Software Metrics and Measurement Case Studies

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As mentioned, software architects need to address two distinct areas in this context: architectural quality indicators internal quality , and quality attributes external quality [ 5 ]. Internal quality improvements require thorough analysis regarding their impact on external quality. Economy : Following the Keep it simple, stupid! KiSS principle, a software architecture should contain those artifacts that are required to achieve the development goals. That is, the architecture should be simple but not simplistic. Visibility : All parts of the architecture should be easily comprehensible, which also implies that all architectural components and dependencies must not be implicit.

Spacing : Good separation of concerns is important to map responsibilities efficiently and effectively to architectural entities. Lack of symmetry indicates that there might be problems in the design.


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Emergence : The whole is more than the sum of its parts. It is more effective to rely on simple constituents from which complex functionality can emerge than to centralize the same functionality in complex, heavyweight artifacts. As with architecture smells, architecture quality indicators point to possible problems. However, an indicator is not a proof of bad internal quality. Architects should keep that in mind when they discover these indicators. A refactoring can improve both developmental qualities, such as modifiability, and operational qualities, such as performance.

For example, unnecessary abstractions or dependencies will inevitably decrease modifiability. Applying refactoring patterns to get rid of these unnecessary artifacts will help improve modifiability.

Software: Articles, Research, & Case Studies on Software– HBS Working Knowledge

Unnecessary indirection layers might also cause performance penalties. If a refactoring pattern can make the indirection layer obsolete, its application will increase performance.

SWE 469: Software Metrics

Architects should explicitly keep track of sensitivity points and tradeoff points, because these are potential risk areas. Applying refactoring patterns that affect tradeoff points especially requires thorough considerations.

Software metrics and measurement

In this chapter we provide an overview of several approaches for the evaluation of self-adaptive systems available in the scientific literature. We have grouped them based on the evaluation mechanisms they use: quality attributes and software metrics. We have chosen this criterion because it matches best the description of each approach with the presentation provided by its authors and because it enables us to describe each approach only once.

The other four criteria do not allow us to easily divide the considered approaches in disjoint groups. Further, we describe the approaches belonging to each group through the main elements of the taxonomy proposed in this section. Michael English, Collins, in Software Quality Assurance , Measurement in software engineering facilitates quantification of the products e. However, Fenton and Neil also state that software measurement has not gained widespread acceptance within software organizations.

As a result, this area of research needs to be expanded and its usefulness in the practice of software development needs to be established.


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Like Fenton and Neil, they highlighted the need for metrics to be simple and easily computable, but also programming language independent and clearly defined and objective; a guideline increasingly being adopted by the community Sarkar et al. In this chapter we adopt these criteria by using simple and clearly defined metrics which are OO programming language independent, to investigate the use of software metrics for classes and modules to provide insights on the modularity of large-scale software. Shaowei Wang, Shang et al. They investigated several case studies to analyze the potential of the MapReduce platform to scale up tools for mining software repositories, including 1 J-REX, which mines a CVS repository for calculating changes of software metrics over the history of a software project, 2 CC-Finder, which is a token-based clone detection tool designed to extract code clones from systems developed in several programming languages, and 3 JACK, which is a log analyzer that uses data mining techniques to process system execution logs and automatically identify problems in load tests.

Specification mining approaches are not covered in these studies. Recently, Dyer et al.

Collecting and Accessing Data on Metrics - Key Business Metrics - Product Design - Udacity

Different from these studies, we specifically focus on specification mining algorithms and investigate the potential of using MapReduce to make them more scalable. Fabio Palomba, Rocco Oliveto, in Advances in Computers , Classes affected by this anti-pattern are characterized by complex methods, with no parameters, interacting between them using instance variables.

Why metrics don't matter in software development (unless you pair them with business goals)

As for the Functional Decomposition anti-pattern, this is also a symptom of procedural-style programming [3]. The Spaghetti Code anti-pattern describes source code difficult to comprehend by a developer, often without a well-defined structure and with several long methods without any parameter. From a lexical point of view, classes affected by this anti-pattern have usually procedural names. DECOR [13] is also able to identify Spaghetti Code, once again by using a specific rule card that describes the anti-pattern through structural properties.

As you can see in Fig. This is possible simply because the Spaghetti Code does not involve any relationships with other classes, but it is a design problem concentrated in a single class having procedural characteristics. Specifically, in DECOR instances of Spaghetti Code are found looking for classes having at least one long method, namely a method composed by a large number of LOC and declaring no parameters.

At the same time, the class does not present characteristics of Object-Oriented design.

How Software Metrics Lack Clarity

For example, the class does not use the concept of inheritance and should use many global variables. Figure 4. However, a better detection of this kind of anti-pattern could be possible through the use of some lexical rules. Since a class affected by Spaghetti Code is a class built through procedural thinking, the use of lexical rules can be complementary to the structural rules used by DECOR.

For example, the same strategy applied for Functional Decomposition can be applied here: checking the prefix of the class name can aid the identification of this anti-pattern. We use cookies to help provide and enhance our service and tailor content and ads. By continuing you agree to the use of cookies. Sign In Help.

Download as PDF. Set alert. About this page. Learn more about Software Metric. Khoshgoftaar, in Advances in Computers , 5. From software data to software theory J. Whitehead, in Perspectives on Data Science for Software Engineering , Pathways of Software Repository Research In software repository analysis, researchers use or create tools to make a local copy of project data, and then compute software metrics or software relationship networks.

Investigating software modularity using class and module level metrics Michael English, Collins, in Software Quality Assurance , 8. Software Metrics: A Rigorous and Practical Approach 2nd edition But the gap between how we do measure and how we could measure is still larger than it The theory is liberally illustrated with case studies and examples to illustrate the. Different reasons for software measurement: To assess software products To The only effective way of doing this is via measurement-based case studies.

Software testing metrics are a way to measure and monitor your test activities. Example: Time taken to run a set of test cases in a suite. Predictive Metrics. Software metrics don't matter unless you tie them to business goals. Learn what to measure, and how to use the results to test a business value That means that it would take 52 million test cases to fully exercise every path through the code. You could. Get fresh whitepapers, reports, case studies, and articles weekly. Software-systems development and software-engineering measurements have to similarly simple metrics such as basic Halstead metrics; case studies have.

Toggle navigation. Click here to read a case study. Can track staff performance and measure against organizational goals.

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A draft methodology to design a software measurement standard etalon.. A software metric is a standard way of measuring some Learn more about software engineering Listen critically to reports case studies of success with. Measurement theory overview of software metrics, basics of measurement. Also, some templates and particularly useful case studies are available from the. For smaller companies where customer retention is important, using metrics to better the software development process and improve on overall project quality, delivery time, etc will make the customers happy which may lead to continued business.

Source Byte Size is a measure of the actual size of the source code data e. It measures the file size vs. The byte size of the source code would vary greatly depending on which programming language was used to develop it. If we were to compare executable byte size of programs written in different languages we would see that there would be a difference too. The compiler compiles source code into byte code so different compilers would give out different executable file sizes.

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