Skip to content
Switch branches/tags
Go to file

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

An Independent Evaluation Model for Open-source Software



This paper purpose is to describe a tool, an independent model, to evaluate open-source software including it’s project, using pragmatic and independent methods and tests. It is constituted by two main approaches, the objective and subjective. The model described here aims to provide a quantitative overview of the software and it’s project quality, covering diferent areas, from technical to social, to help in decision-making.

1. Approaches, Methods and Tests Overview

Evaluation approaches are conceptually distinct ways of thinking about, designing, and conducting evaluation efforts.[6]

In this paper, it will be considered two main approaches for evaluating software and it’s projects quality: Objective Approach and Subjective Approach. By using a pragmatic method and mathematical expressions, any individual or organization can run this evaluation model.

Considering software as an object, and a set of services that aims to solve problems, it can be evaluated objectively, based on software quality principles[7].

When considering subjective evaluation approaches, it is important to use independent entities and blind checks reviews to eliminate bias and validate evaluation transparency and credibility[5].

The evaluations results are only valid if the tests listed below are run by, at least, two independent entities.

The evaluation can also be repeated over a period of time. The difference in results between repeated tests in time, also reveals if the software is growing or decaying in time.

This model also uses a strong emphasis on Occam's razor by intersecting the results obtained on the several tests. For instance, if the expession S4R > (S2R + S3R) asserts to true, it indicates that there is a strong value given in general by the community users, although, individually and technically it is not given so that much value.

1.1 Objective Approach

Constitutes a set of objective methods / tests for evaluating the software and it’s project. Each of the following methods will be extensively described below. An Objective Method / Test is identified by starting with “O” following by a number.

  • O1: Software Quality Assurance Metrics - a set of software qualities evaluation results
  • O2: Data Usage Contexts - evaluates the functional areas where the software can be used to manipulate the data.
  • O3: Interoperability: evaluates the software capabilities to communicate / integrate with other software
  • O4: Dependencies: evaluates how much dependent the software is
  • O5: Software License - evaluation of the the licensing terms in respect of open-source freedoms/restrictions, incluing source code forkability.

1.2 Subjective Approach

Constitutes a set of methods / tests in which the object under study cannot be mathematically calculated. Each of the following methods will be extensively described below. A Subjective Method / Test is identified by starting with “S” followed by a number.

  • S1: Software Documentation: evaluation of the software user manual, API reference, examples and tutorials, in text, video or other formats.
  • S2: Blind User Experience - a set of independent user experiments evaluation using the software
  • S3: Blind Connoisseur - an independent review by an high qualified person in the technologies used by the software
  • S4: Public Opinion - evaluation of the project members and project’s comunity
  • S5: Accreditation - an evaluation of the project’s credits given by official organizations.

1.3 Tests Results

Each evaluation test has a relative variable result. It can be identified starting with the test identifier followed by the letter R, ie. O1R.

For easy calculation, it is recommended that each variable should be an integer between 0 and 9, and having POINTS as units.

1.4 Weighting

Each evaluation test has a relative and constant weighting. Weightings are identified starting with it’s relative test identifier, followed by letter P, ie. S1P.

A priori, an equal weighting among all evaluation tests should give the most balanced results. The more differences exists amoung weightings, the more unbalanced the results will be.

It is recomended that a weighting value must be a constant and integer. Also the sum of all weightings should be 100. The weighting units are POINTS.

2. Formulas

2.1 Individual Evaluation

The maximum points that can be obtained is identified by MAX and is an integer.
The individual evaluation is identifies by IE followed by the evaluation number, and is a floating point, rounded to 2 decimal places.

IE1 = ([O1 * O1P ... ON * ONP] + [S1 * S1P ... SN * SNP]) / MAX

2.1.1 Example

MAX = 901;
O1 = 5; O2 = 4; O3 = 3; O4 = 2; O5 = 1;  
S1 = 2; S2 = 3; S3 = 4; S4 = 5; S5 = 6;  
O1P = 10; O2P = 10; O3P = 10; O4P = 10; O5P = 10;  
S1P = 10; S2P = 10; S3P = 10; S4P = 10; S5P = 10;  
IE1 = (5x10 + 4x10 + 3x10 + 2x10 + 1x10 + 2x10 + 3x10 + 4x10 + 5x10 + 6x10) / 900 = 391 / 900  POINTS
IE1 = 0.39

2.2. Evaluation Exclusion Criteria

A list of defined exclusion criteria should be published together with weightings.

2.2.1 Example

O1R x O1P < 50

2.3 Confirmation Variation

Because this model uses Subjective tests to evaluate the object of study, it is almost impossible to obtain exactly the same value among all the independant results, thus, it is necessary to introduce a Variation value that creates a range where the diferences of the independent results can be considered. Variation is a constant and a floating point value that is used to confirm the independent evaluation results. It is identified by VAR and must be less, or equal, a quarter of 1: VAR <= 0,25. The less the varition is, the more the independent results confirmation is fiable.
The Confirmation is the difference of the minimum IE and the maximum IE is less than the variation, otherwise.

