# `code_metrics`

The purpose of this tool is to assess qualities of source code that may predict negative aspects such as entity coupling, cohesion, complexity, error-proneness, and overall maintainability. It is meant to be extensible via the addition of objects implementing new metrics.

This tool provides predicates for computing metrics for source files, entities, libraries, files, and directories. The actual availability of a particular predicate depends on the specific metric. One set of predicates prints, by default, the computed metric values to the standard output. A second set of predicates computes and returns a score (usually a compound term with the computed metric values as arguments).

## API documentation

This tool API documentation is available at:

../../docs/library_index.html#code-metrics

## Loading

This tool can be loaded using the query:

    | ?- logtalk_load(code_metrics(loader)).

## Testing

To test this tool, load the `tester.lgt` file:

    | ?- logtalk_load(code_metrics(tester)).

## Available metrics

Currently, the following metrics are provided:

- Number of Clauses (`noc_metric`)

- Number of Rules (`nor_metric`)

- Unique Predicate Nodes (`upn_metric`)

- Cyclomatic Complexity (`cc_metric`)

- Depth of Inheritance (`dit_metric`)

- Efferent coupling, afferent coupling, instability, and abstractness (`coupling_metric`)

- Documentation (`doc_metric`)

- Source code size (`size_metric`)

- Halstead complexity (`halstead_metric` and `halstead_metric(Stroud)`)

A helper object, `code_metrics`, is also provided allowing running all loaded individual metrics. For code coverage metrics, see the `lgtunit` tool documentation.

For interpretation of the coupling metric scores, see e.g. the original paper by Robert Martin, “OO Design Quality Metrics”:

    @inproceedings{citeulike:1579528,
        author = "Martin, Robert",
        booktitle = "Workshop Pragmatic and Theoretical Directions in Object-Oriented Software Metrics",
        citeulike-article-id = 1579528,
        citeulike-linkout-0 = "http://www.objectmentor.com/resources/articles/oodmetrc.pdf",
        keywords = "diplomarbeit",
        organization = "OOPSLA'94",
        posted-at = "2007-08-21 11:08:44",
        priority = 0,
        title = "OO Design Quality Metrics - An Analysis of Dependencies",
        url = "http://www.objectmentor.com/resources/articles/oodmetrc.pdf",
        year = 1994
    }

The Halstead metric computation uses the reflection API for performance. The main consequence of this choice is that we abstract all predicate arguments. A computation closer to the original definition of the metric would require switching to use the parser to collect information on syntactic literals, which would imply a much large computation cost.

The coupling metric was also influenced by the metrics rating system in Microsoft Visual Studio and aims to eventually emulate the functionality of a maintainability index score.

The unique predicate nodes (UPN) metric is described in the following paper:

    @article{MOORES199845,
        title = "Applying Complexity Measures to Rule-Based Prolog Programs",
        journal = "Journal of Systems and Software",
        volume = "44",
        number = "1",
        pages = "45 - 52",
        year = "1998",
        issn = "0164-1212",
        doi = "https://doi.org/10.1016/S0164-1212(98)10042-0",
        url = "http://www.sciencedirect.com/science/article/pii/S0164121298100420",
        author = "Trevor T Moores"
    }

The cyclomatic complexity metric uses the same predicate abstraction as the UPN metric and it is also described in the above paper besides the original paper by Thomas J. McCabe:

    @inproceedings{McCabe:1976:CM:800253.807712,
        author = "McCabe, Thomas J.",
        title = "A Complexity Measure",
        booktitle = "Proceedings of the 2Nd International Conference on Software Engineering",
        series = "ICSE '76",
        year = 1976,
        location = "San Francisco, California, USA",
        pages = "407--",
        url = "http://dl.acm.org/citation.cfm?id=800253.807712",
        acmid = 807712,
        publisher = "IEEE Computer Society Press",
        address = "Los Alamitos, CA, USA",
        keywords = "Basis, Complexity measure, Control flow, Decomposition, Graph theory, Independence, Linear, Modularization, Programming, Reduction, Software, Testing",
    }

Be sure to fully understand the metrics individual meanings and any implementation limitations before using them to support any evaluation or decision process.

## Usage

All metrics require the source code to be analyzed to be loaded with the `source_data` flag turned on. For usage examples, see the `SCRIPT.txt` file in the tool directory.

## Defining new metrics

New metrics can be implemented by defining an object that imports the `code_metric` category and implements its score predicates. There is also a `code_metrics_utilities` category that defines useful predicates for the definition of metrics.

## Third-party tools

`cloc` is an open-source command-line program that counts blank lines, comment lines, and lines of source code in many programming languages including Logtalk. Available at https://github.com/AlDanial/cloc

`ohcount` is an open-source command-line program that counts blank lines, comment lines, and lines of source code in many programming languages including Logtalk. Available at https://github.com/blackducksoftware/ohcount

`tokei` is an open-source command-line program that counts blank lines, comment lines, and lines of source code in many programming languages including Logtalk. Available at https://github.com/XAMPPRocky/tokei

## Applying metrics to Prolog modules

Some of the metrics can also be applied to Prolog modules that Logtalk is able to compile as objects. For example, if the Prolog module file is named `module.pl`, try:

    | ?- logtalk_load(module, [source_data(on)]).

Due to the lack of standardization of module systems and the abundance of proprietary extensions, this solution is not expected to work for all cases.

## Applying metrics to plain Prolog code

Some of the metrics can also be applied to plain Prolog code. For example, if the Prolog file is named `code.pl`, simply define an object including its code:

    :- object(code).
        :- include('code.pl').
    :- end_object.

Save the object to an e.g. `code.lgt` file in the same directory as the Prolog file and then load it in debug mode:

    | ?- logtalk_load(code, [source_data(on)]).

In alternative, use the `object_wrapper_hook` provided by the `hook_objects` library:

    | ?- logtalk_load(hook_objects(loader)).
    ...

    | ?- logtalk_load(code, [hook(object_wrapper_hook), source_data(on)]).

With either wrapping solution, pay special attention to any compilation warnings that may signal issues that could prevent the plain Prolog code of working when wrapped by an object.