JayWalker is an open-source build and deployment analysis tool which interrogates a Java application's compiled artifacts and generates static and interactive graphical reports from it. In turn, a software professional can interpret and use these reports to improve software quality and to understand the current state of the software application in question.
Although there are quite a few dependency analysis tools on the market, JayWalker is different because:
* It walks the class files rather than the source files
* It can interrogate nested archives (i.e. a JAR within a WAR within an EAR file)
* It can detect a variety of conflicts that can be identified at build and deployment time in an effort to minimize runtime dependency errors.
* It can be incorporated into a continuous integration solution so conflicts can be identified as they are introduced into source code control rather than addressing errors at runtime.
* It can be run standalone via the commandline on a system which just has a JRE installed
* Other dependency tools are package or class specific. JayWalker has support for archives, packages, and classes.
* Report attributes can be toggled on or off
* Walking across classlist elements can be done in several different ways:
o Deep (default) - recursively follow all paths
o Shallow - recursively follow paths up to and including a boundary element
o System - recursively follow paths up to a boundary element which is not part of the deployment, but is provided by a server or environment.
A. Hoegh, and B. Moskal. FIE'09: Proceedings of the 39th IEEE international conference on Frontiers in education conference, page 1306--1311. Piscataway, NJ, USA, IEEE Press, (2009)Instrumentti asenteiden tutkimukseen CS- ja insinööriopiskelijoilla..
A. Hotho, R. Jäschke, C. Schmitz, and G. Stumme. Proc. First International Conference on Semantics And Digital Media Technology (SAMT), volume 4306 of Lecture Notes in Computer Science, page 56-70. Berlin, Heidelberg, Springer, (2006)
A. Clauset, C. Shalizi, and M. Newman. (2007)cite arxiv:0706.1062
Comment: 43 pages, 11 figures, 7 tables, 4 appendices; code available at
http://www.santafe.edu/~aaronc/powerlaws/.
R. Kumar, J. Novak, and A. Tomkins. KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, page 611--617. New York, NY, USA, ACM, (2006)