzoglou AAngelis L(2020)Evaluating the agreement among technical debt measurement tools: building an empirical benchmark of technical debt liabilitiesEmpirical Software Engineering10.1007/s10664-020-09869-wOnline publication date: 26-Aug-2020
https://doi.org/10.1007/s10664-020-09869-w
Mori AVale GCirilo EFigueiredo E(2019)A Domain-Sensitive Threshold Derivation MethodProceedings of the XV Brazilian Symposium on Information Systems10.1145/3330204.3330252(1-8)Online publication date: 20-May-2019
https://dl.acm.org/doi/10.1145/3330204.3330252
Alqmase MAlshayeb MGhouti L(2019)Threshold Extraction Framework for Software MetricsJournal of Computer Science and Technology10.1007/s11390-019-1960-634:5(1063-1078)Online publication date: 6-Sep-2019
https://doi.org/10.1007/s11390-019-1960-6
Vale GFernandes EFigueiredo E(2019)On the proposal and evaluation of a benchmark-based threshold derivation methodSoftware Quality Journal10.1007/s11219-018-9405-y27:1(275-306)Online publication date: 15-May-2019
https://dl.acm.org/doi/10.1007/s11219-018-9405-y
Mori AVale GViggiato MOliveira JFigueiredo ECirilo EJamshidi PKastner CNord RBuschmann FKruchten P(2018)Evaluating domain-specific metric thresholdsProceedings of the 2018 International Conference on Technical Debt10.1145/3194164.3194173(41-50)Online publication date: 27-May-2018
https://dl.acm.org/doi/10.1145/3194164.3194173
Lavazza LMorasca S(2016)An Empirical Evaluation of Distribution-based Thresholds for Internal Software MeasuresProceedings of the The 12th International Conference on Predictive Models and Data Analytics in Software Engineering10.1145/2972958.2972965(1-10)Online publication date: 9-Sep-2016
https://dl.acm.org/doi/10.1145/2972958.2972965

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