Let the Machines Take Over
Here are some statistics about how useful automation can be and give you some ammunition when you confront management about the need for these tools.
These results have been generated by Capers Jones who has been collecting data for over 15,000 projects for about 40 years. Full results shown in the paper in the references.
Requirements AnalysisThere have been tools available for tracing requirements for quite some time. Generally the only companies forced to provide requirements traceability, but this makes sense to do on all large projects:
Automated requirements tracing can raise productivity by 12.89% and quality by 17.8%
There are tools that can help size programs in terms of function points, which then allows you to get relatively accurate estimates of a project`s cost and time before the project is executed.
Automated sizing in function points can raise productivity by 16.5% and quality by 23.7%
DevelopmentThere are several tools that are useful during development, but by far the biggest bang for your buck comes in the form of automated static analysis.
Automated static analysis can raise productivity by 20.9% and quality by 30.9%
Then getting cyclomatic complexity counts for your code can be done in an automated fashion. Studies have shown that files with a count of 74+ were 98% likely to have defects.
Automated cyclomatic complexity analysis can raise productivity by 14.5% and quality by 19.5%
Performance is a tricky thing, we will talk about it often but rarely do we actually do something about it. Automated performance analysis allows you to determine if there will be production problems before deploying new code.
Automated performance analysis can raise productivity by 12.5% and quality by 19.5%
There are tools for restructuring code automatically, many of these are built directly into today's IDEs. There are many stand alone tools for automated restructuring, some are shown here.
Automated restructuring can raise productivity by 8.0% and quality by 11.7%
Automated unit testing is the easiest way to detect defects early. If your developers are using Test Driven Development (TDD) and any continuous integration tool (i.e, Hudson or Jenkins) then you can find out with each build if a defect has crept into the code.
Automated unit testing can raise productivity by 16.5% and quality by 23.8%
TestingBelieve it or not I was working with a team that was not using version control or defect tracking last year. So there are clearly still some organizations not using defect tracking.
Automated defect tracking can raise productivity by 17.5% and quality by 25.9%
Testing the percentage of the application pathways that are actually being tested is critical. Most of your defects will lie in the pathways that you can not test.
Automated test coverage analysis can raise productivity by 15.5% and quality by 21.2%
Test cases can be generated automatically in some situations.
Automated test case generation can raise productivity by 15.0% and quality by 20.0%
DeploymentThe next two tools are not about technology that you acquire, rather it is about building tools to support critical deployment functions. When the pressure is on it is tough to think about creating applications to manage configuration in an automated way. When management tells you that it would be a luxury to build these tools then show them these results.
Some organizations rely on manually updating configurations, but can be error prone if there are many values to update.
Automated configuration control can raise productivity by 16.4% and quality by 23.5%
Also, when automated configuration tools don`t exist then you often don`t have automated deployment tools.
Automated deployment support can raise productivity by 14.6% and quality by 19.6%
ConclusionOne of the most cost effective ways to improve productivity and quality in your software development is to automate any of the issues above. In most cases you can find a vendor that will provide you support; for deployment you can make the case that building automated tools is the way to go!
- Egyed, Alexander and Grunabacher, Paul, Supporting Software Understanding with Automated Requirements Traceability
- Jones, Capers. SCORING AND EVALUATING SOFTWARE METHODS, PRACTICES, AND RESULTS. 2008.1
- Marjchrzak, T.A., Automated Test Case Generation Based on Coverage Analysis
- Rushby, John. Automated Test Generation and Verified Software.
1N.B. All productivity and quality percentages were derived over 15,000+ actual projects
(Note: Opinions expressed in this article and its replies are the opinions of their respective authors and not those of DZone, Inc.)