plusFORT Quality Assurance
Many people know plusFORT mainly for SPAG, the restructuring tool which unscrambles spaghetti code. However, the plusFORT quality assurance facilities are arguably of even greater importance to most users.
plusFORT Version 7 is unique among QA tools in offering three distinct and complementary approaches to the problem of software quality assurance. Working together these three approaches have far more impact than any one could by itself.
GXCHK is the plusFORT global static analysis tool. GXCHK views data usage from a global perspective, and detects errors and anomalies that compilers and other tools miss. Examples are:
- Subprogram argument mismatch or misuse (e.g. constant actual argument is illegally modified by subprogram).
- COMMON and/or MODULE variables assigned a value but never used, or used but never assigned a value.
- Globally unused COMMON or MODULE variables, COMMON blocks, PARAMETERs, & INCLUDE files.
- Inconsistent COMMON block definitions.
- COMMON or MODULE variable name appears in other contexts (e.g. as a local variable, or in a different COMMON).
Version 7 of plusFORT introduces greatly improved HTML static analysis reports, with comprehensive cross-reference links. These reports are designed to act as a constant companion to coders, providing instant answers to questions like “where is this variable set” and “where is this routine called from”. A new “modularization report” shows how a traditional Fortran 77 program can be reorganised using modules and/or internal subprograms to take full advantage of the modular programming features of Fortran 95 and Fortran 2003.
Try the new GXCHK report interface by clicking here. This report shows an analysis of AERMOD.f90, one of the Polyhedron benchmarks. This file has 50K lines of Fortran 90, but much larger programs (many millions of lines) can be analysed and viewed in this way. Note that most browsers allow you to right-click on links to save particular reports in a separate tab.plusFORT also computes complexity metrics for each subprogram. These figures may help to indicate where rationalisation work should be concentrated.
An unusual feature of GXCHK is its ability to analyse local and global data together. For example, if a local variable in subprogram A has the same name as a COMMON variable in subprogram B, it could be that the programmer has omitted the relevant COMMON statement from subprogram A. GXCHK, unlike other static analysers spots this problem. GXCHK also produces a call tree, and concise but comprehensive charts showing where and how each symbol is used. Handy aggregated reports are produced for COMMON blocks and INCLUDE files.
Interface specifications for every subprogram, showing calls in and out, dummy arguments, PARAMETERs, COMMON and MODULE variables usage etc., can also be produced, and, optionally, embedded as comments back into the original source code.
GXCHK operates in a “compile & link” style which allows reports to be updated with minimal source code analysis. AUTOMAKE can be used to automate the process.
A big advantage of static analysis is that it can check all your code without regard to whether or not it is actually executed in a particular run. On the other hand, static analysis cannot take account of subtleties in program control flow, or the varying nature on input data. Neither can it cannot monitor the status of individual array elements. Arrays are treated as amorphous blobs of data.
If a bug is defined as “an incorrect value in a storage location” then there is a large subset (perhaps 30%) which can be defined as “an undefined value in a storage location”, and many of the remainder may cause that condition as a knock-on effect.
The Dynamic Analysis option of plusFORT is a tool for diagnosing these errors at run-time. A test version of your program is created, which detects any use of an undefined variable or array element, and logs it to a file. In other respects, the test program behaves exactly like the original. This is done by inserting calls to probe routines in the source code before any operation which depends on the value of a data item. The program is compiled and linked in the normal way, and the executable code appears to the user to operate in exactly the same way as the original. However, if a probe detects an undefined data item, it writes details to a log-file for later analysis. Source code for the probe routines is supplied.
A static analyser such as GXCHK can detect a few of these errors, but the majority can only be detected at run-time. Dynamic analysis takes account of program control flow, works with real data, and can monitor individual bytes if required. However it only validates the code which is executed in a particular run. This makes it an almost precise complement of static analysis – each excels where the other is deficient.
|Feature||Static Analysis||Dynamic Analysis|
|Checks code whether or not it executes||Yes||No|
|Checks for unsafe/questionable source code||Yes||No|
|Identifies used before set error||Sometimes||Yes|
|Checks status of individual array elements||No||Yes|
|Handles dependence on external data||No||Yes|
|Effective with dummy args, EQUIVALENCE||poor||Yes|
Dynamic analysis excels at detecting bugs which depend on external data, or on the use of arrays. These characteristics defeat conventional analysers.
Dynamic Analysis – Worked Example
SUBROUTINE QKNUM(Ival,Pos) INTEGER Ival , Pos , vals(50) , ios READ(11,*,IOSTAT=ios) vals IF ( ios.EQ.0 ) THEN DO Pos = 1 , 50 IF ( Ival.EQ.vals(Pos) ) GOTO 100 ENDDO ENDIF Pos = 0 100 END
QKNUM reads 50 numbers, and returns the position (Pos) of the first with value Ival.
If the data file contains “2,9,,11,20*44,26*“, the READ statement leaves some elements of vals undefined, and QKNUM behaves unpredictably.
