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This file is part of Logtalk https://logtalk.org/ SPDX-FileCopyrightText: 2016 Barry Evans <barryevans@kyndi.com> SPDX-FileCopyrightText: 2016 Paulo Moura <pmoura@logtalk.org> SPDX-License-Identifier: Apache-2.0
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
dead_code_scannerThis tool detects likely dead code in Logtalk entities and in Prolog modules compiled as objects. Predicates (and non-terminals) are classified as dead code when:
Given the possibility of false positives, care must be taken before deleting reported dead code to ensure that it's, in fact, code that is not used. A common cause of false positives is the use of conditional compilation directives to provide implementations for predicates missing in some systems or different predicate implementations per operating-system.
The dead_code_scanner.lgt source file implements the scanning predicates for
finding dead code in entities, libraries, and directories. The source file
dead_code_scanner_messages.lgt defines the default translations for the
messages printed when scanning for dead code. These messages can be intercepted
to customize the output, e.g., to make it less verbose or for integration with,
e.g., GUI IDEs and continuous integration servers.
This tool API documentation is available at:
[../../apis/library_index.html#dead-code-scanner](../../apis/library_index.html#dead-code-scanner)
For sample queries, please see the SCRIPT.txt file in the tool directory.
This tool can be loaded using the query:
| ?- logtalk_load(dead_code_scanner(loader)).
To test this tool, load the tester.lgt file:
| ?- logtalk_load(dead_code_scanner(tester)).
This tool provides a set of predicates that allows scanning entities,
libraries, files, and directories. See the tool API documentation for
details. The source code to be analyzed should be loaded with the
source_data and optimize flags turned on (possibly set from a
loader file).
For machine-readable integrations, the diagnostics/2-3, diagnostic/2-3,
diagnostics_summary/2-3, and diagnostics_preflight/2-3 predicates can be
used to collect dead-code results and post-filter counts without relying on
printed messages. Diagnostics are returned as terms of the form:
diagnostic(RuleId, Severity, Confidence, Message, Context, File, Lines, Properties)
where:error, warning, or note)high, medium, or low)export/3-4 predicates serialize
scan results in SARIF format using the json library.
As an example, assume that we want to scan an application with a library
alias my_app. The following goals could be used:
| ?- set_logtalk_flag(source_data, on),
set_logtalk_flag(optimize, on).
yes
| ?- logtalk_load(my_app(loader)).
...
yes
| ?- dead_code_scanner::library(my_app).
...
For complex applications that make use of sub-libraries, there are also
rlibrary/1-2 predicates that perform a recursive scan of a library and
all its sub-libraries. Conversely, we may be interested in scanning a single
entity:
| ?- dead_code_scanner::entity(some_object).
...
For other usage examples, see the SCRIPT.txt file in the tool directory.
A set of options is available to specify code that should be excluded when looking for unused predicates (and non-terminals):
[]); all sub-directories of the excluded directories are also excluded; directories may be listed by full or relative path[]); files may be listed by full path or basename, with or without extension[startup, scratch_directory])[])[]); supports local indicators such as foo/1 and bar//2 plus qualified indicators such as `object::baz/2 and qux/3`[]); intended for reusable CI baselines and supports partially instantiated structured finding terms such as dead_predicate(local_dead_code, medium, _, object, some_object, helper/2, _, _)
The diagnostics_summary/2-3 predicates return a term of the form:
rule_count(RuleId, Count) terms,
SeverityCounts containing severity_count(Severity, Count) terms, and
ConfidenceCounts containing confidence_count(Confidence, Count) terms.
ContextSummaries is a list of terms of the form:
The diagnostics_preflight/2-3 predicates return an ordered set of warnings
describing analysis prerequisites that affect result quality for a target.
Warning terms currently use the form:
The current finding classes are:
local_dead_codeunused_uses_resourceunused_use_module_resource
Confidence is a triage-oriented rating attached to every finding. The JSON
schema allows the values high, medium, and low, but the tool currently
emits only high and medium:high
Used when the tool has stronger evidence that the reported code is really unused.
medium
Used when the result is still useful, but can be affected by missing compilation information such as optimized call graph data.
low
Reserved for future use. It is accepted by the export schema but is not currently generated by the scanner.
For local_dead_code, the confidence depends on the effective compilation mode
of the analyzed file:
optimize(on), the confidence is medium.optimize(on), the confidence is upgraded to
high because the compiler can provide more complete call graph information,
reducing the risk of false positives caused by missed meta-calls.
The effective mode is inferred from the loaded file itself, not from the current scanner defaults. Therefore, results reflect how the analyzed code was actually compiled.
Unused uses/2 and use_module/2 resources are always reported with high
confidence because they are derived from the generated linking clauses and the
recorded call graph rather than from heuristic reachability alone.
When scanning using the text-based predicates such as entity/1-2, file/1-2,
and all/0-1, the tool now emits preflight warnings whenever the analyzed files
were not loaded with source_data(on) or optimize(on) so that potentially
less reliable results can be triaged more carefully.
This tool is a diagnostics producer. To generate SARIF reports from its
diagnostics, load the standalone sarif tool and call
`sarif::generate(dead_code_scanner, Target, Sink, Options) where Target
and Options` are the same ones accepted by the diagnostics predicates.
The generated report uses the SARIF 2.1.0 JSON format and is suitable for
code scanning integrations that consume SARIF reports. The shared generator
includes deterministic result fingerprints derived from the canonical finding
and preserves the rule descriptors and triage-oriented severity mapping
described below.
SARIF findings are exported using one rule descriptor per finding class:
local_dead_codeunused_uses_resourceunused_use_module_resource
Result severities are also triage-aware instead of using a single static SARIF
level for all findings:local_dead_code with high confidence is exported as warninglocal_dead_code with medium or low confidence is exported as noteunused_uses_resource with high confidence is exported as errorunused_use_module_resource with high confidence is exported as error
This mapping allows CI consumers to distinguish advisory dead-code findings
from stronger unused-resource findings without reinterpreting the custom
class and confidence properties.
SARIF reports include the same preflight information as invocation-level
toolExecutionNotifications, allowing consumers to distinguish prerequisite
warnings from dead code findings.
When the analyzed code is inside a git repository, the shared generator also
includes the current branch and commit hash as optional run properties and a
versionControlProvenance entry when the repository URI can be derived.
make tool
The loader.lgt file sets a make target action that will call the
`dead_code_scanner::all` goal whenever the logtalk_make(check) goal
(or its top-level abbreviation, {?}) is called.
Use of local meta-calls with goal arguments only known at runtime can result
in false positives. When using library or user-defined meta-predicates,
compilation of the source files with the optimize flag turned on may allow
meta-calls to be resolved at compile-time and thus allow calling information
for the meta-arguments to be recorded, avoiding false positives for predicates
that are only meta-called.
This tool 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.
This tool 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), optimize(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), optimize(on)]).
With either wrapping solution, pay special attention to any compilation warnings that may signal issues that could prevent the plain Prolog from being fully analyzed when wrapped by an object.
Some tests fail when using the ECLIPSe and Trealla Prolog backends due to their implementation of the multifile/1 directive, specifically when the multifile predicates are also dynamic with clauses defined in a source file: reconsulting the file adds the new clauses to the old ones instead of replacing them.