VAR >= (MAX(IE1 ... IEN) - MIN(IE1 ... IEN))

2.3.1 Example

VAR = 0,25;
0,25 >= (0,50 - 0,43)
0,25 >= 0,07

3. Validation Process

In favor of transparency of the evaluation process, the evaluation is only considered valid if the following items are publish along with the evaluation process:

  • The reference to the evaluation model (this)
  • The evaluation formula
  • The evaluation weightings
  • The list of exclusion criterias
  • The confirmation variation value (VAR)
  • The name of the independent entities that will run the evaluation tests
  • The reports of the individual evaluation [IE1 ... IEN] specifying the results of each test
  • The result of the Confirmation

O1 - Software Quality Assurance Metrics

This method aims to reveal the software quality in general. All tests should be run by an independant entity. The following known metrics should be evaluated.

  • Reliability / Stability - Run tests that can break the application at run-time, that affect users expectations or companies business, as of: introduce changes to the source code; large user input; introduce changes in data storage, etc...
  • Efficiency - The source code and software architecture attributes that ensure high performance once the application is in run-time mode. The measurements of time and space required of the software operations / services.
  • Security - A measure of the likelihood of potential security breaches due to poor coding practices and architecture. This quantifies the risk of encountering critical vulnerabilities that compromises important information.
  • Maintainability - Measures source-code size, forkability, documentation, project managementand other factors that turns hard to make improvements or apply corrections to the source-code.
  • Portability - Measures in which enviroments the software can be executed.
  • Usability - Measures the software interface usage against users of different cultures, education level and handycaped.

O2 - Data Usage Contexts

This method aims to reveal the total of contexts the software can be used.

  • Publishing - Evaluates the number of the operations available to publish the data;
  • Management - Evaluates the number of the operations available to organize and manage the data;
  • Analysis - Evaluates the number of the operations available to analyse and obtain analysis reports of the data;
  • Transformational - Evaluates the number of the operations available that can transform the data;
  • Entertainment - Evaluates the number of the operations available that serves the data as entertaiment.

O3 - Interoperability

This test aims to reveal the total operations that can be used by third-party software. It measures the software capabilities for communicating and integrating with other software. It can also take into account how many changes the software has suffer to communicate / integrate with other software.

O4 - Dependencies

This test aims to reveal the total of the software dependencies to run. For each depency, should be considered a new overall evaluation.

O5 - Software License and Project Governance Model

This test aims to reveal the total of freedoms and restrictions that are inherent to the license policy, as well taking into account, objectively, the pros and cons of the project's governance model.

S1 - Software Documentation

This method aims to reveal the quality and quantity of the software documentation for software users.

S2 - Blind User Experience

This method aims to reveal usability problems, but also, reveals independent acceptance of the software usage, which is very important to reduce human bias and reputation influencies. Must be used with S1. Evaluates individual user experience with the software. The user must know nothing about the software creators, distribution trademarks or any signs that invalidates the blind experience. Best results are obtained with larger user sample.

S3 - Blind Connoisseur Peer Review

This method aims to reveal hidden potential of the software, that is not known by normal users. Submit the software to peer review to a specialized user with high knowledge of the technologies used by the software. Also as in S2, these specialized user must know nothing about the software creator, distributor, trademarks or any sigh that invalidates the blind experience. Aquired the resulting review.

S4 - Public Opinion

This method aims to reveal how much evolved the project is on the social area. Use independent entities to measure project comunity and it’s activity. Evaluate the total number of project members and comunity members.

S5 - Accreditation

This method aims to reveal how much credits the project has received from official organizations. Evaluate the total number of official organizations.

5. Keywords

Project - a collaborative enterprise, involving research or design, that is carefully planned to achieve a particular aim[1], including the social and marketing related areas.

Software - is that part of a computer system that consists of encoded information or computer instructions[2], aimed to resolve a set of problems described in it’s Project.

Open Source Software - computer software with its source code made available with a license in which the copyright holder provides the rights to study, change, and distribute the software to anyone and for any purpose[3].

Evaluation Model - is the process of judging something or someone based on a set of standards[4]. It is also a set of evaluation methods and technics to measure the object in study.

6. References

TODO - Work on references

[1] Wikipedia (2016) -
[2] Wikipedia (2016)-
[3] St. Laurent, Andrew M. (2008). Understanding Open Source and Free Software Licensing. O'Reilly Media. p. 4. ISBN 9780596553951.
[4] Wikipedia (2016) -
[6] Wikipedia (2016) -
[7] Wikipedia (2016) -


An Independent Evaluation Model for Open-source Software



No releases published


No packages published