Code with Dynamic Analysis Probes
SUBROUTINE QKNUM(Ival,Pos) INTEGER Ival , Pos , vals(50) , ios CALL SB$ENT('QKNUM','DYNBEF.FOR') <-- initialize traceback and timing CALL UD$I4(IOS) <-- set variable IOS to undefined CALL UD$AI4(50,VALS) <-- set array VALS to undefined READ (11,*,IOSTAT=ios) vals CALL QD$I4('IOS',IOS,4) IF ( ios.EQ.0 ) THEN DO Pos = 1 , 50 CALL QD$I4('VALS(POS)',VALS(POS),6) <-- check that VALS(IPOS) is defined before use CALL QD$I4('IVAL',IVAL,6) <-- check that IVAL is defined before use IF ( Ival.EQ.vals(Pos) ) GOTO 99999 ENDDO ENDIF Pos = 0 99999 CALL SB$EXI <-- for traceback and timing data END
XTOP2(I+J) value is undefined subprogram FCOMP line 838 file JASO.FOR subprogram VSCAN line 4255 file JASO.FOR subprogram VUTREE line 1049 file JASO.FOR ICHR value is undefined subprogram VSTOP line 6682 file JASO.FOR subprogram JASO line 2241 file JASO.FOR
A reasonable goal for a software test suite is to ensure that every line of source code is executed at least once. The plusFORT coverage analysis facility allows users to monitor progress against this goal, as well as identifying “hot-spots” – the sections of code which are executed most frequently, and which have most effect on program execution time.
The plusFORT coverage analysis facility places probes into Fortran source code which allow users to monitor the effectiveness of testing. At the end of each run, the probes update the coverage statistics for each source file. This data may be analysed at any time using the CVRANAL tool. CVRANAL identifies untested code blocks, and execution hot-spots.
In addition, CVRANAL can annotate your source code as shown below. The annotations are comments and do not affect the validity of the source code.
Fragment of CVRANAL Test Coverage Report
4 Untested code blocks in subprogram MOO in file TESTMOO.BEF at lines 27 32 33 62 NO Untested code blocks in subprogram BC in file TESTMOO.BEF NO Untested code blocks in subprogram GETNUM in file TESTMOO.BEF NO Untested code blocks in subprogram INIT in file TESTMOO.BEF
Fragment of CVRANAL Execution Hot-spot Report
49682 : IF(IGUESS(IDIG).NE.IANS(JDIG))GOTO 10 : in s/prog BC at line 82 of TESTMOO.BEF 16336 : IF(IGUESS(IDIG).EQ.IANS(IDIG))GOTO 40 : in s/prog BC at line 80 of TESTMOO.BEF 14399 : DO 10 JDIG=1,NDIGIT : in s/prog BC at line 81 of TESTMOO.BEF 11283 : 10 IF(J.EQ.NUM(JDIG))GOTO 20 : in s/prog GETNUM at line 104 of TESTMOO.BEF 9039 : GOTO 20 : in s/prog BC at line 86 of TESTMOO.BEF
Annotated Source Code
SUBROUTINE BC(IGUESS,IANS,NBULLS,NCOWS) PARAMETER (NDIGIT=4,MINDIG=1,MAXDIG=9) DIMENSION IGUESS(NDIGIT),IANS(NDIGIT) NBULLS=0 ! 4084 NCOWS=0 DO 20 IDIG=1,NDIGIT IF(IGUESS(IDIG).EQ.IANS(IDIG))GOTO 40 ! 16336 DO 10 JDIG=1,NDIGIT ! 14399 IF(IGUESS(IDIG).NE.IANS(JDIG))GOTO 10 ! 49682 NCOWS=NCOWS+1 ! 5360 GOTO 20 10 CONTINUE GOTO 20 ! 9039 40 NBULLS=NBULLS+1 ! 1937 20 CONTINUE RETURN ! 4084 END
The Next Steps
Ready To Buy?
What do our Customers say about us?
At 13-years old, my daughter’s research manuscript has been accepted for publication in a top tier peer-reviewed Environmental Science journal and OriginPro 8.6 will allow her to export the graphs in a wide variety of formats which can meet any publisher’s requirements. Kudos to OriginLab for designing innovative and intuitive software that can span the needs of both a burgeoning young scientist like my daughter to a PhD expert in their field. It is hard to imagine that other products offer this extraordinary level of user versatility.Michael Grimmett, MD, FACP, FACS Ophthalmologist Palm Beach Gardens, Florida
Excellent! Very much appreciated how the content was tailored to our needs.
I have greatly appreciated your help, your restraint in response to some daft questions and your sheer professionalism.PL, Tunbridge Wells, UK
Bob delivered an engaging and interesting course. His style was very enjoyable.
For the time being we are unable to offer the following product ranges although we are currently working hard to increase the number of products we can offer in the future. Please contact us to talk about alternative products that we may be able to offer you.