University:
California State University, Northridge
Course:
COMP 587 | Software Verification and Validation
Academic year:

2024
Views:

124

Pages:

22
Author:

Aditya Porter

Introduction Automated testing tools assist software engineers to gauge the quality of software by automating the mechanical aspects of software-testing. Automated testing tools vary in their: • Underlying approach • Quality • Ease-of-use How does a project manager choose the best suitable testing tool? Software Quality Metrics • The history of software metrics began with counting the number of lines of code (LOC). • It was assumed that more lines of code implied more complex programs, which in turn were more likely to have errors. • However, software metrics have evolved well beyond the simple measures introduced in the 1960s. Procedural (Traditional) Software Metrics • Since the first introduction of LOC, metrics for traditional or procedural source code have increased in number and complexity. • Cyclomatic complexity • e is the number of edges, n is the number of nodes and p is number of unconnected parts of G. • Offers an estimate of the reliability, testability, and maintainability of a program, based on measuring the number of linearly independent paths through the program. Procedural (Traditional) Software Metrics (Cont.) Function Point is a measure of the size of computer applications and the projects that build them. Object-Oriented Software Metrics • Weighted-methods-per-class (WMC) – the sum of the individual complexities of the methods within that class. • Depth of inheritance tree (DIT) – defined as the maximum length from the node to the root of a class tree. Deeper a class is in the inheritance hierarchy, more complex it gets. • Number of Children (NOC) – Immediate subclasses of class. Large NOC implies great amount of inheritance and resue. • Coupling between object classes (CBO) – When a class inherits methods, instance variables, they are coupled. Greater number = complexity Object-Oriented Software Metrics • Number of key classes (NKC) • Number of subsystems (NSUB) • Class size (CS) • Number of operations added by a subclass (NOA) • Average method size • Average number of instance variables • Class hierarchy nesting level Which Software-Testing Tool to use? • Does it offer critical support for planning tests and monitoring test progress? • Does it have an analysis feature where it assesses the characteristics of the software quality? • Does it offer guiding dynamic testing? • How mature is the tool? Is it easy to implement for your system? Metrics for Tools that support testing procedure software • Human Interface Design (HID) – Tools with well-designed human interfaces enable easy, efficient, and accurate setting of tool configuration. • Tool Management (TM) – the tool should ensure proper management of information. • Ease of Use (EU) – the tool should be easy to use by both new and familiar users. • User Control (UC) – the tool should allow extensive and detail testing coverage rather than one bulky one. 3 Tools for Software Testing •LDRA Testbed •Parasoft Testbed C++ Test CodeWizard Inspire++ •Telelogic Testbed Logiscope LRDA Testbed • Coverage Report (Dynamic Analysis) Branch Coverage Statement Coverage • Metrics Cyclomatic Complexity (Static Analysis) • Quality Report LRDA Testbed – Branch/Decision coverage Part 1 (Part of dynamic testing) LRDA Testbed – Code/branch/decision coverage Part 2 (Part of dynamic testing) Parasoft Testbed • C++ Test White-Box Black-Box Regression testing • Code Wizard 170 industry-accepted C/C++ coding standards •Inspire++ C/C++ runtime error checking Parasoft Testbed (metrics) Parasoft Testbed C++ Test Bug Detective (static analysis) Telelogic Testbed • Logiscope • TestChecker – mentioned in the article • RuleChecker – mentioned in the article • Audit * • Reviewer * * included in the current version of the tool and shown for completeness but not covered further in the slides. Telelogic Logiscope – Bought by IBM – The current version is Rational Telelogic Logiscope Exercising the Software-Testing Tools (Comparison of the tools themselves) • Human Interface Design (HID) Comparison • Keyboard-to-mouse switches (KMS) • Input fields per functions (IFPF) • Average length of input fields (ALIF) • Button recognition factor (BR) Exercising the Software-Testing Tools (Comparison of the tools themselves) Test case generation (TCG) Automated test case generation (ATG) Test case reuse functionality (TRF) Special note: LDRA does not automatically generate test cases but does provide user-friendly features such as pull-down menus for created test cases therefore it was assigned an eight for its level of ATG. Analysis of Results (The output of the tools) LRDA – For Object Oriented tests there were issues with the tool, so no results were obtained. High levels of knots indicate that the code is disjointed LDRA appends the Motor Industry Software Reliability Association (MISRA) C Standard and the Federal Aviation Authority’s DO-178B standard. Importance of this article • Software Metrics have come a long way since the LOC era. • Software Metrics can be use not only to measure the quality of software, but also the effectiveness of the software testing tool. • Choosing a software testing tool is not simple.

Metrics for Measuring the Efectiveness of Software-Testing Tools

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